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Python - Basic Syntax
The Python language has many similarities to Perl, C, and Java. However, there are some definite
differences between the languages. This chapter is designed to quickly get you up to speed on the syntax
that is expected in Python.
First Python Program:
Interactive Mode Programming:
Invoking the interpreter without passing a script file as a parameter brings up the following prompt:
$ python
Python 2.5 (r25:51908, Nov 6 2007, 16:54:01)
[GCC 4.1.2 20070925 (Red Hat 4.1.2-27)] on linux2
Type "help", "copyright", "credits" or "license" for more info.
>>>
Type the following text to the right of the Python prompt and press the Enter key:
>>> print "Hello, Python!";
NOTE: If you are running new version of Python then you would need to use print statement with
parenthisis like print ("Hello, Python!");
This will produce following result:
Hello, Python!
Script Mode Programming :
Invoking the interpreter with a script parameter begins execution of the script and continues until the
script is finished. When the script is finished, the interpreter is no longer active.
Let us write a simple Python program in a script. All python files will have extension .py. So put the
following source code in a test.py file.
#!/usr/bin/python
print "Hello, Python!";
Here I assumed that you have Python interpreter available in /usr/bin directory. Now try to run this
program as follows:
$ chmod +x test.py
$ python test.py
# This is to make file executable
3/22/2011 5:21 PM](https://image.slidesharecdn.com/pythontutorial-140127010149-phpapp02/75/Python-tutorial-8-2048.jpg)
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Statements in Python typically end with a new line. Python does, however, allow the use of the line
continuation character () to denote that the line should continue. For example:
total = item_one +
item_two +
item_three
Statements contained within the [], {}, or () brackets do not need to use the line continuation character.
For example:
days = ['Monday', 'Tuesday', 'Wednesday',
'Thursday', 'Friday']
Quotation in Python:
Python accepts single ('), double (") and triple (''' or """) quotes to denote string literals, as long as the
same type of quote starts and ends the string.
The triple quotes can be used to span the string across multiple lines. For example, all the following are
legal:
word = 'word'
sentence = "This is a sentence."
paragraph = """This is a paragraph. It is
made up of multiple lines and sentences."""
Comments in Python:
A hash sign (#) that is not inside a string literal begins a comment. All characters after the # and up to
the physical line end are part of the comment, and the Python interpreter ignores them.
#!/usr/bin/python
# First comment
print "Hello, Python!";
# second comment
This will produce following result:
Hello, Python!
A comment may be on the same line after a statement or expression:
name = "Madisetti" # This is again comment
You can comment multiple lines as follows:
#
#
#
#
This is a comment.
This is a comment, too.
This is a comment, too.
I said that already.
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Using Blank Lines:
A line containing only whitespace, possibly with a comment, is known as a blank line, and Python totally
ignores it.
In an interactive interpreter session, you must enter an empty physical line to terminate a multiline
statement.
Waiting for the User:
The following line of the program displays the prompt, Press the enter key to exit. and waits for the user
to press the Enter key:
#!/usr/bin/python
raw_input("nnPress the enter key to exit.")
Here "nn" are being used to create two new lines before displaying the actual line.
Once the user presses the key, the program ends. This is a nice trick to keep a console window open until
the user is done with an application.
Multiple Statements on a Single Line:
The semicolon ( ; ) allows multiple statements on the single line given that neither statement starts a
new code block. Here is a sample snip using the semicolon:
import sys; x = 'foo'; sys.stdout.write(x + 'n')
Multiple Statement Groups as Suites:
Groups of individual statements making up a single code block are called suites in Python.
Compound or complex statements, such as if, while, def, and class, are those which require a header line
and a suite.
Header lines begin the statement (with the keyword) and terminate with a colon ( : ) and are followed by
one or more lines which make up the suite.
Example:
if expression :
suite
elif expression :
suite
else :
suite
Command Line Arguments:
You may have seen, for instance, that many programs can be run so that they provide you with some
basic information about how they should be run. Python enables you to do this with -h:
$ python .h
usage: python [option]...[-c cmd | -m mod | file | -] [arg]..
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Options and arguments (and corresponding environment variables):
-c cmd : program passed in as string (terminates option list)
-d
: debug output from parser (also PYTHONDEBUG=x)
-E
: ignore environment variables (such as PYTHONPATH)
-h
: print this help message and exit (also --help)
[ etc. ]
You can also program your script in such a way that it should accept various options. Command Line
Arguments is an advanced topic and should be studied a bit later once you have gone through rest of the
Python concepts.
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Copyright © tutorialspoint.com
Python - Basic Syntax
The Python language has many similarities to Perl, C, and Java. However, there are some definite
differences between the languages. This chapter is designed to quickly get you up to speed on the syntax
that is expected in Python.
First Python Program:
Interactive Mode Programming:
Invoking the interpreter without passing a script file as a parameter brings up the following prompt:
$ python
Python 2.5 (r25:51908, Nov 6 2007, 16:54:01)
[GCC 4.1.2 20070925 (Red Hat 4.1.2-27)] on linux2
Type "help", "copyright", "credits" or "license" for more info.
>>>
Type the following text to the right of the Python prompt and press the Enter key:
>>> print "Hello, Python!";
NOTE: If you are running new version of Python then you would need to use print statement with
parenthisis like print ("Hello, Python!");
This will produce following result:
Hello, Python!
Script Mode Programming :
Invoking the interpreter with a script parameter begins execution of the script and continues until the
script is finished. When the script is finished, the interpreter is no longer active.
Let us write a simple Python program in a script. All python files will have extension .py. So put the
following source code in a test.py file.
#!/usr/bin/python
print "Hello, Python!";
Here I assumed that you have Python interpreter available in /usr/bin directory. Now try to run this
program as follows:
$ chmod +x test.py
$ python test.py
# This is to make file executable
3/22/2011 5:21 PM](https://image.slidesharecdn.com/pythontutorial-140127010149-phpapp02/75/Python-tutorial-14-2048.jpg)
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Statements in Python typically end with a new line. Python does, however, allow the use of the line
continuation character () to denote that the line should continue. For example:
total = item_one +
item_two +
item_three
Statements contained within the [], {}, or () brackets do not need to use the line continuation character.
For example:
days = ['Monday', 'Tuesday', 'Wednesday',
'Thursday', 'Friday']
Quotation in Python:
Python accepts single ('), double (") and triple (''' or """) quotes to denote string literals, as long as the
same type of quote starts and ends the string.
The triple quotes can be used to span the string across multiple lines. For example, all the following are
legal:
word = 'word'
sentence = "This is a sentence."
paragraph = """This is a paragraph. It is
made up of multiple lines and sentences."""
Comments in Python:
A hash sign (#) that is not inside a string literal begins a comment. All characters after the # and up to
the physical line end are part of the comment, and the Python interpreter ignores them.
#!/usr/bin/python
# First comment
print "Hello, Python!";
# second comment
This will produce following result:
Hello, Python!
A comment may be on the same line after a statement or expression:
name = "Madisetti" # This is again comment
You can comment multiple lines as follows:
#
#
#
#
This is a comment.
This is a comment, too.
This is a comment, too.
I said that already.
3/22/2011 5:21 PM](https://image.slidesharecdn.com/pythontutorial-140127010149-phpapp02/75/Python-tutorial-17-2048.jpg)
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Using Blank Lines:
A line containing only whitespace, possibly with a comment, is known as a blank line, and Python totally
ignores it.
In an interactive interpreter session, you must enter an empty physical line to terminate a multiline
statement.
Waiting for the User:
The following line of the program displays the prompt, Press the enter key to exit. and waits for the user
to press the Enter key:
#!/usr/bin/python
raw_input("nnPress the enter key to exit.")
Here "nn" are being used to create two new lines before displaying the actual line.
Once the user presses the key, the program ends. This is a nice trick to keep a console window open until
the user is done with an application.
Multiple Statements on a Single Line:
The semicolon ( ; ) allows multiple statements on the single line given that neither statement starts a
new code block. Here is a sample snip using the semicolon:
import sys; x = 'foo'; sys.stdout.write(x + 'n')
Multiple Statement Groups as Suites:
Groups of individual statements making up a single code block are called suites in Python.
Compound or complex statements, such as if, while, def, and class, are those which require a header line
and a suite.
Header lines begin the statement (with the keyword) and terminate with a colon ( : ) and are followed by
one or more lines which make up the suite.
Example:
if expression :
suite
elif expression :
suite
else :
suite
Command Line Arguments:
You may have seen, for instance, that many programs can be run so that they provide you with some
basic information about how they should be run. Python enables you to do this with -h:
$ python .h
usage: python [option]...[-c cmd | -m mod | file | -] [arg]..
3/22/2011 5:21 PM](https://image.slidesharecdn.com/pythontutorial-140127010149-phpapp02/75/Python-tutorial-18-2048.jpg)
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Options and arguments (and corresponding environment variables):
-c cmd : program passed in as string (terminates option list)
-d
: debug output from parser (also PYTHONDEBUG=x)
-E
: ignore environment variables (such as PYTHONPATH)
-h
: print this help message and exit (also --help)
[ etc. ]
You can also program your script in such a way that it should accept various options. Command Line
Arguments is an advanced topic and should be studied a bit later once you have gone through rest of the
Python concepts.
Copyright © tutorialspoint.com
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Standard Data Types:
The data stored in memory can be of many types. For example, a person.s age is stored as a numeric
value and his or her address is stored as alphanumeric characters.
Python has some standard types that are used to define the operations possible on them and the storage
method for each of them.
Python has five standard data types:
Numbers
String
List
Tuple
Dictionary
Python Numbers:
Number data types store numeric values. They are immutable data types, which means that changing the
value of a number data type results in a newly allocated object.
Number objects are created when you assign a value to them. For example:
var1 = 1
var2 = 10
You can also delete the reference to a number object by using the del statement. The syntax of the del
statement is:
del var1[,var2[,var3[....,varN]]]]
You can delete a single object or multiple objects by using the del statement. For example:
del var
del var_a, var_b
Python supports four different numerical types:
int (signed integers)
long (long integers [can also be represented in octal and hexadecimal])
float (floating point real values)
complex (complex numbers)
Examples:
Here are some examples of numbers:
int
long
float
complex
10
51924361L
0.0
3.14j
100
-0x19323L
15.20
45.j
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-786
0122L
-21.9
9.322e-36j
080
0xDEFABCECBDAECBFBAEl
32.3+e18
.876j
-0490
535633629843L
-90.
-.6545+0J
-0x260
-052318172735L
-32.54e100
3e+26J
0x69
-4721885298529L
70.2-E12
4.53e-7j
Python allows you to use a lowercase L with long, but it is recommended that you use only an
uppercase L to avoid confusion with the number 1. Python displays long integers with an uppercase
L.
A complex number consists of an ordered pair of real floatingpoint numbers denoted by a + bj,
where a is the real part and b is the imaginary part of the complex number.
Python Strings:
Strings in Python are identified as a contiguous set of characters in between quotation marks.
Python allows for either pairs of single or double quotes. Subsets of strings can be taken using the slice
operator ( [ ] and [ : ] ) with indexes starting at 0 in the beginning of the string and working their way
from -1 at the end.
The plus ( + ) sign is the string concatenation operator, and the asterisk ( * ) is the repetition operator.
Example:
#!/usr/bin/python
str = 'Hello World!'
print
print
print
print
print
print
str
str[0]
str[2:5]
str[2:]
str * 2
str + "TEST"
#
#
#
#
#
#
Prints
Prints
Prints
Prints
Prints
Prints
complete string
first character of the string
characters starting from 3rd to 6th
string starting from 3rd character
string two times
concatenated string
This will produce following result:
Hello World!
H
llo
llo World!
Hello World!Hello World!
Hello World!TEST
Python Lists:
Lists are the most versatile of Python's compound data types. A list contains items separated by commas
and enclosed within square brackets ([]).
To some extent, lists are similar to arrays in C. One difference between them is that all the items
belonging to a list can be of different data type.
The values stored in a list can be accessed using the slice operator ( [ ] and [ : ] ) with indexes starting
at 0 in the beginning of the list and working their way to end-1.
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The plus ( + ) sign is the list concatenation operator, and the asterisk ( * ) is the repetition operator.
Example:
#!/usr/bin/python
list = [ 'abcd', 786 , 2.23, 'john', 70.2 ]
tinylist = [123, 'john']
print
print
print
print
print
print
list
#
list[0]
#
list[1:3]
#
list[2:]
#
tinylist * 2 #
list + tinylist
Prints complete list
Prints first element of the list
Prints elements starting from 2nd to 4th
Prints elements starting from 3rd element
Prints list two times
# Prints concatenated lists
This will produce following result:
['abcd', 786, 2.23, 'john', 70.200000000000003]
abcd
[786, 2.23]
[2.23, 'john', 70.200000000000003]
[123, 'john', 123, 'john']
['abcd', 786, 2.23, 'john', 70.200000000000003, 123, 'john']
Python Tuples:
A tuple is another sequence data type that is similar to the list. A tuple consists of a number of values
separated by commas. Unlike lists, however, tuples are enclosed within parentheses.
The main differences between lists and tuples are: Lists are enclosed in brackets ( [ ] ), and their
elements and size can be changed, while tuples are enclosed in parentheses ( ( ) ) and cannot be
updated. Tuples can be thought of as read-only lists.
Example:
#!/usr/bin/python
tuple = ( 'abcd', 786 , 2.23, 'john', 70.2
tinytuple = (123, 'john')
print
print
print
print
print
print
tuple
#
tuple[0]
#
tuple[1:3]
#
tuple[2:]
#
tinytuple * 2
#
tuple + tinytuple
)
Prints complete list
Prints first element of the list
Prints elements starting from 2nd to 4th
Prints elements starting from 3rd element
Prints list two times
# Prints concatenated lists
This will produce following result:
('abcd', 786, 2.23, 'john', 70.200000000000003)
abcd
(786, 2.23)
(2.23, 'john', 70.200000000000003)
(123, 'john', 123, 'john')
('abcd', 786, 2.23, 'john', 70.200000000000003, 123, 'john')
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Following is invalid with tuple, because we attempted to update a tuple,which is not allowed. Similar case
is possible with lists:
#!/usr/bin/python
tuple = ( 'abcd', 786 , 2.23, 'john', 70.2 )
list = [ 'abcd', 786 , 2.23, 'john', 70.2 ]
tuple[2] = 1000
# Invalid syntax with tuple
list[2] = 1000
# Valid syntax with list
Python Dictionary:
Python 's dictionaries are hash table type. They work like associative arrays or hashes found in Perl and
consist of key-value pairs.
Keys can be almost any Python type, but are usually numbers or strings. Values, on the other hand, can
be any arbitrary Python object.
Dictionaries are enclosed by curly braces ( { } ) and values can be assigned and accessed using square
braces ( [] ).
Example:
#!/usr/bin/python
dict = {}
dict['one'] = "This is one"
dict[2]
= "This is two"
tinydict = {'name': 'john','code':6734, 'dept': 'sales'}
print
print
print
print
print
dict['one']
dict[2]
tinydict
tinydict.keys()
tinydict.values()
#
#
#
#
#
Prints
Prints
Prints
Prints
Prints
value for 'one' key
value for 2 key
complete dictionary
all the keys
all the values
This will produce following result:
This is one
This is two
{'dept': 'sales', 'code': 6734, 'name': 'john'}
['dept', 'code', 'name']
['sales', 6734, 'john']
Dictionaries have no concept of order among elements. It is incorrect to say that the elements are "out of
order"; they are simply unordered.
Data Type Conversion:
Sometimes you may beed to perform conversions between the built-in types. To convert between types
you simply use the type name as a function.
There are several built-in functions to perform conversion from one data type to another. These functions
return a new object representing the converted value.
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Function
Description
int(x [,base])
Converts x to an integer. base specifies the base if x is a string.
long(x [,base] )
Converts x to a long integer. base specifies the base if x is a string.
float(x)
Converts x to a floating-point number.
complex(real [,imag])
Creates a complex number.
str(x)
Converts object x to a string representation.
repr(x)
Converts object x to an expression string.
eval(str)
Evaluates a string and returns an object.
tuple(s)
Converts s to a tuple.
list(s)
Converts s to a list.
set(s)
Converts s to a set.
dict(d)
Creates a dictionary. d must be a sequence of (key,value) tuples.
frozenset(s)
Converts s to a frozen set.
chr(x)
Converts an integer to a character.
unichr(x)
Converts an integer to a Unicode character.
ord(x)
Converts a single character to its integer value.
hex(x)
Converts an integer to a hexadecimal string.
oct(x)
Converts an integer to an octal string.
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Python - for Loop Statements
A loop is a construct that causes a section of a program to be repeated a certain number of times. The
repetition continues while the condition set for the loop remains true. When the condition becomes false,
the loop ends and the program control is passed to the statement following the loop.
This tutorial will discuss the for loop construct available in Python.
The for Loop:
The for loop in Python has the ability to iterate over the items of any sequence, such as a list or a string.
The syntax of the loop look is:
for iterating_var in sequence:
statements(s)
If a sequence contains an expression list, it is evaluated first. Then, the first item in the sequence is
assigned to the iterating variable iterating_var. Next, the statements block is executed. Each item in the
list is assigned to iterating_var, and the statements(s) block is executed until the entire sequence is
exhausted.
Note: In Python, all the statements indented by the same number of character spaces after a
programming construct are considered to be part of a single block of code. Python uses indentation as its
method of grouping statements.
Example:
#!/usr/bin/python
for letter in 'Python':
# First Example
print 'Current Letter :', letter
fruits = ['banana', 'apple', 'mango']
for fruit in fruits:
# Second Example
print 'Current fruit :', fruit
print "Good bye!"
This will produce following result:
Current
Current
Current
Current
Current
Current
Current
Current
Current
Letter : P
Letter : y
Letter : t
Letter : h
Letter : o
Letter : n
fruit : banana
fruit : apple
fruit : mango
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Good bye!
Iterating by Sequence Index:
An alternative way of iterating through each item is by index offset into the sequence itself:
Example:
#!/usr/bin/python
fruits = ['banana', 'apple', 'mango']
for index in range(len(fruits)):
print 'Current fruit :', fruits[index]
print "Good bye!"
This will produce following result:
Current fruit : banana
Current fruit : apple
Current fruit : mango
Good bye!
Here we took the assistance of the len() built-in function, which provides the total number of elements in
the tuple as well as the range() built-in function to give us the actual sequence to iterate over.
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Python - Numbers
Number data types store numeric values. They are immutable data types, which means that changing the
value of a number data type results in a newly allocated object.
Number objects are created when you assign a value to them. For example:
var1 = 1
var2 = 10
You can also delete the reference to a number object by using the del statement. The syntax of the del
statement is:
del var1[,var2[,var3[....,varN]]]]
You can delete a single object or multiple objects by using the del statement. For example:
del var
del var_a, var_b
Python supports four different numerical types:
int (signed integers): often called just integers or ints, are positive or negative whole numbers
with no decimal point.
long (long integers ): or longs, are integers of unlimited size, written like integers and followed
by an uppercase or lowercase L.
float (floating point real values) : or floats, represent real numbers and are written with a
decimal point dividing the integer and fractional parts. Floats may also be in scientific notation,
with E or e indicating the power of 10 (2.5e2 = 2.5 x 102 = 250).
complex (complex numbers) : are of the form a + bJ, where a and b are floats and J (or j)
represents the square root of -1 (which is an imaginary number). a is the real part of the number,
and b is the imaginary part. Complex numbers are not used much in Python programming.
Examples:
Here are some examples of numbers:
int
long
float
complex
10
51924361L
0.0
3.14j
100
-0x19323L
15.20
45.j
-786
0122L
-21.9
9.322e-36j
080
0xDEFABCECBDAECBFBAEl
32.3+e18
.876j
-0490
535633629843L
-90.
-.6545+0J
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-0x260
-052318172735L
-32.54e100
3e+26J
0x69
-4721885298529L
70.2-E12
4.53e-7j
Python allows you to use a lowercase L with long, but it is recommended that you use only an
uppercase L to avoid confusion with the number 1. Python displays long integers with an uppercase
L.
A complex number consists of an ordered pair of real floatingpoint numbers denoted by a + bj,
where a is the real part and b is the imaginary part of the complex number.
Number Type Conversion:
Python converts numbers internally in an expression containing mixed types to a common type for
evaluation. But sometimes, you'll need to coerce a number explicitly from one type to another to satisfy
the requirements of an operator or function parameter.
Type int(x)to convert x to a plain integer.
Type long(x) to convert x to a long integer.
Type float(x) to convert x to a floating-point number.
Type complex(x) to convert x to a complex number with real part x and imaginary part zero.
Type complex(x, y) to convert x and y to a complex number with real part x and imaginary part y.
x and y are numeric expressions
Built-in Number Functions:
Mathematical Functions:
Python includes following functions that perform mathematical calculations.
Function
Returns ( description )
abs(x)
The absolute value of x: the (positive) distance between x and zero.
ceil(x)
The ceiling of x: the smallest integer not less than x
cmp(x, y)
-1 if x < y, 0 if x == y, or 1 if x > y
exp(x)
The exponential of x: ex
fabs(x)
The absolute value of x.
floor(x)
The floor of x: the largest integer not greater than x
log(x)
The natural logarithm of x, for x> 0
log10(x)
The base-10 logarithm of x for x> 0 .
max(x1, x2,...)
The largest of its arguments: the value closest to positive infinity
min(x1, x2,...)
The smallest of its arguments: the value closest to negative infinity
modf(x)
The fractional and integer parts of x in a two-item tuple. Both parts have the
same sign as x. The integer part is returned as a float.
pow(x, y)
The value of x**y.
round(x [,n])
x rounded to n digits from the decimal point. Python rounds away from zero
as a tie-breaker: round(0.5) is 1.0 and round(-0.5) is -1.0.
sqrt(x)
The square root of x for x > 0
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Random Number Functions:
Random numbers are used for games, simulations, testing, security, and privacy applications. Python
includes following functions that are commonly used.
Function
Returns ( description )
choice(seq)
A random item from a list, tuple, or string.
randrange ([start,] stop
[,step])
A randomly selected element from range(start, stop, step)
random()
A random float r, such that 0 is less than or equal to r and r is less than 1
seed([x])
Sets the integer starting value used in generating random numbers. Call this
function before calling any other random module function. Returns None.
shuffle(lst)
Randomizes the items of a list in place. Returns None.
uniform(x, y)
A random float r, such that x is less than or equal to r and r is less than y
Trigonometric Functions:
Python includes following functions that perform trigonometric calculations.
Function
Description
acos(x)
Return the arc cosine of x, in radians.
asin(x)
Return the arc sine of x, in radians.
atan(x)
Return the arc tangent of x, in radians.
atan2(y, x)
Return atan(y / x), in radians.
cos(x)
Return the cosine of x radians.
hypot(x, y)
Return the Euclidean norm, sqrt(x*x + y*y).
sin(x)
Return the sine of x radians.
tan(x)
Return the tangent of x radians.
degrees(x)
Converts angle x from radians to degrees.
radians(x)
Converts angle x from degrees to radians.
Mathematical Constants:
The module also defines two mathematical constants:
Constant
Description
pi
The mathematical constant pi.
e
The mathematical constant e.
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Python - Strings
Strings are amongst the most popular types in Python. We can create them simply by enclosing
characters in quotes. Python treats single quotes the same as double quotes.
Creating strings is as simple as assigning a value to a variable. For example:
var1 = 'Hello World!'
var2 = "Python Programming"
Accessing Values in Strings:
Python does not support a character type; these are treated as strings of length one, thus also considered
a substring.
To access substrings, use the square brackets for slicing along with the index or indices to obtain your
substring:
Example:
#!/usr/bin/python
var1 = 'Hello World!'
var2 = "Python Programming"
print "var1[0]: ", var1[0]
print "var2[1:5]: ", var2[1:5]
This will produce following result:
var1[0]: H
var2[1:5]: ytho
Updating Strings:
You can "update" an existing string by (re)assigning a variable to another string. The new value can be
related to its previous value or to a completely different string altogether.
Example:
#!/usr/bin/python
var1 = 'Hello World!'
print "Updated String :- ", var1[:6] + 'Python'
This will produce following result:
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Updated String :-
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Hello Python
Escape Characters:
Following table is a list of escape or non-printable characters that can be represented with backslash
notation.
NOTE: In a doublequoted string, an escape character is interpreted; in a singlequoted string, an escape
character is preserved.
Backslash
notation
Hexadecimal
character
Description
a
0x07
Bell or alert
b
0x08
Backspace
cx
Control-x
C-x
Control-x
e
0x1b
Escape
f
0x0c
Formfeed
M-C-x
n
Meta-Control-x
0x0a
nnn
Newline
Octal notation, where n is in the range 0.7
r
0x0d
Carriage return
s
0x20
Space
t
0x09
Tab
v
0x0b
Vertical tab
x
Character x
xnn
Hexadecimal notation, where n is in the range 0.9, a.f, or A.F
String Special Operators:
Assume string variable a holds 'Hello' and variable b holds 'Python' then:
Operator
Description
Example
+
Concatenation - Adds values on either side of
the operator
a + b will give HelloPython
*
Repetition - Creates new strings,
concatenating multiple copies of the same
string
a*2 will give -HelloHello
[]
Slice - Gives the character from the given
index
a[1] will give e
[:]
Range Slice - Gives the characters from the
given range
a[1:4] will give ell
in
Membership - Returns true if a character
exists in the given string
H in a will give 1
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Symbol
Functionality
*
argument specifies width or precision
-
left justification
+
display the sign
<sp>
leave a blank space before a positive number
#
add the octal leading zero ( '0' ) or hexadecimal leading '0x' or '0X',
depending on whether 'x' or 'X' were used.
0
pad from left with zeros (instead of spaces)
%
'%%' leaves you with a single literal '%'
(var)
mapping variable (dictionary arguments)
m.n.
m is the minimum total width and n is the number of digits to display
after the decimal point (if appl.)
Triple Quotes:
Python's triple quotes comes to the rescue by allowing strings to span multiple lines, including verbatim
NEWLINEs, TABs, and any other special characters.
The syntax for triple quotes consists of three consecutive single or double quotes.
#!/usr/bin/python
para_str = """this is a long string that is made up of
several lines and non-printable characters such as
TAB ( t ) and they will show up that way when displayed.
NEWLINEs within the string, whether explicitly given like
this within the brackets [ n ], or just a NEWLINE within
the variable assignment will also show up.
"""
print para_str;
This will produce following result. Note how every single special character has been converted to its
printed form, right down to the last NEWLINE at the end of the string between the "up." and closing triple
quotes. Also note that NEWLINEs occur either with an explicit carriage return at the end of a line or its
escape code (n):
this is a long string that is made up of
several lines and non-printable characters such as
TAB (
) and they will show up that way when displayed.
NEWLINEs within the string, whether explicitly given like
this within the brackets [
], or just a NEWLINE within
the variable assignment will also show up.
Raw String:
Raw strings don't treat the backslash as a special character at all. Every character you put into a raw
string stays the way you wrote it:
#!/usr/bin/python
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4
encode(encoding='UTF-8',errors='strict')
Returns encoded string version of string; on error, default is to raise a ValueError unless errors is
given with 'ignore' or 'replace'.
5
endswith(suffix, beg=0, end=len(string))
Determines if string or a substring of string (if starting index beg and ending index end are given)
ends with suffix; Returns true if so, and false otherwise
6
expandtabs(tabsize=8)
Expands tabs in string to multiple spaces; defaults to 8 spaces per tab if tabsize not provided
7
find(str, beg=0 end=len(string))
Determine if str occurs in string, or in a substring of string if starting index beg and ending index
end are given; returns index if found and -1 otherwise
8
index(str, beg=0, end=len(string))
Same as find(), but raises an exception if str not found
9
isa1num()
Returns true if string has at least 1 character and all characters are alphanumeric and false
otherwise
10
isalpha()
Returns true if string has at least 1 character and all characters are alphabetic and false otherwise
11
isdigit()
Returns true if string contains only digits and false otherwise
12
islower()
Returns true if string has at least 1 cased character and all cased characters are in lowercase and
false otherwise
13
isnumeric()
Returns true if a unicode string contains only numeric characters and false otherwise
14
isspace()
Returns true if string contains only whitespace characters and false otherwise
15
istitle()
Returns true if string is properly "titlecased" and false otherwise
16
isupper()
Returns true if string has at least one cased character and all cased characters are in uppercase
and false otherwise
17
join(seq)
Merges (concatenates) the string representations of elements in sequence seq into a string, with
separator string
18
len(string)
Returns the length of the string
19
ljust(width[, fillchar])
Returns a space-padded string with the original string left-justified to a total of width columns
20
lower()
Converts all uppercase letters in string to lowercase
21
lstrip()
Removes all leading whitespace in string
22
maketrans()
Returns a translation table to be used in translate function.
23
max(str)
Returns the max alphabetical character from the string str
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min(str)
Returns the min alphabetical character from the string str
25
replace(old, new [, max])
Replaces all occurrences of old in string with new, or at most max occurrences if max given
26
rfind(str, beg=0,end=len(string))
Same as find(), but search backwards in string
27
rindex( str, beg=0, end=len(string))
Same as index(), but search backwards in string
28
rjust(width,[, fillchar])
Returns a space-padded string with the original string right-justified to a total of width columns.
29
rstrip()
Removes all trailing whitespace of string
30
split(str="", num=string.count(str))
Splits string according to delimiter str (space if not provided) and returns list of substrings; split
into at most num substrings if given
31
splitlines( num=string.count('n'))
Splits string at all (or num) NEWLINEs and returns a list of each line with NEWLINEs removed
32
startswith(str, beg=0,end=len(string))
Determines if string or a substring of string (if starting index beg and ending index end are given)
starts with substring str; Returns true if so, and false otherwise
33
strip([chars])
Performs both lstrip() and rstrip() on string
34
swapcase()
Inverts case for all letters in string
35
title()
Returns "titlecased" version of string, that is, all words begin with uppercase, and the rest are
lowercase
36
translate(table, deletechars="")
Translates string according to translation table str(256 chars), removing those in the del string
37
upper()
Converts lowercase letters in string to uppercase
38
zfill (width)
Returns original string leftpadded with zeros to a total of width characters; intended for numbers,
zfill() retains any sign given (less one zero)
39
isdecimal()
Returns true if a unicode string contains only decimal characters and false otherwise
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Python - Lists
Few words about Python Sequences:
The most basic data structure in Python is the sequence. Each element of a sequence is assigned a
number - its position, or index. The first index is zero, the second index is one, and so forth.
Python has six built-in types of sequences, but the most common ones are lists and tuples which we
would see in this tutorial.
There are certain things you can do with all sequence types. These operations include indexing, slicing,
adding, multiplying, and checking for membership. In addition, Python has built-in functions for finding
the length of a sequence, and for finding its largest and smallest elements.
Python Lists:
The list is a most versatile datatype available in Python, which can be written as a list of commaseparated values (items) between square brackets. Good thing about a list that items in a list need not all
have the same type:
Creating a list is as simple as putting different comma-separated values between squere brackets. For
example:
list1 = ['physics', 'chemistry', 1997, 2000];
list2 = [1, 2, 3, 4, 5 ];
list3 = ["a", "b", "c", "d"];
Like string indices, list indices start at 0, and lists can be sliced, concatenated and so on.
Accessing Values in Lists:
To access values in lists, use the square brackets for slicing along with the index or indices to obtain
value available at that index:
Example:
#!/usr/bin/python
list1 = ['physics', 'chemistry', 1997, 2000];
list2 = [1, 2, 3, 4, 5, 6, 7 ];
print "list1[0]: ", list1[0]
print "list2[1:5]: ", list2[1:5]
This will produce following result:
list1[0]: physics
list2[1:5]: [2, 3, 4, 5]
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Updating Lists:
You can update single or multiple elements of lists by giving the slice on the left-hand side of the
assignment operator, and you can add to elements in a list with the append() method:
Example:
#!/usr/bin/python
list1 = ['physics', 'chemistry', 1997, 2000];
print "Value available at index 2 : "
print list1[2];
list1[2] = 2001;
print "New value available at index 2 : "
print list1[2];
Note: append() method is discussed in subsequent section.
This will produce following result:
Value available at index 2 :
1997
New value available at index 2 :
2001
Delete List Elements:
To remove a list element, you can use either the del statement if you know exactly which element(s) you
are deleting or the remove() method if you do not know.
Example:
#!/usr/bin/python
list1 = ['physics', 'chemistry', 1997, 2000];
print list1;
del list1[2];
print "After deleting value at index 2 : "
print list1;
This will produce following result:
['physics', 'chemistry', 1997, 2000]
After deleting value at index 2 :
['physics', 'chemistry', 2000]
Note: remove() method is discussed in subsequent section.
Basic List Operations:
Lists respond to the + and * operators much like strings; they mean concatenation and repetition here
too, except that the result is a new list, not a string.
In fact, lists respond to all of the general sequence operations we used on strings in the prior chapter :
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Python Expression
Results
Description
len([1, 2, 3])
3
Length
[1, 2, 3] + [4, 5, 6]
[1, 2, 3, 4, 5, 6]
Concatenation
['Hi!'] * 4
['Hi!', 'Hi!', 'Hi!', 'Hi!']
Repetition
3 in [1, 2, 3]
True
Membership
for x in [1, 2, 3]: print x,
123
Iteration
Indexing, Slicing, and Matrixes:
Because lists are sequences, indexing and slicing work the same way for lists as they do for strings.
Assuming following input:
L = ['spam', 'Spam', 'SPAM!']
Python Expression
Results
Description
L[2]
'SPAM!'
Offsets start at zero
L[-2]
'Spam'
Negative: count from the right
L[1:]
['Spam', 'SPAM!']
Slicing fetches sections
Built-in List Functions & Methods:
Python includes following list functions
SN
Function with Description
1
cmp(list1, list2)
Compares elements of both lists.
2
len(list)
Gives the total length of the list.
3
max(list)
Returns item from the list with max value.
4
min(list)
Returns item from the list with min value.
5
list(seq)
Converts a tuple into list.
Python includes following list methods
SN
Methods with Description
1
list.append(obj)
Appends object obj to list
2
list.count(obj)
Returns count of how many times obj occurs in list
3
list.extend(seq)
Appends the contents of seq to list
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4
list.index(obj)
Returns the lowest index in list that obj appears
5
list.insert(index, obj)
Inserts object obj into list at offset index
6
list.pop(obj=list[-1])
Removes and returns last object or obj from list
7
list.remove(obj)
Removes object obj from list
8
list.reverse()
Reverses objects of list in place
9
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list.sort([func])
Sorts objects of list, use compare func if given
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Python - Tuples
A tuple is a sequence of immutable Python objects. Tuples are sequences, just like lists. The only
difference is that tuples can't be changed ie. tuples are immutable and tuples use parentheses and lists
use square brackets.
Creating a tuple is as simple as putting different comma-separated values and optionally you can put
these comma-separated values between parentheses also. For example:
tup1 = ('physics', 'chemistry', 1997, 2000);
tup2 = (1, 2, 3, 4, 5 );
tup3 = "a", "b", "c", "d";
The empty tuple is written as two parentheses containing nothing:
tup1 = ();
To write a tuple containing a single value you have to include a comma, even though there is only one
value:
tup1 = (50,);
Like string indices, tuple indices start at 0, and tuples can be sliced, concatenated and so on.
Accessing Values in Tuples:
To access values in tuple, use the square brackets for slicing along with the index or indices to obtain
value available at that index:
Example:
#!/usr/bin/python
tup1 = ('physics', 'chemistry', 1997, 2000);
tup2 = (1, 2, 3, 4, 5, 6, 7 );
print "tup1[0]: ", tup1[0]
print "tup2[1:5]: ", tup2[1:5]
This will produce following result:
tup1[0]: physics
tup2[1:5]: [2, 3, 4, 5]
Updating Tuples:
Tuples are immutable which means you cannot update them or change values of tuple elements. But we
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Python Expression
Results
Description
len((1, 2, 3))
3
Length
(1, 2, 3) + (4, 5, 6)
(1, 2, 3, 4, 5, 6)
Concatenation
['Hi!'] * 4
('Hi!', 'Hi!', 'Hi!', 'Hi!')
Repetition
3 in (1, 2, 3)
True
Membership
for x in (1, 2, 3): print x,
123
Iteration
Indexing, Slicing, and Matrixes:
Because tuples are sequences, indexing and slicing work the same way for tuples as they do for strings.
Assuming following input:
L = ('spam', 'Spam', 'SPAM!')
Python Expression
Results
Description
L[2]
'SPAM!'
Offsets start at zero
L[-2]
'Spam'
Negative: count from the right
L[1:]
['Spam', 'SPAM!']
Slicing fetches sections
No Enclosing Delimiters:
Any set of multiple objects, comma-separated, written without identifying symbols, i.e., brackets for lists,
parentheses for tuples, etc., default to tuples, as indicated in these short examples:
#!/usr/bin/python
print 'abc', -4.24e93, 18+6.6j, 'xyz';
x, y = 1, 2;
print "Value of x , y : ", x,y;
print var;
This will reduce following result:
abc -4.24e+93 (18+6.6j) xyz
Value of x , y : 1 2
Built-in Tuple Functions:
Python includes following tuple functions
SN
Function with Description
1
cmp(tuple1, tuple2)
Compares elements of both tuples.
2
len(tuple)
Gives the total length of the tuple.
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Python - Dictionary
A dictionary is mutable and is another container type that can store any number of Python objects,
including other container types.
Dictionaries consist of pairs (called items) of keys and their corresponding values.
Python dictionaries are also known as associative arrays or hash tables. The general syntax of a
dictionary is as follows:
dict = {'Alice': '2341', 'Beth': '9102', 'Cecil': '3258'}
You can create dictionary in the following way as well:
dict1 = { 'abc': 456 };
dict2 = { 'abc': 123, 98.6: 37 };
Each key is separated from its value by a colon (:), the items are separated by commas, and the whole
thing is enclosed in curly braces. An empty dictionary without any items is written with just two curly
braces, like this: {}.
Keys are unique within a dictionary while values may not be. The values of a dictionary can be of any
type, but the keys must be of an immutable data type such as strings, numbers, or tuples.
Accessing Values in Dictionary:
To access dictionary elements, you use the familiar square brackets along with the key to obtain its
value:
Example:
#!/usr/bin/python
dict = {'Name': 'Zara', 'Age': 7, 'Class': 'First'};
print "dict['Name']: ", dict['Name'];
print "dict['Age']: ", dict['Age'];
This will produce following result:
dict['Name']: Zara
dict['Age']: 7
If we attempt to access a data item with a key which is not part of the dictionary, we get an error as
follows:
#!/usr/bin/python
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dict = {'Name': 'Zara', 'Age': 7, 'Class': 'First'};
print "dict['Alice']: ", dict['Alice'];
This will produce following result:
dict['Zara']:
Traceback (most recent call last):
File "test.py", line 4, in <module>
print "dict['Alice']: ", dict['Alice'];
KeyError: 'Alice'
Updating Dictionary:
You can update a dictionary by adding a new entry or item (i.e., a key-value pair), modifying an existing
entry, or deleting an existing entry as shown below:
Example:
#!/usr/bin/python
dict = {'Name': 'Zara', 'Age': 7, 'Class': 'First'};
dict['Age'] = 8; # update existing entry
dict['School'] = "DPS School"; # Add new entry
print "dict['Age']: ", dict['Age'];
print "dict['School']: ", dict['School'];
This will produce following result:
dict['Age']: 8
dict['School']:
DPS School
Delete Dictionary Elements:
You can either remove individual dictionary elements or clear the entire contents of a dictionary. You can
also delete entire dictionary in a single operation.
To explicitly remove an entire dictionary, just use the del statement:
Example:
#!/usr/bin/python
dict = {'Name': 'Zara', 'Age': 7, 'Class': 'First'};
del dict['Name']; # remove entry with key 'Name'
dict.clear();
# remove all entries in dict
del dict ;
# delete entire dictionary
print "dict['Age']: ", dict['Age'];
print "dict['School']: ", dict['School'];
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This will produce following result. Note an exception raised, this is because after del dict dictionary does
not exist any more:
dict['Age']:
Traceback (most recent call last):
File "test.py", line 8, in <module>
print "dict['Age']: ", dict['Age'];
TypeError: 'type' object is unsubscriptable
Note: del() method is discussed in subsequent section.
Properties of Dictionary Keys:
Dictionary values have no restrictions. They can be any arbitrary Python object, either standard objects or
user-defined objects. However, same is not true for the keys.
There are two important points to remember about dictionary keys:
(a) More than one entry per key not allowed. Which means no duplicate key is allowed. When duplicate
keys encountered during assignment, the last assignment wins.
Example:
#!/usr/bin/python
dict = {'Name': 'Zara', 'Age': 7, 'Name': 'Manni'};
print "dict['Name']: ", dict['Name'];
This will produce following result:
dict['Name']:
Manni
(b) Keys must be immutable. Which means you can use strings, numbers, or tuples as dictionary keys
but something like ['key'] is not allowed.
Example:
#!/usr/bin/python
dict = {['Name']: 'Zara', 'Age': 7};
print "dict['Name']: ", dict['Name'];
This will produce following result. Note an exception raised:
Traceback (most recent call last):
File "test.py", line 3, in <module>
dict = {['Name']: 'Zara', 'Age': 7};
TypeError: list objects are unhashable
Built-in Dictionary Functions & Methods:
Python includes following dictionary functions
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Function with Description
1
cmp(dict1, dict2)
Compares elements of both dict.
2
len(dict)
Gives the total length of the dictionary. This would be equal to the number of items in the
dictionary.
3
str(dict)
Produces a printable string representation of a dictionary
4
type(variable)
Returns the type of the passed variable. If passed variable is dictionary then it would return a
dictionary type.
Python includes following dictionary methods
SN
Methods with Description
1
dict.clear()
Removes all elements of dictionary dict
2
dict.copy()
Returns a shallow copy of dictionary dict
2
dict.fromkeys()
Create a new dictionary with keys from seq and values set to value.
3
dict.get(key, default=None)
For key key, returns value or default if key not in dictionary
4
dict.has_key(key)
Returns true if key in dictionary dict, false otherwise
5
dict.items()
Returns a list of dict's (key, value) tuple pairs
6
dict.keys()
Returns list of dictionary dict's keys
7
dict.setdefault(key, default=None)
Similar to get(), but will set dict[key]=default if key is not already in dict
8
dict.update(dict2)
Adds dictionary dict2's key-values pairs to dict
9
dict.values()
Returns list of dictionary dict2's values
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cal = calendar.month(2008, 1)
print "Here is the calendar:"
print cal;
This would produce following result:
Here is the
January
Mo Tu We Th
1 2 3
7 8 9 10
14 15 16 17
21 22 23 24
28 29 30 31
calendar:
2008
Fr Sa Su
4 5 6
11 12 13
18 19 20
25 26 27
The time Module:
There is a popular time module available in Python which provides functions for working with times, and
for converting between representations. Here is the list of all available methods:
SN
Function with Description
1
time.altzone
The offset of the local DST timezone, in seconds west of UTC, if one is defined. This is negative if
the local DST timezone is east of UTC (as in Western Europe, including the UK). Only use this if
daylight is nonzero.
2
time.asctime([tupletime])
Accepts a time-tuple and returns a readable 24-character string such as 'Tue Dec 11 18:07:14
2008'.
3
time.clock( )
Returns the current CPU time as a floating-point number of seconds. To measure computational
costs of different approaches, the value of time.clock is more useful than that of time.time().
4
time.ctime([secs])
Like asctime(localtime(secs)) and without arguments is like asctime( )
5
time.gmtime([secs])
Accepts an instant expressed in seconds since the epoch and returns a time-tuple t with the UTC
time. Note : t.tm_isdst is always 0
6
time.localtime([secs])
Accepts an instant expressed in seconds since the epoch and returns a time-tuple t with the local
time (t.tm_isdst is 0 or 1, depending on whether DST applies to instant secs by local rules).
7
time.mktime(tupletime)
Accepts an instant expressed as a time-tuple in local time and returns a floating-point value with
the instant expressed in seconds since the epoch.
8
time.sleep(secs)
Suspends the calling thread for secs seconds.
9
time.strftime(fmt[,tupletime])
Accepts an instant expressed as a time-tuple in local time and returns a string representing the
instant as specified by string fmt.
10
time.strptime(str,fmt='%a %b %d %H:%M:%S %Y')
Parses str according to format string fmt and returns the instant in time-tuple format.
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Python - Functions
A function is a block of organized, reusable code that is used to perform a single, related action.
Functions provides better modularity for your application and a high degree of code reusing.
As you already know, Python gives you many built-in functions like print() etc. but you can also create
your own functions. These functions are called user-defined functions.
Defining a Function
You can define functions to provide the required functionality. Here are simple rules to define a function
in Python:
Function blocks begin with the keyword def followed by the function name and parentheses ( ( ) ).
Any input parameters or arguments should be placed within these parentheses. You can also define
parameters inside these parentheses.
The first statement of a function can be an optional statement - the documentation string of the
function or docstring.
The code block within every function starts with a colon (:) and is indented.
The statement return [expression] exits a function, optionally passing back an expression to the
caller. A return statement with no arguments is the same as return None.
Syntax:
def functionname( parameters ):
"function_docstring"
function_suite
return [expression]
By default, parameters have a positional behavior, and you need to inform them in the same order that
they were defined.
Example:
Here is the simplest form of a Python function. This function takes a string as input parameter and prints
it on standard screen.
def printme( str ):
"This prints a passed string into this function"
print str
return
Calling a Function
Defining a function only gives it a name, specifies the parameters that are to be included in the function,
and structures the blocks of code.
Once the basic structure of a function is finalized, you can execute it by calling it from another function or
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directly from the Python prompt.
Following is the example to call printme() function:
#!/usr/bin/python
# Function definition is here
def printme( str ):
"This prints a passed string into this function"
print str;
return;
# Now you can call printme function
printme("I'm first call to user defined function!");
printme("Again second call to the same function");
This would produce following result:
I'm first call to user defined function!
Again second call to the same function
Pass by reference vs value
All parameters (arguments) in the Python language are passed by reference. It means if you change what
a parameter refers to within a function, the change also reflects back in the calling function. For example:
#!/usr/bin/python
# Function definition is here
def changeme( mylist ):
"This changes a passed list into this function"
mylist.append([1,2,3,4]);
print "Values inside the function: ", mylist
return
# Now you can call changeme function
mylist = [10,20,30];
changeme( mylist );
print "Values outside the function: ", mylist
Here we are maintaining reference of the passed object and appending values in the same object. So this
would produce following result:
Values inside the function: [10, 20, 30, [1, 2, 3, 4]]
Values outside the function: [10, 20, 30, [1, 2, 3, 4]]
There is one more example where argument is being passed by reference but inside the function, but the
reference is being over-written.
#!/usr/bin/python
# Function definition is here
def changeme( mylist ):
"This changes a passed list into this function"
mylist = [1,2,3,4]; # This would assig new reference in mylist
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print "Values inside the function: ", mylist
return
# Now you can call changeme function
mylist = [10,20,30];
changeme( mylist );
print "Values outside the function: ", mylist
The parameter mylist is local to the function changeme. Changing mylist within the function does not
affect mylist. The function accomplishes nothing and finally this would produce following result:
Values inside the function: [1, 2, 3, 4]
Values outside the function: [10, 20, 30]
Function Arguments:
You can call a function by using the following types of formal arguments::
Required arguments
Keyword arguments
Default arguments
Variable-length arguments
Required arguments:
Required arguments are the arguments passed to a function in correct positional order. Here the number
of arguments in the function call should match exactly with the function definition.
To call the function printme() you definitely need to pass one argument otherwise it would give a syntax
error as follows:
#!/usr/bin/python
# Function definition is here
def printme( str ):
"This prints a passed string into this function"
print str;
return;
# Now you can call printme function
printme();
This would produce following result:
Traceback (most recent call last):
File "test.py", line 11, in <module>
printme();
TypeError: printme() takes exactly 1 argument (0 given)
Keyword arguments:
Keyword arguments are related to the function calls. When you use keyword arguments in a function call,
the caller identifies the arguments by the parameter name.
This allows you to skip arguments or place them out of order because the Python interpreter is able to
use the keywords provided to match the values with parameters.
You can also make keyword calls to the printme() function in the following ways:
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Name: miki
Age 50
Name: miki
Age 35
Variable-length arguments:
You may need to process a function for more arguments than you specified while defining the function.
These arguments are called variable-length arguments and are not named in the function definition, unlike
required and default arguments.
The general syntax for a function with non-keyword variable arguments is this:
def functionname([formal_args,] *var_args_tuple ):
"function_docstring"
function_suite
return [expression]
An asterisk (*) is placed before the variable name that will hold the values of all nonkeyword variable
arguments. This tuple remains empty if no additional arguments are specified during the function call. For
example:
#!/usr/bin/python
# Function definition is here
def printinfo( arg1, *vartuple ):
"This prints a variable passed arguments"
print "Output is: "
print arg1
for var in vartuple:
print var
return;
# Now you can call printinfo function
printinfo( 10 );
printinfo( 70, 60, 50 );
This would produce following result:
Output is:
10
Output is:
70
60
50
The Anonymous Functions:
You can use the lambda keyword to create small anonymous functions. These functions are called
anonymous because they are not declared in the standard manner by using the def keyword.
Lambda forms can take any number of arguments but return just one value in the form of an
expression. They cannot contain commands or multiple expressions.
An anonymous function cannot be a direct call to print because lambda requires an expression.
Lambda functions have their own local namespace and cannot access variables other than those in
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their parameter list and those in the global namespace.
Although it appears that lambda's are a one-line version of a function, they are not equivalent to
inline statements in C or C++, whose purpose is by passing function stack allocation during
invocation for performance reasons.
Syntax:
The syntax of lambda functions contains only a single statement, which is as follows:
lambda [arg1 [,arg2,.....argn]]:expression
Example:
Following is the example to show how lembda form of function works:
#!/usr/bin/python
# Function definition is here
sum = lambda arg1, arg2: arg1 + arg2;
# Now you can call sum as a function
print "Value of total : ", sum( 10, 20 )
print "Value of total : ", sum( 20, 20 )
This would produce following result:
Value of total :
Value of total :
30
40
The return Statement:
The statement return [expression] exits a function, optionally passing back an expression to the caller. A
return statement with no arguments is the same as return None
All the above examples are not returning any value, but if you like you can return a value from a function
as follows:
#!/usr/bin/python
# Function definition is here
def sum( arg1, arg2 ):
# Add both the parameters and return them."
total = arg1 + arg2
print "Inside the function : ", total
return total;
# Now you can call sum function
total = sum( 10, 20 );
print "Outside the function : ", total
This would produce following result:
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Python - Modules
A module allows you to logically organize your Python code. Grouping related code into a module makes
the code easier to understand and use.
A module is a Python object with arbitrarily named attributes that you can bind and reference.
Simply, a module is a file consisting of Python code. A module can define functions, classes, and
variables. A module can also include runnable code.
Example:
The Python code for a module named aname normally resides in a file named aname.py. Here's an
example of a simple module, hello.py
def print_func( par ):
print "Hello : ", par
return
The import Statement:
You can use any Python source file as a module by executing an import statement in some other Python
source file. import has the following syntax:
import module1[, module2[,... moduleN]
When the interpreter encounters an import statement, it imports the module if the module is present in
the search path. Asearch path is a list of directories that the interpreter searches before importing a
module.
Example:
To import the module hello.py, you need to put the following command at the top of the script:
#!/usr/bin/python
# Import module hello
import hello
# Now you can call defined function that module as follows
hello.print_func("Zara")
This would produce following result:
Hello : Zara
A module is loaded only once, regardless of the number of times it is imported. This prevents the module
execution from happening over and over again if multiple imports occur.
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The from...import Statement
Python's from statement lets you import specific attributes from a module into the current namespace:
Syntax:
from modname import name1[, name2[, ... nameN]]
Example:
For example, to import the function fibonacci from the module fib, use the following statement:
from fib import fibonacci
This statement does not import the entire module fib into the current namespace; it just introduces the
item fibonacci from the module fib into the global symbol table of the importing module.
The from...import * Statement:
It is also possible to import all names from a module into the current namespace by using the following
import statement:
from modname import *
This provides an easy way to import all the items from a module into the current namespace; however,
this statement should be used sparingly.
Locating Modules:
When you import a module, the Python interpreter searches for the module in the following sequences:
The current directory.
If the module isn't found, Python then searches each directory in the shell variable PYTHONPATH.
If all else fails, Python checks the default path. On UNIX, this default path is normally /usr/local
/lib/python/.
The module search path is stored in the system module sys as the sys.path variable. The sys.path
variable contains the current directory, PYTHONPATH, and the installation-dependent default.
The PYTHONPATH Variable:
The PYTHONPATH is an environment variable, consisting of a list of directories. The syntax of
PYTHONPATH is the same as that of the shell variable PATH.
Here is a typical PYTHONPATH from a Windows system:
set PYTHONPATH=c:python20lib;
And here is a typical PYTHONPATH from a UNIX system:
set PYTHONPATH=/usr/local/lib/python
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'fabs', 'floor', 'fmod', 'frexp', 'hypot', 'ldexp', 'log',
'log10', 'modf', 'pi', 'pow', 'radians', 'sin', 'sinh',
'sqrt', 'tan', 'tanh']
Here the special string variable __name__ is the module's name, and __file__ is the filename from which
the module was loaded.
The globals() and locals() Functions:
The globals() and locals() functions can be used to return the names in the global and local namespaces
depending on the location from where they are called.
If locals() is called from within a function, it will return all the names that can be accessed locally from
that function.
If globals() is called from within a function, it will return all the names that can be accessed globally from
that function.
The return type of both these functions is dictionary. Therefore, names can be extracted using the keys()
function.
The reload() Function:
When the module is imported into a script, the code in the top-level portion of a module is executed only
once.
Therefore, if you want to reexecute the top-level code in a module, you can use the reload() function. The
reload() function imports a previously imported module again.
Syntax:
The syntax of the reload() function is this:
reload(module_name)
Here module_name is the name of the module you want to reload and not the string containing the
module name. For example to re-load hello module, do the following:
reload(hello)
Packages in Python:
A package is a hierarchical file directory structure that defines a single Python application environment
that consists of modules and subpackages and sub-subpackages, and so on.
Example:
Consider a file Pots.py available in Phone directory. This file has following line of source code:
#!/usr/bin/python
def Pots():
print "I'm Pots Phone"
Similar way we have another two files having different functions with the same name as above:
Phone/Isdn.py file having function Isdn()
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Python Files I/O
This chapter will cover all the basic I/O functions available in Python. For more functions please refere to
standard Python documentation.
Printing to the Screen:
The simplest way to produce output is using the print statement where you can pass zero or more
expressions, separated by commas. This function converts the expressions you pass it to a string and
writes the result to standard output as follows:
#!/usr/bin/python
print "Python is really a great language,", "isn't it?";
This would produce following result on your standard screen:
Python is really a great language, isn't it?
Reading Keyboard Input:
Python provides two built-in functions to read a line of text from standard input, which by default comes
from the keyboard. These functions are:
raw_input
input
The raw_input Function:
The raw_input([prompt]) function reads one line from standard input and returns it as a string (removing
the trailing newline):
#!/usr/bin/python
str = raw_input("Enter your input: ");
print "Received input is : ", str
This would prompt you to enter any string and it would display same string on the screen. When I typed
"Hello Python!", it output is like this:
Enter your input: Hello Python
Received input is : Hello Python
The input Function:
The input([prompt]) function is equivalent to raw_input, except that it assumes the input is a valid Python
expression and returns the evaluated result to you:
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#!/usr/bin/python
str = input("Enter your input: ");
print "Received input is : ", str
This would produce following result against the entered input:
Enter your input: [x*5 for x in range(2,10,2)]
Recieved input is : [10, 20, 30, 40]
Opening and Closing Files:
Until now, you have been reading and writing to the standard input and output. Now we will see how to
play with actual data files.
Python provides basic functions and methods necessary to manipulate files by default. You can do your
most of the file manipulation using a file object.
The open Function:
Before you can read or write a file, you have to open it using Python's built-in open() function. This
function creates a file object which would be utilized to call other support methods associated with it.
Syntax:
file object = open(file_name [, access_mode][, buffering])
Here is paramters detail:
file_name: The file_name argument is a string value that contains the name of the file that you
want to access.
access_mode: The access_mode determines the mode in which the file has to be opened ie. read,
write append etc. A complete list of possible values is given below in the table. This is optional
parameter and the default file access mode is read (r)
buffering: If the buffering value is set to 0, no buffering will take place. If the buffering value is 1,
line buffering will be performed while accessing a file. If you specify the buffering value as an
integer greater than 1, then buffering action will be performed with the indicated buffer size. If
negative, the buffer size is the system default(default behavior).
Here is a list of the different modes of opening a file:
Modes
Description
r
Opens a file for reading only. The file pointer is placed at the beginning of the file. This is the
default mode.
rb
Opens a file for reading only in binary format. The file pointer is placed at the beginning of the
file. This is the default mode.
r+
Opens a file for both reading and writing. The file pointer will be at the beginning of the file.
rb+
Opens a file for both reading and writing in binary format. The file pointer will be at the
beginning of the file.
w
Opens a file for writing only. Overwrites the file if the file exists. If the file does not exist,
creates a new file for writing.
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Python is a great language.
Yeah its great!!
The read() Method:
The read() method read a string from an open file. It is important to note that Python strings can have
binary data and not just text.
Syntax:
fileObject.read([count]);
Here passed parameter is the number of bytes to be read from the opend file. This method starts reading
from the beginning of the file and if count is missing then it tries to read as much as possible, may be
until the end of file.
Example:
Let's take a file foo.txt which we have created above.
#!/usr/bin/python
# Open a file
fo = open("foo.txt", "r+")
str = fo.read(10);
print "Read String is : ", str
# Close opend file
fo.close()
This would produce following result:
Read String is :
Python is
File Positions:
The tell() method tells you the current position within the file in other words, the next read or write will
occur at that many bytes from the beginning of the file:
The seek(offset[, from]) method changes the current file position. The offset argument indicates the
number of bytes to be moved. The from argument specifies the reference position from where the bytes
are to be moved.
If from is set to 0, it means use the beginning of the file as the reference position and 1 means use the
current position as the reference position and if it is set to 2 then the end of the file would be taken as
the reference position.
Example:
Let's take a file foo.txt which we have created above.
#!/usr/bin/python
# Open a file
fo = open("foo.txt", "r+")
str = fo.read(10);
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The except clause with multiple exceptions:
You can also use the same except statement to handle multiple exceptions as follows:
try:
You do your operations here;
......................
except(Exception1[, Exception2[,...ExceptionN]]]):
If there is any exception from the given exception list,
then execute this block.
......................
else:
If there is no exception then execute this block.
Standard Exceptions:
Here is a list standard Exceptions available in Python: Standard Exceptions
The try-finally clause:
You can use a finally: block along with a try: block. The finally block is a place to put any code that
must execute, whether the try-block raised an exception or not. The syntax of the try-finally statement is
this:
try:
You do your operations here;
......................
Due to any exception, this may be skipped.
finally:
This would always be executed.
......................
Note that you can provide except clause(s), or a finally clause, but not both. You can not use else clause
as well along with a finally clause.
Example:
#!/usr/bin/python
try:
fh = open("testfile", "w")
fh.write("This is my test file for exception handling!!")
finally:
print "Error: can't find file or read data"
If you do not have permission to open the file in writing mode then this will produce following result:
Error: can't find file or read data
Same example can be written more cleanly as follows:
#!/usr/bin/python
try:
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Syntax:
raise [Exception [, args [, traceback]]]
Here Exception is the type of exception (for example, NameError) and argument is a value for the
exception argument. The argument is optional; if not supplied, the exception argument is None.
The final argument, traceback, is also optional (and rarely used in practice), and, if present, is the
traceback object used for the exception
Example:
An exception can be a string, a class, or an object. Most of the exceptions that the Python core raises are
classes, with an argument that is an instance of the class. Defining new exceptions is quite easy and can
be done as follows:
def functionName( level ):
if level < 1:
raise "Invalid level!", level
# The code below to this would not be executed
# if we raise the exception
Note: In order to catch an exception, an "except" clause must refer to the same exception thrown either
class object or simple string. For example to capture above exception we must write our except clause as
follows:
try:
Business Logic here...
except "Invalid level!":
Exception handling here...
else:
Rest of the code here...
User-Defined Exceptions:
Python also allows you to create your own exceptions by deriving classes from the standard built-in
exceptions.
Here is an example related to RuntimeError. Here a class is created that is subclassed from RuntimeError.
This is useful when you need to display more specific information when an exception is caught.
In the try block, the user-defined exception is raised and caught in the except block. The variable e is
used to create an instance of the class Networkerror.
class Networkerror(RuntimeError):
def __init__(self, arg):
self.args = arg
So once you defined above class, you can raise your exception as follows:
try:
raise Networkerror("Bad hostname")
except Networkerror,e:
print e.args
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class Employee:
'Common base class for all employees'
empCount = 0
def __init__(self, name, salary):
self.name = name
self.salary = salary
Employee.empCount += 1
def displayCount(self):
print "Total Employee %d" % Employee.empCount
def displayEmployee(self):
print "Name : ", self.name,
", Salary: ", self.salary
"This would create first object of Employee class"
emp1 = Employee("Zara", 2000)
"This would create second object of Employee class"
emp2 = Employee("Manni", 5000)
emp1.displayEmployee()
emp2.displayEmployee()
print "Total Employee %d" % Employee.empCount
This would produce following result:
Name : Zara ,Salary: 2000
Name : Manni ,Salary: 5000
Total Employee 2
You can add, remove, or modify attributes of classes and objects at any time:
emp1.age = 7
emp1.age = 8
del emp1.age
# Add an 'age' attribute.
# Modify 'age' attribute.
# Delete 'age' attribute.
Instead of using the normal statements to access attributes, you can use following functions:
The getattr(obj, name[, default]) : to access the attribute of object.
The hasattr(obj,name) : to check if an attribute exists or not.
The setattr(obj,name,value) : to set an attribute. If attribute does not exist then it would be
created.
The delattr(obj, name) : to delete an attribute.
hasattr(emp1,
getattr(emp1,
setattr(emp1,
delattr(empl,
'age')
#
'age')
#
'age', 8) #
'age')
#
Returns true if 'age' attribute exists
Returns value of 'age' attribute
Set attribute 'age' at 8
Delete attribute 'age'
Built-In Class Attributes:
Every Python class keeps following built-in attributes and they can be accessed using dot operator like
any other attribute:
__dict__ : Dictionary containing the class's namespace.
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__doc__ : Class documentation string, or None if undefined.
__name__: Class name.
__module__: Module name in which the class is defined. This attribute is "__main__" in
interactive mode.
__bases__ : A possibly empty tuple containing the base classes, in the order of their occurrence
in the base class list.
For the above class let's try to access all these attributes:
print
print
print
print
print
"Employee.__doc__:", Employee.__doc__
"Employee.__name__:", Employee.__name__
"Employee.__module__:", Employee.__module__
"Employee.__bases__:", Employee.__bases__
"Employee.__dict__:", Employee.__dict__
This would produce following result:
Employee.__doc__: Common base class for all employees
Employee.__name__: Employee
Employee.__module__: __main__
Employee.__bases__: ()
Employee.__dict__: {'__module__': '__main__', 'displayCount':
<function displayCount at 0xb7c84994>, 'empCount': 2,
'displayEmployee': <function displayEmployee at 0xb7c8441c>,
'__doc__': 'Common base class for all employees',
'__init__': <function __init__ at 0xb7c846bc>}
Destroying Objects (Garbage Collection):
Python deletes unneeded objects (built-in types or class instances) automatically to free memory space.
The process by which Python periodically reclaims blocks of memory that no longer are in use is termed
garbage collection.
Python's garbage collector runs during program execution and is triggered when an object's reference
count reaches zero. An object's reference count changes as the number of aliases that point to it changes:
An object's reference count increases when it's assigned a new name or placed in a container (list, tuple,
or dictionary). The object's reference count decreases when it's deleted with del, its reference is
reassigned, or its reference goes out of scope. When an object's reference count reaches zero, Python
collects it automatically.
a = 40
b = a
c = [b]
# Create object <40>
# Increase ref. count
# Increase ref. count
of <40>
of <40>
del a
b = 100
c[0] = -1
# Decrease ref. count
# Decrease ref. count
# Decrease ref. count
of <40>
of <40>
of <40>
You normally won't notice when the garbage collector destroys an orphaned instance and reclaims its
space. But a class can implement the special method __del__(), called a destructor, that is invoked when
the instance is about to be destroyed. This method might be used to clean up any nonmemory resources
used by an instance.
Example:
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This __del__() destructor prints the class name of an instance that is about to be destroyed:
#!/usr/bin/python
class Point:
def __init( self, x=0, y=0):
self.x = x
self.y = y
def __del__(self):
class_name = self.__class__.__name__
print class_name, "destroyed"
pt1 = Point()
pt2 = pt1
pt3 = pt1
print id(pt1), id(pt2), id(pt3) # prints the ids of the obejcts
del pt1
del pt2
del pt3
This would produce following result:
3083401324 3083401324 3083401324
Point destroyed
Note: Ideally, you should define your classes in separate file then you should import them in your main
program file using import statement. Kindly check Python - Modules chapter for more detail on importing
modules and classes.
Class Inheritance:
Instead of starting from scratch, you can create a class by deriving it from a preexisting class by listing
the parent class in parentheses after the new class name:
The child class inherits the attributes of its parent class, and you can use those attributes as if they were
defined in the child class. A child class can also override data members and methods from the parent.
Syntax:
Derived classes are declared much like their parent class; however, a list of base classes to inherit from
are given after the class name:
class SubClassName (ParentClass1[, ParentClass2, ...]):
'Optional class documentation string'
class_suite
Example:
#!/usr/bin/python
class Parent:
# define parent class
parentAttr = 100
def __init__(self):
print "Calling parent constructor"
def parentMethod(self):
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def myMethod(self):
print 'Calling parent method'
class Child(Parent): # define child class
def myMethod(self):
print 'Calling child method'
c = Child()
c.myMethod()
# instance of child
# child calls overridden method
This would produce following result:
Calling child method
Base Overloading Methods:
Following table lists some generic functionality that you can override in your own classes:
SN
Method, Description & Sample Call
1
__init__ ( self [,args...] )
Constructor (with any optional arguments)
Sample Call : obj = className(args)
2
__del__( self )
Destructor, deletes an object
Sample Call : dell obj
3
__repr__( self )
Evaluatable string representation
Sample Call : repr(obj)
4
__str__( self )
Printable string representation
Sample Call : str(obj)
5
__cmp__ ( self, x )
Object comparison
Sample Call : cmp(obj, x)
Overloading Operators:
Suppose you've created a Vector class to represent two-dimensional vectors. What happens when you use
the plus operator to add them? Most likely Python will yell at you.
You could, however, define the __add__ method in your class to perform vector addition, and then the
plus operator would behave as per expectation:
Example:
#!/usr/bin/python
class Vector:
def __init__(self, a, b):
self.a = a
self.b = b
def __str__(self):
return 'Vector (%d, %d)' % (self.a, self.b)
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# Delete Python-style comments
num = re.sub(r'#.*$', "", phone)
print "Phone Num : ", num
# Remove anything other than digits
num = re.sub(r'D', "", phone)
print "Phone Num : ", num
This will produce following result:
Phone Num :
Phone Num :
2004-959-559
2004959559
Regular-expression Modifiers - Option Flags
Regular expression literals may include an optional modifier to control various aspects of matching. The
modifier are specified as an optional flag. You can provide multiple modified using exclusive OR (|), as
shown previously and may be represented by one of these:
Modifier
Description
re.I
Performs case-insensitive matching.
re.L
Interprets words according to the current locale.This interpretation affects the
alphabetic group (w and W), as well as word boundary behavior (b and
B).
re.M
Makes $ match the end of a line (not just the end of the string) and makes ^
match the start of any line (not just the start of the string).
re.S
Makes a period (dot) match any character, including a newline.
re.U
Interprets letters according to the Unicode character set. This flag affects the
behavior of w, W, b, B.
re.X
Permits "cuter" regular expression syntax. It ignores whitespace (except
inside a set [] or when escaped by a backslash), and treats unescaped # as a
comment marker.
Regular-expression patterns:
Except for control characters, (+ ? . * ^ $ ( ) [ ] { } | ), all characters match themselves. You can
escape a control character by preceding it with a backslash.
Following table lists the regular expression syntax that is available in Python.
Pattern
Description
^
Matches beginning of line.
$
Matches end of line.
.
Matches any single character except newline. Using m option allows it to
match newline as well.
[...]
Matches any single character in brackets.
[^...]
Matches any single character not in brackets
re*
Matches 0 or more occurrences of preceding expression.
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re+
Matches 1 or more occurrence of preceding expression.
re?
Matches 0 or 1 occurrence of preceding expression.
re{ n}
Matches exactly n number of occurrences of preceding expression.
re{ n,}
Matches n or more occurrences of preceding expression.
re{ n, m}
Matches at least n and at most m occurrences of preceding expression.
a| b
Matches either a or b.
(re)
Groups regular expressions and remembers matched text.
(?imx)
Temporarily toggles on i, m, or x options within a regular expression. If in
parentheses, only that area is affected.
(?-imx)
Temporarily toggles off i, m, or x options within a regular expression. If in
parentheses, only that area is affected.
(?: re)
Groups regular expressions without remembering matched text.
(?imx: re)
Temporarily toggles on i, m, or x options within parentheses.
(?-imx: re)
Temporarily toggles off i, m, or x options within parentheses.
(?#...)
Comment.
(?= re)
Specifies position using a pattern. Doesn't have a range.
(?! re)
Specifies position using pattern negation. Doesn't have a range.
(?> re)
Matches independent pattern without backtracking.
w
Matches word characters.
W
Matches nonword characters.
s
Matches whitespace. Equivalent to [tnrf].
S
Matches nonwhitespace.
d
Matches digits. Equivalent to [0-9].
D
Matches nondigits.
A
Matches beginning of string.
Z
Matches end of string. If a newline exists, it matches just before newline.
z
Matches end of string.
G
Matches point where last match finished.
b
Matches word boundaries when outside brackets. Matches backspace (0x08)
when inside brackets.
B
Matches nonword boundaries.
n, t, etc.
Matches newlines, carriage returns, tabs, etc.
1...9
Matches nth grouped subexpression.
10
Matches nth grouped subexpression if it matched already. Otherwise refers to
the octal representation of a character code.
Regular-expression Examples:
Literal characters:
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Example
python
Description
Match "python".
Character classes:
Example
Description
[Pp]ython
Match "Python" or "python"
rub[ye]
Match "ruby" or "rube"
[aeiou]
Match any one lowercase vowel
[0-9]
Match any digit; same as [0123456789]
[a-z]
Match any lowercase ASCII letter
[A-Z]
Match any uppercase ASCII letter
[a-zA-Z0-9]
Match any of the above
[^aeiou]
Match anything other than a lowercase vowel
[^0-9]
Match anything other than a digit
Special Character Classes:
Example
Description
.
Match any character except newline
d
Match a digit: [0-9]
D
Match a nondigit: [^0-9]
s
Match a whitespace character: [ trnf]
S
Match nonwhitespace: [^ trnf]
w
Match a single word character: [A-Za-z0-9_]
W
Match a nonword character: [^A-Za-z0-9_]
Repetition Cases:
Example
Description
ruby?
Match "rub" or "ruby": the y is optional
ruby*
Match "rub" plus 0 or more ys
ruby+
Match "rub" plus 1 or more ys
d{3}
Match exactly 3 digits
d{3,}
Match 3 or more digits
d{3,5}
Match 3, 4, or 5 digits
Nongreedy repetition:
This matches the smallest number of repetitions:
Example
<.*>
Description
Greedy repetition: matches "<python>perl>"
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<.*?>
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Nongreedy: matches "<python>" in "<python>perl>"
Grouping with parentheses:
Example
Description
Dd+
No group: + repeats d
(Dd)+
Grouped: + repeats Dd pair
([Pp]ython(, )?)+
Match "Python", "Python, python, python", etc.
Backreferences:
This matches a previously matched group again:
Example
Description
([Pp])ython&1ails
Match python&rails or Python&Rails
(['"])[^1]*1
Single or double-quoted string. 1 matches whatever the 1st group matched .
2 matches whatever the 2nd group matched, etc.
Alternatives:
Example
Description
python|perl
Match "python" or "perl"
rub(y|le))
Match "ruby" or "ruble"
Python(!+|?)
"Python" followed by one or more ! or one ?
Anchors:
This need to specify match position
Example
Description
^Python
Match "Python" at the start of a string or internal line
Python$
Match "Python" at the end of a string or line
APython
Match "Python" at the start of a string
PythonZ
Match "Python" at the end of a string
bPythonb
Match "Python" at a word boundary
brubB
B is nonword boundary: match "rub" in "rube" and "ruby" but not alone
Python(?=!)
Match "Python", if followed by an exclamation point
Python(?!!)
Match "Python", if not followed by an exclamation point
Special syntax with parentheses:
Example
Description
R(?#comment)
Matches "R". All the rest is a comment
R(?i)uby
Case-insensitive while matching "uby"
R(?i:uby)
Same as above
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#!/usr/bin/python
import os
print "Content-type: text/htmlrnrn";
print "<font size=+1>Environment</font><br>";
for param in os.environ.keys():
print "<b>%20s</b>: %s<br>" % (param,os.environ[param])
GET and POST Methods
You must have come across many situations when you need to pass some information from your browser
to web server and ultimately to your CGI Program. Most frequently browser uses two methods two pass
this information to web server. These methods are GET Method and POST Method.
Passing Information using GET method:
The GET method sends the encoded user information appended to the page request. The page and the
encoded information are separated by the ? character as follows:
http://www.test.com/cgi-bin/hello.py?key1=value1&key2=value2
The GET method is the defualt method to pass information from browser to web server and it produces a
long string that appears in your browser's Location:box. Never use the GET method if you have password
or other sensitive information to pass to the server. The GET method has size limtation: only 1024
characters can be in a request string.
This information is passed using QUERY_STRING header and will be accessible in your CGI Program
through QUERY_STRING environment variable
You can pass information by simply concatenating key and value pairs alongwith any URL or you can use
HTML <FORM> tags to pass information using GET method.
Simple URL Example : Get Method
Here is a simple URL which will pass two values to hello_get.py program using GET method.
/cgi-bin/hello_get.py?first_name=ZARA&last_name=ALI
Below is hello_get.py script to handle input given by web browser. We are going to use cgi module
which makes it very easy to access passed information:
#!/usr/bin/python
# Import modules for CGI handling
import cgi, cgitb
# Create instance of FieldStorage
form = cgi.FieldStorage()
# Get data from fields
first_name = form.getvalue('first_name')
last_name = form.getvalue('last_name')
print
print
print
print
"Content-type:text/htmlrnrn"
"<html>"
"<head>"
"<title>Hello - Second CGI Program</title>"
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This is very easy to send cookies to browser. These cookies will be sent along with HTTP Header before
to Content-type filed. Assuming you want to set UserID and Password as cookies. So cookies setting will
be done as follows
#!/usr/bin/python
print "Set-Cookie:UserID=XYZ;rn"
print "Set-Cookie:Password=XYZ123;rn"
print "Set-Cookie:Expires=Tuesday, 31-Dec-2007 23:12:40 GMT";rn"
print "Set-Cookie:Domain=www.tutorialspoint.com;rn"
print "Set-Cookie:Path=/perl;n"
print "Content-type:text/htmlrnrn"
...........Rest of the HTML Content....
From this example you must have understood how to set cookies. We use Set-Cookie HTTP header to set
cookies.
Here it is optional to set cookies attributes like Expires, Domain, and Path. It is notable that cookies are
set before sending magic line "Content-type:text/htmlrnrn.
Retrieving Cookies
This is very easy to retrieve all the set cookies. Cookies are stored in CGI environment variable
HTTP_COOKIE and they will have following form.
key1=value1;key2=value2;key3=value3....
Here is an example of how to retrieving cookies.
#!/usr/bin/python
# Import modules for CGI handling
from os import environ
import cgi, cgitb
if environ.has_key('HTTP_COOKIE'):
for cookie in map(strip, split(environ['HTTP_COOKIE'], ';')):
(key, value ) = split(cookie, '=');
if key == "UserID":
user_id = value
if key == "Password":
password = value
print "User ID = %s" % user_id
print "Password = %s" % password
This will produce following result for the cookies set by above script:
User ID = XYZ
Password = XYZ123
File Upload Example:
To upload a file the HTML form must have the enctype attribute set to multipart/form-data. The input
tag with the file type will create a "Browse" button.
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<html>
<body>
<form enctype="multipart/form-data"
action="save_file.py" method="post">
<p>File: <input type="file" name="filename" /></p>
<p><input type="submit" value="Upload" /></p>
</form>
</body>
</html>
The result of this code is the following form:
File:
Note: Above example has been disabled intentionally to save people uploading file on our server. But
you can try above code with your server.
Here is the script save_file.py to handle file upload:
#!/usr/bin/python
import cgi, os
import cgitb; cgitb.enable()
form = cgi.FieldStorage()
# Get filename here.
fileitem = form['filename']
# Test if the file was uploaded
if fileitem.filename:
# strip leading path from file name to avoid
# directory traversal attacks
fn = os.path.basename(fileitem.filename)
open('/tmp/' + fn, 'wb').write(fileitem.file.read())
message = 'The file "' + fn + '" was uploaded successfully'
else:
message = 'No file was uploaded'
print """
Content-Type: text/htmln
<html>
<body>
<p>%s</p>
</body>
</html>
""" % (message,)
Note: If you are running above script on Unix/Linux then you would have to take care of replacing file
separator as follows, otherwise on your windows machine above open() statement should work fine.
fn = os.path.basename(fileitem.filename.replace("", "/" ))
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..................................
READ Operation:
READ Operation on any databasse means to fetch some useful information from the database.
Once our database connection is established, we are ready to make a query into this database. We can
use either fetchone() method to fetch single record or fetchall method to fetech multiple values from a
database table.
fetchone(): This method fetches the next row of a query result set. A result set is an object that is
returned when a cursor object is used to query a table.
fetchall(): This method fetches all the rows in a result set. If some rows have already been
extracted from the result set, the fetchall() method retrieves the remaining rows from the result set.
rowcount: This is a read-only attribute and returns the number of rows that were affected by an
execute() method.
Example:
Following is the procedure to query all the records from EMPLOYEE table having salary more than 1000.
#!/usr/bin/python
import MySQLdb
# Open database connection
db = MySQLdb.connect("localhost","testuser","test123","TESTDB" )
# prepare a cursor object using cursor() method
cursor = db.cursor()
# Prepare SQL query to INSERT a record into the database.
sql = "SELECT * FROM EMPLOYEE
WHERE INCOME > '%d'" % (1000)
try:
# Execute the SQL command
cursor.execute(sql)
# Fetch all the rows in a list of lists.
results = cursor.fetchall()
for row in results:
fname = row[0]
lname = row[1]
age = row[2]
sex = row[3]
income = row[4]
# Now print fetched result
print "fname=%s,lname=%s,age=%d,sex=%s,income=%d" %
(fname, lname, age, sex, income )
except:
print "Error: unable to fecth data"
# disconnect from server
db.close()
This will produce following result:
fname=Mac, lname=Mohan, age=20, sex=M, income=2000
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Python - Sending Email using SMTP
Simple Mail Transfer Protocol (SMTP) is a protocol which handles sending e-mail and routing e-mail
between mail servers.
Python provides smtplib module which defines an SMTP client session object that can be used to send
mail to any Internet machine with an SMTP or ESMTP listener daemon.
Here is a simple syntax to create one SMTP object which can later be used to send an email:
import smtplib
smtpObj = smtplib.SMTP( [host [, port [, local_hostname]]] )
Here is the detail of the parameters:
host: This is the host running your SMTP server. You can specifiy IP address of the host or a
domain name like tutorialspoint.com. This is optional argument.
port: If you are providing host argument then you need to specifiy a port where SMTP server is
listening. Usually this port would be 25.
local_hostname: If your SMTP server is running on your local machine then you can specify just
localhost as of this option.
An SMTP object has an instance method called sendmail, which will typically be used to do the work of
mailing a message. It takes three parameters:
The sender - A string with the address of the sender.
The receivers - A list of strings, one for each recipient.
The message - A message as a string formatted as specified in the various RFCs.
Example:
Here is a simple way to send one email using Python script. Try it once:
#!/usr/bin/python
import smtplib
sender = 'from@fromdomain.com'
receivers = ['to@todomain.com']
message = """From: From Person <from@fromdomain.com>
To: To Person <to@todomain.com>
Subject: SMTP e-mail test
This is a test e-mail message.
"""
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Python - Multithreaded Programming
Running several threads is similar to running several different programs concurrently, but with the
following benefits:
Multiple threads within a process share the same data space with the main thread and can therefore
share information or communicate with each other more easily than if they were separate
processes.
Threads sometimes called light-weight processes and they do not require much memory overhead;
theycare cheaper than processes.
A thread has a beginning, an execution sequence, and a conclusion. It has an instruction pointer that
keeps track of where within its context it is currently running.
It can be pre-empted (interrupted)
It can temporarily be put on hold (also known as sleeping) while other threads are running - this is
called yielding.
Starting a New Thread:
To spawn another thread, you need to call following method available in thread module:
thread.start_new_thread ( function, args[, kwargs] )
This method call enables a fast and efficient way to create new threads in both Linux and Windows.
The method call returns immediately and the child thread starts and calls function with the passed list of
agrs. When function returns, the thread terminates.
Here args is a tuple of arguments; use an empty tuple to call function without passing any arguments.
kwargs is an optional dictionary of keyword arguments.
Example:
#!/usr/bin/python
import thread
import time
# Define a function for the thread
def print_time( threadName, delay):
count = 0
while count < 5:
time.sleep(delay)
count += 1
print "%s: %s" % ( threadName, time.ctime(time.time()) )
# Create two threads as follows
try:
thread.start_new_thread( print_time, ("Thread-1", 2, ) )
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thread.start_new_thread( print_time, ("Thread-2", 4, ) )
except:
print "Error: unable to start thread"
while 1:
pass
This would produce following result:
Thread-1:
Thread-1:
Thread-2:
Thread-1:
Thread-2:
Thread-1:
Thread-1:
Thread-2:
Thread-2:
Thread-2:
Thu
Thu
Thu
Thu
Thu
Thu
Thu
Thu
Thu
Thu
Jan
Jan
Jan
Jan
Jan
Jan
Jan
Jan
Jan
Jan
22
22
22
22
22
22
22
22
22
22
15:42:17
15:42:19
15:42:19
15:42:21
15:42:23
15:42:23
15:42:25
15:42:27
15:42:31
15:42:35
2009
2009
2009
2009
2009
2009
2009
2009
2009
2009
Although it is very effective for low-level threading, but the thread module is very limited compared to
the newer threading module.
The Threading Module:
The newer threading module included with Python 2.4 provides much more powerful, high-level support
for threads than the thread module discussed in the previous section.
The threading module exposes all the methods of the thread module and provides some additional
methods:
threading.activeCount(): Returns the number of thread objects that are active.
threading.currentThread(): Returns the number of thread objects in the caller's thread control.
threading.enumerate(): Returns a list of all thread objects that are currently active.
In addition to the methods, the threading module has the Thread class that implements threading. The
methods provided by the Thread class are as follows:
run(): The run() method is the entry point for a thread.
start(): The start() method starts a thread by calling the run method.
join([time]): The join() waits for threads to terminate.
isAlive(): The isAlive() method checks whether a thread is still executing.
getName(): The getName() method returns the name of a thread.
setName(): The setName() method sets the name of a thread.
Creating Thread using Threading Module:
To implement a new thread using the threading module, you have to do the following:
Define a new subclass of the Thread class.
Override the __init__(self [,args]) method to add additional arguments.
Then override the run(self [,args]) method to implement what the thread should do when started.
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Thread-2: Thu Jan 22 15:53:14 2009
Exiting Thread-2
Exiting Main Thread
Synchronizing Threads:
The threading module provided with Python includes a simple-to-implement locking mechanism that will
allow you to synchronize threads. A new lock is created by calling the Lock() method, which returns the
new lock.
The acquire(blocking) method the new lock object would be used to force threads to run synchronously.
The optional blocking parameter enables you to control whether the thread will wait to acquire the lock.
If blocking is set to 0, the thread will return immediately with a 0 value if the lock cannot be acquired and
with a 1 if the lock was acquired. If blocking is set to 1, the thread will block and wait for the lock to be
released.
The release() method of the the new lock object would be used to release the lock when it is no longer
required.
Example:
#!/usr/bin/python
import threading
import time
class myThread (threading.Thread):
def __init__(self, threadID, name, counter):
self.threadID = threadID
self.name = name
self.counter = counter
threading.Thread.__init__(self)
def run(self):
print "Starting " + self.name
# Get lock to synchronize threads
threadLock.acquire()
print_time(self.name, self.counter, 3)
# Free lock to release next thread
threadLock.release()
def print_time(threadName, delay, counter):
while counter:
time.sleep(delay)
print "%s: %s" % (threadName, time.ctime(time.time()))
counter -= 1
threadLock = threading.Lock()
threads = []
# Create new threads
thread1 = myThread(1, "Thread-1", 1)
thread2 = myThread(2, "Thread-2", 2)
# Start new Threads
thread1.start()
thread2.start()
# Add threads to thread list
threads.append(thread1)
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data = q.get()
queueLock.release()
print "%s processing %s" % (threadName, data)
else:
queueLock.release()
time.sleep(1)
threadList = ["Thread-1", "Thread-2", "Thread-3"]
nameList = ["One", "Two", "Three", "Four", "Five"]
queueLock = threading.Lock()
workQueue = Queue.Queue(10)
threads = []
threadID = 1
# Create new threads
for tName in threadList:
thread = myThread(threadID, tName, workQueue)
thread.start()
threads.append(thread)
threadID += 1
# Fill the queue
queueLock.acquire()
for word in nameList:
workQueue.put(word)
queueLock.release()
# Wait for queue to empty
while not workQueue.empty():
pass
# Notify threads it's time to exit
exitFlag = 1
# Wait for all threads to complete
for t in threads:
t.join()
print "Exiting Main Thread"
This would produce following result:
Starting Thread-2
Starting Thread-1
Starting Thread-3
Thread-2 processing
Thread-1 processing
Thread-3 processing
Thread-2 processing
Thread-1 processing
Exiting Thread-3
Exiting Thread-2
Exiting Thread-1
Exiting Main Thread
One
Two
Three
Four
Five
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<movie title="Trigun">
<type>Anime, Action</type>
<format>DVD</format>
<episodes>4</episodes>
<rating>PG</rating>
<stars>10</stars>
<description>Vash the Stampede!</description>
</movie>
<movie title="Ishtar">
<type>Comedy</type>
<format>VHS</format>
<rating>PG</rating>
<stars>2</stars>
<description>Viewable boredom</description>
</movie>
</collection>
Parsing XML with SAX APIs:
SAX is a standard interface for event-driven XML parsing. Parsing XML with SAX generally requires you to
create your own ContentHandler, by subclassing xml.sax.ContentHandler.
Your ContentHandler handles the particular tags and attributes of your flavor(s) of XML. A ContentHandler
object provides methods to handle various parsing events. Its owning parser calls ContentHandler
methods as it parses the XML file.
The methods startDocument and endDocument are called at the start and the end of the XML file. The
method characters(text) is passed character data of the XML file via the parameter text.
The ContentHandler is called at the start and end of each element. If the parser is not in namespace
mode, the methods startElement(tag, attributes) and endElement(tag) are called; otherwise, the
corresponding methods startElementNS and endElementNS are called. Here, tag is the element tag, and
attributes is an Attributes object.
Here are other important methods to understand before proceeding:
The make_parser Method:
Following method creates a new parser object and returns it. The parser object created will be of the first
parser type the system finds.
xml.sax.make_parser( [parser_list] )
Here is the detail of the parameters:
parser_list: The optional argument consisting of a list of parsers to use, which must all implement
the make_parser method.
The parse Method:
Following method creates a SAX parser and use it to parse a document.
xml.sax.parse( xmlfile, contenthandler[, errorhandler])
Here is the detail of the parameters:
xmlfile: This is the name of the XML file to read from.
contenthandler: This must be a ContentHandler object.
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errorhandler: If specified, errorhandler must be a SAX ErrorHandler object.
The parseString Method:
There is one more method to create a SAX parser and to parse the specified XML string.
xml.sax.parseString(xmlstring, contenthandler[, errorhandler])
Here is the detail of the parameters:
xmlstring: This is the name of the XML string to read from.
contenthandler: This must be a ContentHandler object.
errorhandler: If specified, errorhandler must be a SAX ErrorHandler object.
Example:
#!/usr/bin/python
import xml.sax
class MovieHandler( xml.sax.ContentHandler ):
def __init__(self):
self.CurrentData = ""
self.type = ""
self.format = ""
self.year = ""
self.rating = ""
self.stars = ""
self.description = ""
# Call when an element starts
def startElement(self, tag, attributes):
self.CurrentData = tag
if tag == "movie":
print "*****Movie*****"
title = attributes["title"]
print "Title:", title
# Call when an elements ends
def endElement(self, tag):
if self.CurrentData == "type":
print "Type:", self.type
elif self.CurrentData == "format":
print "Format:", self.format
elif self.CurrentData == "year":
print "Year:", self.year
elif self.CurrentData == "rating":
print "Rating:", self.rating
elif self.CurrentData == "stars":
print "Stars:", self.stars
elif self.CurrentData == "description":
print "Description:", self.description
self.CurrentData = ""
# Call when a character is read
def characters(self, content):
if self.CurrentData == "type":
self.type = content
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The Document Object Model, or "DOM," is a cross-language API from the World Wide Web Consortium
(W3C) for accessing and modifying XML documents.
The DOM is extremely useful for random-access applications. SAX only allows you a view of one bit of
the document at a time. If you are looking at one SAX element, you have no access to another.
Here is the easiest way to quickly load an XML document and to create a minidom object using the
xml.dom module. The minidom object provides a simple parser method that will quickly create a DOM
tree from the XML file.
The sample phrase calls the parse( file [,parser] ) function of the minidom object to parse the XML file
designated by file into a DOM tree object.
#!/usr/bin/python
from xml.dom.minidom import parse
import xml.dom.minidom
# Open XML document using minidom parser
DOMTree = xml.dom.minidom.parse("text.xml")
collection = DOMTree.documentElement
if collection.hasAttribute("shelf"):
print "Root element : %s" % collection.getAttribute("shelf")
# Get all the movies in the collection
movies = collection.getElementsByTagName("movie")
# Print detail of each movie.
for movie in movies:
print "*****Movie*****"
if movie.hasAttribute("title"):
print "Title: %s" % movie.getAttribute("title")
type = movie.getElementsByTagName('type')[0]
print "Type: %s" % type.childNodes[0].data
format = movie.getElementsByTagName('format')[0]
print "Format: %s" % format.childNodes[0].data
rating = movie.getElementsByTagName('rating')[0]
print "Rating: %s" % rating.childNodes[0].data
description = movie.getElementsByTagName('description')[0]
print "Description: %s" % description.childNodes[0].data
This would produce following result:
Root element : New Arrivals
*****Movie*****
Title: Enemy Behind
Type: War, Thriller
Format: DVD
Rating: PG
Description: Talk about a US-Japan war
*****Movie*****
Title: Transformers
Type: Anime, Science Fiction
Format: DVD
Rating: R
Description: A schientific fiction
*****Movie*****
Title: Trigun
Type: Anime, Action
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Each one of the preceding declarations returns a Python object. There's no such thing as a void function
in Python as there is in C. If you don't want your functions to return a value, return the C equivalent of
Python's None value. The Python headers define a macro, Py_RETURN_NONE, that does this for us.
The names of your C functions can be whatever you like as they will never be seen outside of the
extension module. So they would be defined as static function.
Your C functions usually are named by combining the Python module and function names together, as
shown here:
static PyObject *module_func(PyObject *self, PyObject *args) {
/* Do your stuff here. */
Py_RETURN_NONE;
}
This would be a Python function called func inside of the module module. You'll be putting pointers to
your C functions into the method table for the module that usually comes next in your source code.
The method mapping table:
This method table is a simple array of PyMethodDef structures. That structure looks something like this:
struct PyMethodDef {
char *ml_name;
PyCFunction ml_meth;
int ml_flags;
char *ml_doc;
};
Here is the description of the members of this structure:
ml_name: This is the name of the function as the Python interpreter will present it when it is used
in Python programs.
ml_meth: This must be the address to a function that has any one of the signatures described in
previous seection.
ml_flags: This tells the interpreter which of the three signatures ml_meth is using.
This flag will usually have a value of METH_VARARGS.
This flag can be bitwise or'ed with METH_KEYWORDS if you want to allow keyword
arguments into your function.
This can also have a value of METH_NOARGS that indicates you don't want to accept any
arguments.
ml_doc: This is the docstring for the function, which could be NULL if you don't feel like writing
one
This table needs to be terminated with a sentinel that consists of NULL and 0 values for the appropriate
members.
Example:
For the above defined function, we would have following method mapping table:
static PyMethodDef module_methods[] = {
{ "func", (PyCFunction)module_func, METH_NOARGS, NULL },
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{ NULL, NULL, 0, NULL }
The initialization function:
The last part of your extension module is the initialization function. This function is called by the Python
interpreter when the module is loaded. It's required that the function be named initModule, where
Module is the name of the module.
The initialization function needs to be exported from the library you'll be building. The Python headers
define PyMODINIT_FUNC to include the appropriate incantations for that to happen for the particular
environment in which we're compiling. All you have to do is use it when defining the function.
Your C initialization function generally has the following overall structure:
PyMODINIT_FUNC initModule() {
Py_InitModule3(func, module_methods, "docstring...");
}
Here is the description of Py_InitModule3 function:
func: This is the function to be exported.
module_methods: This is the mapping table name defined above.
docstring: This is the comment you want to give in your extension.
Putting this all together looks like the following:
#include <Python.h>
static PyObject *module_func(PyObject *self, PyObject *args) {
/* Do your stuff here. */
Py_RETURN_NONE;
}
static PyMethodDef module_methods[] = {
{ "func", (PyCFunction)module_func, METH_NOARGS, NULL },
{ NULL, NULL, 0, NULL }
};
PyMODINIT_FUNC initModule() {
Py_InitModule3(func, module_methods, "docstring...");
}
Example:
A simple example that makes use of all the above concepts:
#include <Python.h>
static PyObject* helloworld(PyObject* self)
{
return Py_BuildValue("s", "Hello, Python extensions!!");
}
static char helloworld_docs[] =
"helloworld( ): Any message you want to put here!!n";
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static PyMethodDef helloworld_funcs[] = {
{"helloworld", (PyCFunction)helloworld,
METH_NOARGS, helloworld_docs},
{NULL}
};
void inithelloworld(void)
{
Py_InitModule3("helloworld", helloworld_funcs,
"Extension module example!");
}
Here the Py_BuildValue function is used to build a Python value. Save above code in hello.c file. We
would see how to compile and install this module to be called from Python script.
Building and Installing Extensions:
The distutils package makes it very easy to distribute Python modules, both pure Python and extension
modules, in a standard way. Modules are distributed in source form and built and installed via a setup
script usually called setup.py as follows.
For the above module, you would have to prepare following setup.py script:
from distutils.core import setup, Extension
setup(name='helloworld', version='1.0',
ext_modules=[Extension('helloworld', ['hello.c'])])
Now use the following command, which would perform all needed compilation and linking steps, with the
right compiler and linker commands and flags, and copies the resulting dynamic library into an
appropriate directory:
$ python setup.py install
On Unix-based systems, you'll most likely need to run this command as root in order to have permissions
to write to the site-packages directory. This usually isn't a problem on Windows
Import Extensions:
Once you installed your extension, you would be able to import and call that extension in your Python
script as follows:
#!/usr/bin/python
import helloworld
print helloworld.helloworld()
This would produce following result:
Hello, Python extensions!!
Passing Function Parameters:
Because you'll most likely want to define functions that do accept arguments, you can use one of the
other signatures for your C functions. For example, following function, that accepts some number of
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parameters, would be defined like this:
static PyObject *module_func(PyObject *self, PyObject *args) {
/* Parse args and do something interesting here. */
Py_RETURN_NONE;
}
The method table containing an entry for the new function would look like this:
static PyMethodDef module_methods[] = {
{ "func", (PyCFunction)module_func, METH_NOARGS, NULL },
{ "func", module_func, METH_VARARGS, NULL },
{ NULL, NULL, 0, NULL }
};
You can use API PyArg_ParseTuple function to extract the arguments from the one PyObject pointer
passed into your C function.
The first argument to PyArg_ParseTuple is the args argument. This is the object you'll be parsing. The
second argument is a format string describing the arguments as you expect them to appear. Each
argument is represented by one or more characters in the format string as follows.
static PyObject *module_func(PyObject *self, PyObject *args) {
int i;
double d;
char *s;
if (!PyArg_ParseTuple(args, "ids", &i, &d, &s)) {
return NULL;
}
}
/* Do something interesting here. */
Py_RETURN_NONE;
Compiling the new version of your module and importing it will enable you to invoke the new function
with any number of arguments of any type:
module.func(1, s="three", d=2.0)
module.func(i=1, d=2.0, s="three")
module.func(s="three", d=2.0, i=1)
You can probably come up with even more variations.
The PyArg_ParseTuple Function:
Here is the standard signature for PyArg_ParseTuple function:
int PyArg_ParseTuple(PyObject* tuple,char* format,...)
This function returns 0 for errors, and a value not equal to 0 for success. tuple is the PyObject* that was
the C function's second argument. Here format is a C string that describes mandatory and optional
arguments.
Here is a list of format codes for PyArg_ParseTuple function:
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static PyObject *foo_add_subtract(PyObject *self, PyObject *args) {
int a;
int b;
if (!PyArg_ParseTuple(args, "ii", &a, &b)) {
return NULL;
}
return Py_BuildValue("ii", a + b, a - b);
}
This is what it would look like if implemented in Python:
def add_subtract(a, b):
return (a + b, a - b)
The Py_BuildValue Function:
Here is the standard signature for Py_BuildValue function:
PyObject* Py_BuildValue(char* format,...)
Here format is a C string that describes the Python object to build. The following arguments of
Py_BuildValue are C values from which the result is built. The PyObject* result is a new reference.
Following table lists the commonly used code strings, of which zero or more are joined into string format.
Code
C type
Meaning
c
char
A C char becomes a Python string of length 1.
d
double
A C double becomes a Python float.
f
float
A C float becomes a Python float.
i
int
A C int becomes a Python int.
l
long
A C long becomes a Python int.
N
PyObject*
Passes a Python object and steals a reference.
O
PyObject*
Passes a Python object and INCREFs it as normal.
O&
convert+void*
Arbitrary conversion
s
char*
C 0-terminated char* to Python string, or NULL to None.
s#
char*+int
C char* and length to Python string, or NULL to None.
u
Py_UNICODE*
C-wide, null-terminated string to Python Unicode, or NULL to None.
u#
Py_UNICODE*+int C-wide string and length to Python Unicode, or NULL to None.
w#
char*+int
Read/write single-segment buffer to C address and length.
z
char*
Like s, also accepts None (sets C char* to NULL).
z#
char*+int
Like s#, also accepts None (sets C char* to NULL).
(...)
as per ...
Builds Python tuple from C values.
[...]
as per ...
Builds Python list from C values.
{...}
as per ...
Builds Python dictionary from C values, alternating keys and values.
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root# python
Python 2.5 (r25:51908, Nov 6 2007, 16:54:01)
[GCC 4.1.2 20070925 (Red Hat 4.1.2-27)] on linux2
Type "help", "copyright", "credits" or "license" for more info.
>>>
Type the following text to the right of the Python prompt and press the Enter key:
>>> print "Hello, Python!";
This will produce following result:
Hello, Python!
Python Identifiers:
A Python identifier is a name used to identify a variable, function, class, module, or other object. An
identifier starts with a letter A to Z or a to z or an underscore (_) followed by zero or more letters,
underscores, and digits (0 to 9).
Python does not allow punctuation characters such as @, $, and % within identifiers. Python is a case
sensitive programming language. Thus Manpower and manpower are two different identifiers in
Python.
Here are following identifier naming convention for Python:
Class names start with an uppercase letter and all other identifiers with a lowercase letter.
Starting an identifier with a single leading underscore indicates by convention that the identifier is
meant to be private.
Starting an identifier with two leading underscores indicates a strongly private identifier.
If the identifier also ends with two trailing underscores, the identifier is a language-defined special
name.
Reserved Words:
The following list shows the reserved words in Python. These reserved words may not be used as
constant or variable or any other identifier names.
Keywords contain lowercase letters only.
and
exec
not
assert
finally
or
break
for
pass
class
from
print
continue
global
raise
def
if
return
del
import
try
elif
in
while
else
is
with
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lambda
yield
Lines and Indentation:
One of the first caveats programmers encounter when learning Python is the fact that there are no braces
to indicate blocks of code for class and function definitions or flow control. Blocks of code are denoted by
line indentation, which is rigidly enforced.
The number of spaces in the indentation is variable, but all statements within the block must be indented
the same amount. Both blocks in this example are fine:
if True:
print "True"
else:
print "False"
However, the second block in this example will generate an error:
if True:
print "Answer"
print "True"
else:
print "Answer"
print "False"
Multi-Line Statements:
Statements in Python typically end with a new line. Python does, however, allow the use of the line
continuation character () to denote that the line should continue. For example:
total = item_one +
item_two +
item_three
Statements contained within the [], {}, or () brackets do not need to use the line continuation character.
For example:
days = ['Monday', 'Tuesday', 'Wednesday',
'Thursday', 'Friday']
Quotation in Python:
Python accepts single ('), double (") and triple (''' or """) quotes to denote string literals, as long as the
same type of quote starts and ends the string.
The triple quotes can be used to span the string across multiple lines. For example, all the following are
legal:
word = 'word'
sentence = "This is a sentence."
paragraph = """This is a paragraph. It is
made up of multiple lines and sentences."""
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if expression :
suite
elif expression :
suite
else :
suite
Python - Variable Types:
Variables are nothing but reserved memory locations to store values. This means that when you create a
variable you reserve some space in memory.
Based on the data type of a variable, the interpreter allocates memory and decides what can be stored in
the reserved memory. Therefore, by assigning different data types to variables, you can store integers,
decimals, or characters in these variables.
Assigning Values to Variables:
The operand to the left of the = operator is the name of the variable, and the operand to the right of the
= operator is the value stored in the variable. For example:
counter = 100
miles
= 1000.0
name
= "John"
# An integer assignment
# A floating point
# A string
print counter
print miles
print name
Standard Data Types:
Python has five standard data types:
Numbers
String
List
Tuple
Dictionary
Python Numbers:
Number objects are created when you assign a value to them. For example:
var1 = 1
var2 = 10
Python supports four different numerical types:
int (signed integers)
long (long integers [can also be represented in octal and hexadecimal])
float (floating point real values)
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complex (complex numbers)
Here are some examples of numbers:
int
long
float
complex
10
51924361L
0.0
3.14j
100
-0x19323L
15.20
45.j
-786
0122L
-21.9
9.322e-36j
080
0xDEFABCECBDAECBFBAEl
32.3+e18
.876j
-0490
535633629843L
-90.
-.6545+0J
-0x260
-052318172735L
-32.54e100
3e+26J
0x69
-4721885298529L
70.2-E12
4.53e-7j
Python Strings:
Strings in Python are identified as a contiguous set of characters in between quotation marks.
Example:
str = 'Hello World!'
print
print
print
print
print
print
str
str[0]
str[2:5]
str[2:]
str * 2
str + "TEST"
#
#
#
#
#
#
Prints
Prints
Prints
Prints
Prints
Prints
complete string
first character of the string
characters starting from 3rd to 6th
string starting from 3rd character
string two times
concatenated string
Python Lists:
Lists are the most versatile of Python's compound data types. A list contains items separated by commas
and enclosed within square brackets ([]).
#!/usr/bin/python
list = [ 'abcd', 786 , 2.23, 'john', 70.2 ]
tinylist = [123, 'john']
print
print
print
print
print
print
list
#
list[0]
#
list[1:3]
#
list[2:]
#
tinylist * 2 #
list + tinylist
Prints complete list
Prints first element of the list
Prints elements starting from 2nd to 4th
Prints elements starting from 3rd element
Prints list two times
# Prints concatenated lists
Python Tuples:
A tuple is another sequence data type that is similar to the list. A tuple consists of a number of values
separated by commas. Unlike lists, however, tuples are enclosed within parentheses.
Tuples can be thought of as read-only lists.
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tuple = ( 'abcd', 786 , 2.23, 'john', 70.2
tinytuple = (123, 'john')
print
print
print
print
print
print
tuple
#
tuple[0]
#
tuple[1:3]
#
tuple[2:]
#
tinytuple * 2
#
tuple + tinytuple
)
Prints complete list
Prints first element of the list
Prints elements starting from 2nd to 4th
Prints elements starting from 3rd element
Prints list two times
# Prints concatenated lists
Python Dictionary:
Python 's dictionaries are hash table type. They work like associative arrays or hashes found in Perl and
consist of key-value pairs.
tinydict = {'name': 'john','code':6734, 'dept': 'sales'}
print dict['one']
# Prints value for 'one' key
print dict[2]
# Prints value for 2 key
print tinydict
# Prints complete dictionary
print tinydict.keys()
# Prints all the keys
print tinydict.values() # Prints all the values
Python - Basic Operators:
Operator
Description
Example
+
Addition - Adds values on either side of the
operator
a + b will give 30
-
Subtraction - Subtracts right hand operand
from left hand operand
a - b will give -10
*
Multiplication - Multiplies values on either
side of the operator
a * b will give 200
/
Division - Divides left hand operand by right
hand operand
b / a will give 2
%
Modulus - Divides left hand operand by right
hand operand and returns remainder
b % a will give 0
**
Exponent - Performs exponential (power)
calculation on operators
a**b will give 10 to the power 20
//
Floor Division - The division of operands
where the result is the quotient in which the
digits after the decimal point are removed.
9//2 is equal to 4 and 9.0//2.0 is equal to
4.0
==
Checks if the value of two operands are equal
or not, if yes then condition becomes true.
(a == b) is not true.
!=
Checks if the value of two operands are equal
or not, if values are not equal then condition
becomes true.
(a != b) is true.
<>
Checks if the value of two operands are equal
or not, if values are not equal then condition
becomes true.
(a <> b) is true. This is similar to !=
operator.
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while expression:
statement(s)
The Infinite Loops:
You must use caution when using while loops because of the possibility that this condition never resolves
to a false value. This results in a loop that never ends. Such a loop is called an infinite loop.
An infinite loop might be useful in client/server programming where the server needs to run continuously
so that client programs can communicate with it as and when required.
Single Statement Suites:
Similar to the if statement syntax, if your while clause consists only of a single statement, it may be
placed on the same line as the while header.
Here is an example of a one-line while clause:
while expression : statement
The for Loop:
The syntax of the loop look is:
for iterating_var in sequence:
statements(s)
Iterating by Sequence Index:
An alternative way of iterating through each item is by index offset into the sequence itself:
fruits = ['banana', 'apple', 'mango']
for index in range(len(fruits)):
print 'Current fruit :', fruits[index]
print "Good bye!"
The break Statement:
The break statement in Python terminates the current loop and resumes execution at the next statement,
just like the traditional break found in C.
The most common use for break is when some external condition is triggered requiring a hasty exit from
a loop. The break statement can be used in both while and for loops.
for letter in 'Python':
# First Example
if letter == 'h':
break
print 'Current Letter :', letter
var = 10
# Second Example
while var > 0:
print 'Current variable value :', var
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You can define functions to provide the required functionality. Here are simple rules to define a function
in Python:
Function blocks begin with the keyword def followed by the function name and parentheses ( ( ) ).
Any input parameters or arguments should be placed within these parentheses. You can also define
parameters inside these parentheses.
The first statement of a function can be an optional statement - the documentation string of the
function or docstring.
The code block within every function starts with a colon (:) and is indented.
The statement return [expression] exits a function, optionally passing back an expression to the
caller. A return statement with no arguments is the same as return None.
Syntax:
def functionname( parameters ):
"function_docstring"
function_suite
return [expression]
By default, parameters have a positional behavior, and you need to inform them in the same order that
they were defined.
Example:
Here is the simplest form of a Python function. This function takes a string as input parameter and prints
it on standard screen.
def printme( str ):
"This prints a passed string into this function"
print str
return
Calling a Function
Defining a function only gives it a name, specifies the parameters that are to be included in the function,
and structures the blocks of code.
Once the basic structure of a function is finalized, you can execute it by calling it from another function or
directly from the Python prompt.
Following is the example to call printme() function:
#!/usr/bin/python
# Function definition is here
def printme( str ):
"This prints a passed string into this function"
print str;
return;
# Now you can call printme function
printme("I'm first call to user defined function!");
printme("Again second call to the same function");
This would produce following result:
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I'm first call to user defined function!
Again second call to the same function
Python - Modules:
A module allows you to logically organize your Python code. Grouping related code into a module makes
the code easier to understand and use.
A module is a Python object with arbitrarily named attributes that you can bind and reference.
Simply, a module is a file consisting of Python code. A module can define functions, classes, and
variables. A module can also include runnable code.
Example:
The Python code for a module named aname normally resides in a file named aname.py. Here's an
example of a simple module, hello.py
def print_func( par ):
print "Hello : ", par
return
The import Statement:
You can use any Python source file as a module by executing an import statement in some other Python
source file. import has the following syntax:
import module1[, module2[,... moduleN]
When the interpreter encounters an import statement, it imports the module if the module is present in
the search path. Asearch path is a list of directories that the interpreter searches before importing a
module.
Example:
To import the module hello.py, you need to put the following command at the top of the script:
#!/usr/bin/python
# Import module hello
import hello
# Now you can call defined function that module as follows
hellp.print_func("Zara")
This would produce following result:
Hello : Zara
A module is loaded only once, regardless of the number of times it is imported. This prevents the module
execution from happening over and over again if multiple imports occur.
Opening and Closing Files:
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The open Function:
Before you can read or write a file, you have to open it using Python's built-in open() function. This
function creates a file object which would be utilized to call other support methods associated with it.
Syntax:
file object = open(file_name [, access_mode][, buffering])
Here is paramters detail:
file_name: The file_name argument is a string value that contains the name of the file that you
want to access.
access_mode: The access_mode determines the mode in which the file has to be opened ie. read,
write append etc. A complete list of possible values is given below in the table. This is optional
parameter and the default file access mode is read (r)
buffering: If the buffering value is set to 0, no buffering will take place. If the buffering value is 1,
line buffering will be performed while accessing a file. If you specify the buffering value as an
integer greater than 1, then buffering action will be performed with the indicated buffer size. This is
optional paramter.
Here is a list of the different modes of opening a file:
Modes
Description
r
Opens a file for reading only. The file pointer is placed at the beginning of the file. This is the
default mode.
rb
Opens a file for reading only in binary format. The file pointer is placed at the beginning of the
file. This is the default mode.
r+
Opens a file for both reading and writing. The file pointer will be at the beginning of the file.
rb+
Opens a file for both reading and writing in binary format. The file pointer will be at the
beginning of the file.
w
Opens a file for writing only. Overwrites the file if the file exists. If the file does not exist,
creates a new file for writing.
wb
Opens a file for writing only in binary format. Overwrites the file if the file exists. If the file
does not exist, creates a new file for writing.
w+
Opens a file for both writing and reading. Overwrites the existing file if the file exists. If the
file does not exist, creates a new file for reading and writing.
wb+
Opens a file for both writing and reading in binary format. Overwrites the existing file if the file
exists. If the file does not exist, creates a new file for reading and writing.
a
Opens a file for appending. The file pointer is at the end of the file if the file exists. That is, the
file is in the append mode. If the file does not exist, it creates a new file for writing.
ab
Opens a file for appending in binary format. The file pointer is at the end of the file if the file
exists. That is, the file is in the append mode. If the file does not exist, it creates a new file for
writing.
a+
Opens a file for both appending and reading. The file pointer is at the end of the file if the file
exists. The file opens in the append mode. If the file does not exist, it creates a new file for
reading and writing.
ab+
Opens a file for both appending and reading in binary format. The file pointer is at the end of
the file if the file exists. The file opens in the append mode. If the file does not exist, it creates
a new file for reading and writing.
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The file object atrributes:
Once a file is opened and you have one file object, you can get various information related to that file.
Here is a list of all attributes related to file object:
Attribute
Description
file.closed
Returns true if file is closed, false otherwise.
file.mode
Returns access mode with which file was opened.
file.name
Returns name of the file.
file.softspace
Returns false if space explicitly required with print, true otherwise.
The close() Method:
The close() method of a file object flushes any unwritten information and closes the file object, after
which no more writing can be done.
fileObject.close();
Reading and Writing Files:
The write() Method:
Syntax:
fileObject.write(string);
The read() Method:
Syntax:
fileObject.read([count]);
File Positions:
The tell() method tells you the current position within the file in other words, the next read or write will
occur at that many bytes from the beginning of the file:
The seek(offset[, from]) method changes the current file position. The offset argument indicates the
number of bytes to be moved. The from argument specifies the reference position from where the bytes
are to be moved.
If from is set to 0, it means use the beginning of the file as the reference position and 1 means use the
current position as the reference position and if it is set to 2 then the end of the file would be taken as
the reference position.
Renaming and Deleting Files:
Syntax:
os.rename(current_file_name, new_file_name)
The remove() Method:
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......................
except ExceptionI:
If there is ExceptionI, then execute this block.
except ExceptionII:
If there is ExceptionII, then execute this block.
......................
else:
If there is no exception then execute this block.
Here are few important points above the above mentioned syntax:
A single try statement can have multiple except statements. This is useful when the try block
contains statements that may throw different types of exceptions.
You can also provide a generic except clause, which handles any exception.
After the except clause(s), you can include an else-clause. The code in the else-block executes if
the code in the try: block does not raise an exception.
The else-block is a good place for code that does not need the try: block's protection.
The except clause with no exceptions:
You can also use the except statement with no exceptions defined as follows:
try:
Do you operations here;
......................
except:
If there is any exception, then execute this block.
......................
else:
If there is no exception then execute this block.
The except clause with multiple exceptions:
You can also use the same except statement to handle multiple exceptions as follows:
try:
Do you operations here;
......................
except(Exception1[, Exception2[,...ExceptionN]]]):
If there is any exception from the given exception list,
then execute this block.
......................
else:
If there is no exception then execute this block.
Standard Exceptions:
Here is a list standard Exceptions available in Python: Standard Exceptions
The try-finally clause:
You can use a finally: block along with a try: block. The finally block is a place to put any code that
must execute, whether the try-block raised an exception or not. The syntax of the try-finally statement is
this:
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try:
Do you operations here;
......................
Due to any exception, this may be skipped.
finally:
This would always be executed.
......................
Argument of an Exception:
An exception can have an argument, which is a value that gives additional information about the problem.
The contents of the argument vary by exception. You capture an exception's argument by supplying a
variable in the except clause as follows:
try:
Do you operations here;
......................
except ExceptionType, Argument:
You can print value of Argument here...
Raising an exceptions:
You can raise exceptions in several ways by using the raise statement. The general syntax for the raise
statement.
Syntax:
raise [Exception [, args [, traceback]]]
User-Defined Exceptions:
Python also allows you to create your own exceptions by deriving classes from the standard built-in
exceptions.
Here is an example related to RuntimeError. Here a class is created that is subclassed from RuntimeError.
This is useful when you need to display more specific information when an exception is caught.
In the try block, the user-defined exception is raised and caught in the except block. The variable e is
used to create an instance of the class Networkerror.
class Networkerror(RuntimeError):
def __init__(self, arg):
self.args = arg
So once you defined above class, you can raise your exception as follows:
try:
raise Networkerror("Bad hostname")
except Networkerror,e:
print e.args
Creating Classes:
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An object's reference count increases when it's assigned a new name or placed in a container (list, tuple,
or dictionary). The object's reference count decreases when it's deleted with del, its reference is
reassigned, or its reference goes out of scope. When an object's reference count reaches zero, Python
collects it automatically.
Class Inheritance:
Instead of starting from scratch, you can create a class by deriving it from a preexisting class by listing
the parent class in parentheses after the new class name:
The child class inherits the attributes of its parent class, and you can use those attributes as if they were
defined in the child class. A child class can also override data members and methods from the parent.
Syntax:
Derived classes are declared much like their parent class; however, a list of base classes to inherit from
are given after the class name:
class SubClassName (ParentClass1[, ParentClass2, ...]):
'Optional class documentation string'
class_suite
Overriding Methods:
You can always override your parent class methods. One reason for overriding parent's methods is
because you may want special or different functionality in your subclass.
class Parent:
# define parent class
def myMethod(self):
print 'Calling parent method'
class Child(Parent): # define child class
def myMethod(self):
print 'Calling child method'
c = Child()
c.myMethod()
# instance of child
# child calls overridden method
Base Overloading Methods:
Following table lists some generic functionality that you can override in your own classes:
SN
Method, Description & Sample Call
1
__init__ ( self [,args...] )
Constructor (with any optional arguments)
Sample Call : obj = className(args)
2
__del__( self )
Destructor, deletes an object
Sample Call : dell obj
3
__repr__( self )
Evaluatable string representation
Sample Call : repr(obj)
4
__str__( self )
Printable string representation
Sample Call : str(obj)
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Matching vs Searching:
Python offers two different primitive operations based on regular expressions: match checks for a match
only at the beginning of the string, while search checks for a match anywhere in the string (this is what
Perl does by default).
Search and Replace:
Some of the most important re methods that use regular expressions is sub.
Syntax:
sub(pattern, repl, string, max=0)
This method replace all occurrences of the RE pattern in string with repl, substituting all occurrences
unless max provided. This method would return modified string.
Regular-expression Modifiers - Option Flags
Regular expression literals may include an optional modifier to control various aspects of matching. The
modifier are specified as an optional flag. You can provide multiple modified using exclusive OR (|), as
shown previously and may be represented by one of these:
Modifier
Description
re.I
Performs case-insensitive matching.
re.L
Interprets words according to the current locale.This interpretation affects the
alphabetic group (w and W), as well as word boundary behavior (b and
B).
re.M
Makes $ match the end of a line (not just the end of the string) and makes ^
match the start of any line (not just the start of the string).
re.S
Makes a period (dot) match any character, including a newline.
re.U
Interprets letters according to the Unicode character set. This flag affects the
behavior of w, W, b, B.
re.X
Permits "cuter" regular expression syntax. It ignores whitespace (except
inside a set [] or when escaped by a backslash), and treats unescaped # as a
comment marker.
Regular-expression patterns:
Except for control characters, (+ ? . * ^ $ ( ) [ ] { } | ), all characters match themselves. You can
escape a control character by preceding it with a backslash.
Following table lists the regular expression syntax that is available in Python.
Pattern
Description
^
Matches beginning of line.
$
Matches end of line.
.
Matches any single character except newline. Using m option allows it to
match newline as well.
[...]
Matches any single character in brackets.
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[^...]
Matches any single character not in brackets
re*
Matches 0 or more occurrences of preceding expression.
re+
Matches 0 or 1 occurrence of preceding expression.
re{ n}
Matches exactly n number of occurrences of preceding expression.
re{ n,}
Matches n or more occurrences of preceding expression.
re{ n, m}
Matches at least n and at most m occurrences of preceding expression.
a| b
Matches either a or b.
(re)
Groups regular expressions and remembers matched text.
(?imx)
Temporarily toggles on i, m, or x options within a regular expression. If in
parentheses, only that area is affected.
(?-imx)
Temporarily toggles off i, m, or x options within a regular expression. If in
parentheses, only that area is affected.
(?: re)
Groups regular expressions without remembering matched text.
(?imx: re)
Temporarily toggles on i, m, or x options within parentheses.
(?-imx: re)
Temporarily toggles off i, m, or x options within parentheses.
(?#...)
Comment.
(?= re)
Specifies position using a pattern. Doesn't have a range.
(?! re)
Specifies position using pattern negation. Doesn't have a range.
(?> re)
Matches independent pattern without backtracking.
w
Matches word characters.
W
Matches nonword characters.
s
Matches whitespace. Equivalent to [tnrf].
S
Matches nonwhitespace.
d
Matches digits. Equivalent to [0-9].
D
Matches nondigits.
A
Matches beginning of string.
Z
Matches end of string. If a newline exists, it matches just before newline.
z
Matches end of string.
G
Matches point where last match finished.
b
Matches word boundaries when outside brackets. Matches backspace (0x08)
when inside brackets.
B
Matches nonword boundaries.
n, t, etc.
Matches newlines, carriage returns, tabs, etc.
1...9
Matches nth grouped subexpression.
10
Matches nth grouped subexpression if it matched already. Otherwise refers to
the octal representation of a character code.
Regular-expression Examples:
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Literal characters:
Example
python
Description
Match "python".
Character classes:
Example
Description
[Pp]ython
Match "Python" or "python"
rub[ye]
Match "ruby" or "rube"
[aeiou]
Match any one lowercase vowel
[0-9]
Match any digit; same as [0123456789]
[a-z]
Match any lowercase ASCII letter
[A-Z]
Match any uppercase ASCII letter
[a-zA-Z0-9]
Match any of the above
[^aeiou]
Match anything other than a lowercase vowel
[^0-9]
Match anything other than a digit
Special Character Classes:
Example
Description
.
Match any character except newline
d
Match a digit: [0-9]
D
Match a nondigit: [^0-9]
s
Match a whitespace character: [ trnf]
S
Match nonwhitespace: [^ trnf]
w
Match a single word character: [A-Za-z0-9_]
W
Match a nonword character: [^A-Za-z0-9_]
Repetition Cases:
Example
Description
ruby?
Match "rub" or "ruby": the y is optional
ruby*
Match "rub" plus 0 or more ys
ruby+
Match "rub" plus 1 or more ys
d{3}
Match exactly 3 digits
d{3,}
Match 3 or more digits
d{3,5}
Match 3, 4, or 5 digits
Nongreedy repetition:
This matches the smallest number of repetitions:
Example
Description
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<.*>
Greedy repetition: matches "<python>perl>"
<.*?>
Nongreedy: matches "<python>" in "<python>perl>"
Grouping with parentheses:
Example
Description
Dd+
No group: + repeats d
(Dd)+
Grouped: + repeats Dd pair
([Pp]ython(, )?)+
Match "Python", "Python, python, python", etc.
Backreferences:
This matches a previously matched group again:
Example
Description
([Pp])ython&1ails
Match python&rails or Python&Rails
(['"])[^1]*1
Single or double-quoted string. 1 matches whatever the 1st group matched .
2 matches whatever the 2nd group matched, etc.
Alternatives:
Example
Description
python|perl
Match "python" or "perl"
rub(y|le))
Match "ruby" or "ruble"
Python(!+|?)
"Python" followed by one or more ! or one ?
Anchors:
This need to specify match position
Example
Description
^Python
Match "Python" at the start of a string or internal line
Python$
Match "Python" at the end of a string or line
APython
Match "Python" at the start of a string
PythonZ
Match "Python" at the end of a string
bPythonb
Match "Python" at a word boundary
brubB
B is nonword boundary: match "rub" in "rube" and "ruby" but not alone
Python(?=!)
Match "Python", if followed by an exclamation point
Python(?!!)
Match "Python", if not followed by an exclamation point
Special syntax with parentheses:
Example
Description
R(?#comment)
Matches "R". All the rest is a comment
R(?i)uby
Case-insensitive while matching "uby"
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The pdb Module
The pdb module is the standard Python debugger. It is based on the bdb debugger framework.
You can run the debugger from the command line (type n [or next] to go to the next line and help to get
a list of available commands):
Example:
Before you try to run pdb.py, set your path properly to Python lib directory. So let us try with above
example sum.py:
$pdb.py sum.py
> /test/sum.py(3)<module>()
-> import dis
(Pdb) n
> /test/sum.py(5)<module>()
-> def sum():
(Pdb) n
>/test/sum.py(14)<module>()
-> dis.dis(sum)
(Pdb) n
6
0 LOAD_CONST
3 STORE_FAST
7
9
10
6 LOAD_CONST
9 STORE_FAST
1 (10)
0 (vara)
2 (20)
1 (varb)
12
15
18
19
LOAD_FAST
LOAD_FAST
BINARY_ADD
STORE_FAST
0 (vara)
1 (varb)
22
25
28
29
30
31
34
LOAD_CONST
LOAD_FAST
BINARY_MODULO
PRINT_ITEM
PRINT_NEWLINE
LOAD_CONST
RETURN_VALUE
3 ('vara + varb = %d')
2 (sum)
2 (sum)
0 (None)
--Return-> /test/sum.py(14)<module>()->None
-v dis.dis(sum)
(Pdb) n
--Return-> <string>(1)<module>()->None
(Pdb)
The profile Module:
The profile module is the standard Python profiler. You can run the profiler from the command line:
Example:
Let us try to profile following program:
#!/usr/bin/python
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Uploaded byVijay Chaitanya
Python tutorial
(1) Python uses indentation rather than braces to indicate blocks of code for functions and control flow. All statements within a block must be indented the same amount. (2) Python identifiers can consist of letters, numbers, and underscores but must start with a letter or underscore. Identifiers are case-sensitive. (3) There are reserved words in Python that cannot be used as identifiers such as def, if, else, and, or, not, etc.
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Python tutorial
- 1. Python Tutorial http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright ©tutorialspoint.com Python Tutorial Python is a general purpose interpreted, interactive, object-oriented and high-level programming language. Python was created by Guido van Rossum in the late eighties and early nineties. Like Perl, Python source code is now available under the GNU General Public License (GPL). This tutorial gives a complete understanding on Python. Send your feedback using Contact Us Form DIPANKAR DUTTA IIT ROORKEE Quick Links for Python Programmers (1) Python Quick Reference Guide A quick Python reference guide for Python Programmers. Python Quick Reference Guide (2) Useful Python Resources A collection of Python Sites, Books and Articles is given at this page. Useful Python Resources (3) Python Tools and Utilities Here you will find a useful Python's tools and utilities which you will require very frequently while doing Python programming. Python Tools and Utilities Copyright © tutorialspoint.com 1 of 1 3/22/2011 5:19 PM
- 2. Python Overview 1 of2 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python Overview Python is a high-level, interpreted, interactive and object oriented-scripting language. Python was designed to be highly readable which uses English keywords frequently where as other languages use punctuation and it has fewer syntactical constructions than other languages. Python is Interpreted: This means that it is processed at runtime by the interpreter and you do not need to compile your program before executing it. This is similar to PERL and PHP. Python is Interactive: This means that you can actually sit at a Python prompt and interact with the interpreter directly to write your programs. Python is Object-Oriented: This means that Python supports Object-Oriented style or technique of programming that encapsulates code within objects. Python is Beginner's Language: Python is a great language for the beginner programmers and supports the development of a wide range of applications, from simple text processing to WWW browsers to games. History of Python: Python was developed by Guido van Rossum in the late eighties and early nineties at the National Research Institute for Mathematics and Computer Science in the Netherlands. Python is derived from many other languages, including ABC, Modula-3, C, C++, Algol-68, SmallTalk, and Unix shell and other scripting languages. Python is copyrighted, Like Perl, Python source code is now available under the GNU General Public License (GPL). Python is now maintained by a core development team at the institute, although Guido van Rossum still holds a vital role in directing it's progress. Python Features: Python's feature highlights include: Easy-to-learn: Python has relatively few keywords, simple structure, and a clearly defined syntax. This allows the student to pick up the language in a relatively short period of time. Easy-to-read: Python code is much more clearly defined and visible to the eyes. Easy-to-maintain: Python's success is that its source code is fairly easy-to-maintain. A broad standard library: One of Python's greatest strengths is the bulk of the library is very portable and cross-platform compatible on UNIX, Windows, and Macintosh. Interactive Mode: Support for an interactive mode in which you can enter results from a terminal right to the language, allowing interactive testing and debugging of snippets of code. Portable: Python can run on a wide variety of hardware platforms and has the same interface on all platforms. Extendable: You can add low-level modules to the Python interpreter. These modules enable programmers to add to or customize their tools to be more efficient. 3/22/2011 5:20 PM
- 3. Python Overview 2 of2 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Databases: Python provides interfaces to all major commercial databases. GUI Programming: Python supports GUI applications that can be created and ported to many system calls, libraries, and windows systems, such as Windows MFC, Macintosh, and the X Window system of Unix. Scalable: Python provides a better structure and support for large programs than shell scripting. Apart from the above mentioned features, Python has a big list of good features, few are listed below: Support for functional and structured programming methods as well as OOP. It can be used as a scripting language or can be compiled to byte-code for building large applications. Very high-level dynamic data types and supports dynamic type checking. Supports automatic garbage collection. It can be easily integrated with C, C++, COM, ActiveX, CORBA, and Java. Copyright © tutorialspoint.com 3/22/2011 5:20 PM
- 4. Python Environment 1 of4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python Environment Before we start writing our Python programs, let's understand how to setup our Python environment. Python is available on a wide variety of platforms: Unix (Solaris, Linux, FreeBSD, AIX, HP/UX, SunOS, IRIX etc.) Win 9x/NT/2000 Macintosh (PPC, 68K) OS/2 DOS (multiple versions) PalmOS Nokia mobile phones Windows CE Acorn/RISC OS BeOS Amiga VMS/OpenVMS QNX VxWorks Psion Python has also been ported to the Java and .NET virtual machines. Getting Python: The most up-to-date and current source code, binaries, documentation, news, etc. is available at the official website of Python: Python Official Website : http://www.python.org/ You can download the Python documentation from the following site. The documentation is available in HTML, PDF, and PostScript formats. Python Documentation Website : www.python.org/doc/ Install Python: Python distribution is available for a wide variety of platforms. You need to download only the binary code applicable for your platform and install Python. If the binary code for your platform is not available, you need a C compiler to compile the source code manually. Compiling the source code offers more flexibility in terms of choice of features that you require in your installation. Here is a quick overview of installing Python on various platforms: Unix & Linux Installation: Here are the simple steps to install Python on Unix/Linux machine. Open a Web browser and go to http://www.python.org/download/ Follow the link to download zipped source code available for Unix/Linux. Download and extract files. 3/22/2011 5:20 PM
- 5. Python Environment 2 of4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Editing the Modules/Setup file if you want to customize some options. run ./configure script make make install This will install python in a standard location /usr/local/bin and its libraries are installed in /usr/local /lib/pythonXX where XX is the version of Python that you are using. Windows Installation: Here are the steps to install Python on Windows machine. Open a Web browser and go to http://www.python.org/download/ Follow the link for the Windows installer python-XYZ.msi file where XYZ is the version you are going to install. To use this installers python-XYZ.msi, the Windows system must support Microsoft Installer 2.0. Just save the installer file to your local machine and then run it to find out if your machine supports MSI. Run the downloaded file by double-clicking it in Windows Explorer. This brings up the Python install wizard, which is really easy to use. Just accept the default settings, wait until the install is finished, and you.re ready to roll! Macintosh Installation: MacPython is a Python version available for the Macintosh. Jack Jansen maintains it, and you can have full access to the entire documentation at his Web site. Jack Jansen Website : http://www.cwi.nl/~jack/macpython.html Just go to this link and you will find complete installation detail for Mac OS installation. Setting up PATH: Programs and other executable files can live in many directories, so operating systems provide a search path that lists the directories that the OS searches for executables. The path is stored in an environment variable, which is a named string maintained by the operating system. These variables contain information available to the command shell and other programs. The path variable is named PATH in Unix or Path in Windows (Unix is case-sensitive; Windows is not). In Mac OS, the installer handles the path details. To invoke the Python interpreter from any particular directory, you must add the Python directory to your path. Setting path at Unix/Linux: To add the Python directory to the path for a particular session in Unix: In the csh shell: type setenv PATH "$PATH:/usr/local/bin/python" and press Enter. In the bash shell (Linux): type export PATH="$PATH:/usr/local/bin/python" and press Enter. In the sh or ksh shell: type PATH="$PATH:/usr/local/bin/python" and press Enter. Note: /usr/local/bin/python is the path of the Python directory 3/22/2011 5:20 PM
- 6. Python Environment 3 of4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Setting path at Windows: To add the Python directory to the path for a particular session in Windows: At a command prompt : type path %path%;C:Python and press Enter. Note: C:Python is the path of the Python directory Python Environment Variables: Here are important environment variables which can be recognized by Python: Variable PYTHONPATH Description Has a role similar to PATH. This variable tells the Python interpreter where to locate the module files you import into a program. PYTHONPATH should include the Python source library directory and the directories containing your Python source code. PYTHONPATH is sometimes preset by the Python installer. Contains the path of an initialization file containing Python source code that is executed every time you start the interpreter (similar to the Unix .profile or .login PYTHONSTARTUP file). This file, often named .pythonrc.py in Unix, usually contains commands that load utilities or modify PYTHONPATH. PYTHONCASEOK Used in Windows to instruct Python to find the first case-insensitive match in an import statement. Set this variable to any value to activate it. PYTHONHOME An alternative module search path. It's usually embedded in the PYTHONSTARTUP or PYTHONPATH directories to make switching module libraries easy. Running Python: There are three different ways to start Python: (1) Interactive Interpreter: You can enter python and start coding right away in the interactive interpreter by starting it from the command line. You can do this from Unix, DOS, or any other system which provides you a command-line interpreter or shell window. $python # Unix/Linux or python% # Unix/Linux or C:>python # Windows/DOS Here is the list of all the available command line options: Option Description -d provide debug output -O generate optimized bytecode (resulting in .pyo files) -S do not run import site to look for Python paths on startup 3/22/2011 5:20 PM
- 7. Python Environment 4 of4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... -v verbose output (detailed trace on import statements) -X disable class-based built-in exceptions (just use strings); obsolete starting with version 1.6 -c cmd run Python script sent in as cmd string file run Python script from given file (2) Script from the Command-line: A Python script can be executed at command line by invoking the interpreter on your application, as in the following: $python script.py # Unix/Linux or python% script.py # Unix/Linux or C:>python script.py # Windows/DOS Note: Be sure the file permission mode allows execution. (3) Integrated Development Environment You can run Python from a graphical user interface (GUI) environment as well. All you need is a GUI application on your system that supports Python. Unix: IDLE is the very first Unix IDE for Python. Windows: PythonWin is the first Windows interface for Python and is an IDE with a GUI. Macintosh: The Macintosh version of Python is called MacPython and also available from the main website, downloadable as either MacBinary or BinHex'd files. MacPython includes an IDE. Before proceeding to next chapter, make sure your environment is properly setup and working perfectly fine. If you are not able to setup the environment properly then you can take help from your system admin. Note: Further chapters will explain all the examples using Linux OS. Copyright © tutorialspoint.com 3/22/2011 5:20 PM
- 8. Python - BasicSyntax 1 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Basic Syntax The Python language has many similarities to Perl, C, and Java. However, there are some definite differences between the languages. This chapter is designed to quickly get you up to speed on the syntax that is expected in Python. First Python Program: Interactive Mode Programming: Invoking the interpreter without passing a script file as a parameter brings up the following prompt: $ python Python 2.5 (r25:51908, Nov 6 2007, 16:54:01) [GCC 4.1.2 20070925 (Red Hat 4.1.2-27)] on linux2 Type "help", "copyright", "credits" or "license" for more info. >>> Type the following text to the right of the Python prompt and press the Enter key: >>> print "Hello, Python!"; NOTE: If you are running new version of Python then you would need to use print statement with parenthisis like print ("Hello, Python!"); This will produce following result: Hello, Python! Script Mode Programming : Invoking the interpreter with a script parameter begins execution of the script and continues until the script is finished. When the script is finished, the interpreter is no longer active. Let us write a simple Python program in a script. All python files will have extension .py. So put the following source code in a test.py file. #!/usr/bin/python print "Hello, Python!"; Here I assumed that you have Python interpreter available in /usr/bin directory. Now try to run this program as follows: $ chmod +x test.py $ python test.py # This is to make file executable 3/22/2011 5:21 PM
- 9. Python - BasicSyntax 2 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... This will produce following result: Hello, Python! You have seen a simple Python program in interactive as well as script mode, now lets see few basic concepts related to Python Syntax: Python Identifiers: A Python identifier is a name used to identify a variable, function, class, module, or other object. An identifier starts with a letter A to Z or a to z or an underscore (_) followed by zero or more letters, underscores, and digits (0 to 9). Python does not allow punctuation characters such as @, $, and % within identifiers. Python is a case sensitive programming language. Thus Manpower and manpower are two different identifiers in Python. Here are following identifier naming convention for Python: Class names start with an uppercase letter and all other identifiers with a lowercase letter. Starting an identifier with a single leading underscore indicates by convention that the identifier is meant to be private. Starting an identifier with two leading underscores indicates a strongly private identifier. If the identifier also ends with two trailing underscores, the identifier is a language-defined special name. Reserved Words: The following list shows the reserved words in Python. These reserved words may not be used as constant or variable or any other identifier names. Keywords contain lowercase letters only. and exec not assert finally or break for pass class from print continue global raise def if return del import try elif in while else is with except lambda yield Lines and Indentation: One of the first caveats programmers encounter when learning Python is the fact that there are no braces to indicate blocks of code for class and function definitions or flow control. Blocks of code are denoted by line indentation, which is rigidly enforced. The number of spaces in the indentation is variable, but all statements within the block must be indented 3/22/2011 5:21 PM
- 10. Python - BasicSyntax 3 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... the same amount. Both blocks in this example are fine: if True: print "True" else: print "False" However, the second block in this example will generate an error: if True: print "Answer" print "True" else: print "Answer" print "False" Thus, in Python all the continous lines indented with similar number of spaces would form a block. Following is the example having various statement blocks: Note: Don't try to understand logic or different functions used. Just make sure you undertood various blocks even if they are without braces. #!/usr/bin/python import sys try: # open file stream file = open(file_name, "w") except IOError: print "There was an error writing to", file_name sys.exit() print "Enter '", file_finish, print "' When finished" while file_text != file_finish: file_text = raw_input("Enter text: ") if file_text == file_finish: # close the file file.close break file.write(file_text) file.write("n") file.close() file_name = raw_input("Enter filename: ") if len(file_name) == 0: print "Next time please enter something" sys.exit() try: file = open(file_name, "r") except IOError: print "There was an error reading file" sys.exit() file_text = file.read() file.close() print file_text Multi-Line Statements: 3/22/2011 5:21 PM
- 11. Python - BasicSyntax 4 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Statements in Python typically end with a new line. Python does, however, allow the use of the line continuation character () to denote that the line should continue. For example: total = item_one + item_two + item_three Statements contained within the [], {}, or () brackets do not need to use the line continuation character. For example: days = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday'] Quotation in Python: Python accepts single ('), double (") and triple (''' or """) quotes to denote string literals, as long as the same type of quote starts and ends the string. The triple quotes can be used to span the string across multiple lines. For example, all the following are legal: word = 'word' sentence = "This is a sentence." paragraph = """This is a paragraph. It is made up of multiple lines and sentences.""" Comments in Python: A hash sign (#) that is not inside a string literal begins a comment. All characters after the # and up to the physical line end are part of the comment, and the Python interpreter ignores them. #!/usr/bin/python # First comment print "Hello, Python!"; # second comment This will produce following result: Hello, Python! A comment may be on the same line after a statement or expression: name = "Madisetti" # This is again comment You can comment multiple lines as follows: # # # # This is a comment. This is a comment, too. This is a comment, too. I said that already. 3/22/2011 5:21 PM
- 12. Python - BasicSyntax 5 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Using Blank Lines: A line containing only whitespace, possibly with a comment, is known as a blank line, and Python totally ignores it. In an interactive interpreter session, you must enter an empty physical line to terminate a multiline statement. Waiting for the User: The following line of the program displays the prompt, Press the enter key to exit. and waits for the user to press the Enter key: #!/usr/bin/python raw_input("nnPress the enter key to exit.") Here "nn" are being used to create two new lines before displaying the actual line. Once the user presses the key, the program ends. This is a nice trick to keep a console window open until the user is done with an application. Multiple Statements on a Single Line: The semicolon ( ; ) allows multiple statements on the single line given that neither statement starts a new code block. Here is a sample snip using the semicolon: import sys; x = 'foo'; sys.stdout.write(x + 'n') Multiple Statement Groups as Suites: Groups of individual statements making up a single code block are called suites in Python. Compound or complex statements, such as if, while, def, and class, are those which require a header line and a suite. Header lines begin the statement (with the keyword) and terminate with a colon ( : ) and are followed by one or more lines which make up the suite. Example: if expression : suite elif expression : suite else : suite Command Line Arguments: You may have seen, for instance, that many programs can be run so that they provide you with some basic information about how they should be run. Python enables you to do this with -h: $ python .h usage: python [option]...[-c cmd | -m mod | file | -] [arg].. 3/22/2011 5:21 PM
- 13. Python - BasicSyntax 6 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Options and arguments (and corresponding environment variables): -c cmd : program passed in as string (terminates option list) -d : debug output from parser (also PYTHONDEBUG=x) -E : ignore environment variables (such as PYTHONPATH) -h : print this help message and exit (also --help) [ etc. ] You can also program your script in such a way that it should accept various options. Command Line Arguments is an advanced topic and should be studied a bit later once you have gone through rest of the Python concepts. Copyright © tutorialspoint.com 3/22/2011 5:21 PM
- 14. Python - BasicSyntax 1 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Basic Syntax The Python language has many similarities to Perl, C, and Java. However, there are some definite differences between the languages. This chapter is designed to quickly get you up to speed on the syntax that is expected in Python. First Python Program: Interactive Mode Programming: Invoking the interpreter without passing a script file as a parameter brings up the following prompt: $ python Python 2.5 (r25:51908, Nov 6 2007, 16:54:01) [GCC 4.1.2 20070925 (Red Hat 4.1.2-27)] on linux2 Type "help", "copyright", "credits" or "license" for more info. >>> Type the following text to the right of the Python prompt and press the Enter key: >>> print "Hello, Python!"; NOTE: If you are running new version of Python then you would need to use print statement with parenthisis like print ("Hello, Python!"); This will produce following result: Hello, Python! Script Mode Programming : Invoking the interpreter with a script parameter begins execution of the script and continues until the script is finished. When the script is finished, the interpreter is no longer active. Let us write a simple Python program in a script. All python files will have extension .py. So put the following source code in a test.py file. #!/usr/bin/python print "Hello, Python!"; Here I assumed that you have Python interpreter available in /usr/bin directory. Now try to run this program as follows: $ chmod +x test.py $ python test.py # This is to make file executable 3/22/2011 5:21 PM
- 15. Python - BasicSyntax 2 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... This will produce following result: Hello, Python! You have seen a simple Python program in interactive as well as script mode, now lets see few basic concepts related to Python Syntax: Python Identifiers: A Python identifier is a name used to identify a variable, function, class, module, or other object. An identifier starts with a letter A to Z or a to z or an underscore (_) followed by zero or more letters, underscores, and digits (0 to 9). Python does not allow punctuation characters such as @, $, and % within identifiers. Python is a case sensitive programming language. Thus Manpower and manpower are two different identifiers in Python. Here are following identifier naming convention for Python: Class names start with an uppercase letter and all other identifiers with a lowercase letter. Starting an identifier with a single leading underscore indicates by convention that the identifier is meant to be private. Starting an identifier with two leading underscores indicates a strongly private identifier. If the identifier also ends with two trailing underscores, the identifier is a language-defined special name. Reserved Words: The following list shows the reserved words in Python. These reserved words may not be used as constant or variable or any other identifier names. Keywords contain lowercase letters only. and exec not assert finally or break for pass class from print continue global raise def if return del import try elif in while else is with except lambda yield Lines and Indentation: One of the first caveats programmers encounter when learning Python is the fact that there are no braces to indicate blocks of code for class and function definitions or flow control. Blocks of code are denoted by line indentation, which is rigidly enforced. The number of spaces in the indentation is variable, but all statements within the block must be indented 3/22/2011 5:21 PM
- 16. Python - BasicSyntax 3 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... the same amount. Both blocks in this example are fine: if True: print "True" else: print "False" However, the second block in this example will generate an error: if True: print "Answer" print "True" else: print "Answer" print "False" Thus, in Python all the continous lines indented with similar number of spaces would form a block. Following is the example having various statement blocks: Note: Don't try to understand logic or different functions used. Just make sure you undertood various blocks even if they are without braces. #!/usr/bin/python import sys try: # open file stream file = open(file_name, "w") except IOError: print "There was an error writing to", file_name sys.exit() print "Enter '", file_finish, print "' When finished" while file_text != file_finish: file_text = raw_input("Enter text: ") if file_text == file_finish: # close the file file.close break file.write(file_text) file.write("n") file.close() file_name = raw_input("Enter filename: ") if len(file_name) == 0: print "Next time please enter something" sys.exit() try: file = open(file_name, "r") except IOError: print "There was an error reading file" sys.exit() file_text = file.read() file.close() print file_text Multi-Line Statements: 3/22/2011 5:21 PM
- 17. Python - BasicSyntax 4 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Statements in Python typically end with a new line. Python does, however, allow the use of the line continuation character () to denote that the line should continue. For example: total = item_one + item_two + item_three Statements contained within the [], {}, or () brackets do not need to use the line continuation character. For example: days = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday'] Quotation in Python: Python accepts single ('), double (") and triple (''' or """) quotes to denote string literals, as long as the same type of quote starts and ends the string. The triple quotes can be used to span the string across multiple lines. For example, all the following are legal: word = 'word' sentence = "This is a sentence." paragraph = """This is a paragraph. It is made up of multiple lines and sentences.""" Comments in Python: A hash sign (#) that is not inside a string literal begins a comment. All characters after the # and up to the physical line end are part of the comment, and the Python interpreter ignores them. #!/usr/bin/python # First comment print "Hello, Python!"; # second comment This will produce following result: Hello, Python! A comment may be on the same line after a statement or expression: name = "Madisetti" # This is again comment You can comment multiple lines as follows: # # # # This is a comment. This is a comment, too. This is a comment, too. I said that already. 3/22/2011 5:21 PM
- 18. Python - BasicSyntax 5 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Using Blank Lines: A line containing only whitespace, possibly with a comment, is known as a blank line, and Python totally ignores it. In an interactive interpreter session, you must enter an empty physical line to terminate a multiline statement. Waiting for the User: The following line of the program displays the prompt, Press the enter key to exit. and waits for the user to press the Enter key: #!/usr/bin/python raw_input("nnPress the enter key to exit.") Here "nn" are being used to create two new lines before displaying the actual line. Once the user presses the key, the program ends. This is a nice trick to keep a console window open until the user is done with an application. Multiple Statements on a Single Line: The semicolon ( ; ) allows multiple statements on the single line given that neither statement starts a new code block. Here is a sample snip using the semicolon: import sys; x = 'foo'; sys.stdout.write(x + 'n') Multiple Statement Groups as Suites: Groups of individual statements making up a single code block are called suites in Python. Compound or complex statements, such as if, while, def, and class, are those which require a header line and a suite. Header lines begin the statement (with the keyword) and terminate with a colon ( : ) and are followed by one or more lines which make up the suite. Example: if expression : suite elif expression : suite else : suite Command Line Arguments: You may have seen, for instance, that many programs can be run so that they provide you with some basic information about how they should be run. Python enables you to do this with -h: $ python .h usage: python [option]...[-c cmd | -m mod | file | -] [arg].. 3/22/2011 5:21 PM
- 19. Python - BasicSyntax 6 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Options and arguments (and corresponding environment variables): -c cmd : program passed in as string (terminates option list) -d : debug output from parser (also PYTHONDEBUG=x) -E : ignore environment variables (such as PYTHONPATH) -h : print this help message and exit (also --help) [ etc. ] You can also program your script in such a way that it should accept various options. Command Line Arguments is an advanced topic and should be studied a bit later once you have gone through rest of the Python concepts. Copyright © tutorialspoint.com 3/22/2011 5:21 PM
- 20. Python - VariableTypes 1 of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Variable Types Variables are nothing but reserved memory locations to store values. This means that when you create a variable you reserve some space in memory. Based on the data type of a variable, the interpreter allocates memory and decides what can be stored in the reserved memory. Therefore, by assigning different data types to variables, you can store integers, decimals, or characters in these variables. Assigning Values to Variables: Python variables do not have to be explicitly declared to reserve memory space. The declaration happens automatically when you assign a value to a variable. The equal sign (=) is used to assign values to variables. The operand to the left of the = operator is the name of the variable, and the operand to the right of the = operator is the value stored in the variable. For example: #!/usr/bin/python counter = 100 miles = 1000.0 name = "John" # An integer assignment # A floating point # A string print counter print miles print name Here 100, 1000.0 and "John" are the values assigned to counter, miles and name variables, respectively. While running this program, this will produce following result: 100 1000.0 John Multiple Assignment: You can also assign a single value to several variables simultaneously. For example: a = b = c = 1 Here, an integer object is created with the value 1, and all three variables are assigned to the same memory location. You can also assign multiple objects to multiple variables. For example: a, b, c = 1, 2, "john" Here two integer objects with values 1 and 2 are assigned to variables a and b, and one string object with the value "john" is assigned to the variable c. 3/22/2011 5:21 PM
- 21. Python - VariableTypes 2 of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Standard Data Types: The data stored in memory can be of many types. For example, a person.s age is stored as a numeric value and his or her address is stored as alphanumeric characters. Python has some standard types that are used to define the operations possible on them and the storage method for each of them. Python has five standard data types: Numbers String List Tuple Dictionary Python Numbers: Number data types store numeric values. They are immutable data types, which means that changing the value of a number data type results in a newly allocated object. Number objects are created when you assign a value to them. For example: var1 = 1 var2 = 10 You can also delete the reference to a number object by using the del statement. The syntax of the del statement is: del var1[,var2[,var3[....,varN]]]] You can delete a single object or multiple objects by using the del statement. For example: del var del var_a, var_b Python supports four different numerical types: int (signed integers) long (long integers [can also be represented in octal and hexadecimal]) float (floating point real values) complex (complex numbers) Examples: Here are some examples of numbers: int long float complex 10 51924361L 0.0 3.14j 100 -0x19323L 15.20 45.j 3/22/2011 5:21 PM
- 22. Python - VariableTypes 3 of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... -786 0122L -21.9 9.322e-36j 080 0xDEFABCECBDAECBFBAEl 32.3+e18 .876j -0490 535633629843L -90. -.6545+0J -0x260 -052318172735L -32.54e100 3e+26J 0x69 -4721885298529L 70.2-E12 4.53e-7j Python allows you to use a lowercase L with long, but it is recommended that you use only an uppercase L to avoid confusion with the number 1. Python displays long integers with an uppercase L. A complex number consists of an ordered pair of real floatingpoint numbers denoted by a + bj, where a is the real part and b is the imaginary part of the complex number. Python Strings: Strings in Python are identified as a contiguous set of characters in between quotation marks. Python allows for either pairs of single or double quotes. Subsets of strings can be taken using the slice operator ( [ ] and [ : ] ) with indexes starting at 0 in the beginning of the string and working their way from -1 at the end. The plus ( + ) sign is the string concatenation operator, and the asterisk ( * ) is the repetition operator. Example: #!/usr/bin/python str = 'Hello World!' print print print print print print str str[0] str[2:5] str[2:] str * 2 str + "TEST" # # # # # # Prints Prints Prints Prints Prints Prints complete string first character of the string characters starting from 3rd to 6th string starting from 3rd character string two times concatenated string This will produce following result: Hello World! H llo llo World! Hello World!Hello World! Hello World!TEST Python Lists: Lists are the most versatile of Python's compound data types. A list contains items separated by commas and enclosed within square brackets ([]). To some extent, lists are similar to arrays in C. One difference between them is that all the items belonging to a list can be of different data type. The values stored in a list can be accessed using the slice operator ( [ ] and [ : ] ) with indexes starting at 0 in the beginning of the list and working their way to end-1. 3/22/2011 5:21 PM
- 23. Python - VariableTypes 4 of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... The plus ( + ) sign is the list concatenation operator, and the asterisk ( * ) is the repetition operator. Example: #!/usr/bin/python list = [ 'abcd', 786 , 2.23, 'john', 70.2 ] tinylist = [123, 'john'] print print print print print print list # list[0] # list[1:3] # list[2:] # tinylist * 2 # list + tinylist Prints complete list Prints first element of the list Prints elements starting from 2nd to 4th Prints elements starting from 3rd element Prints list two times # Prints concatenated lists This will produce following result: ['abcd', 786, 2.23, 'john', 70.200000000000003] abcd [786, 2.23] [2.23, 'john', 70.200000000000003] [123, 'john', 123, 'john'] ['abcd', 786, 2.23, 'john', 70.200000000000003, 123, 'john'] Python Tuples: A tuple is another sequence data type that is similar to the list. A tuple consists of a number of values separated by commas. Unlike lists, however, tuples are enclosed within parentheses. The main differences between lists and tuples are: Lists are enclosed in brackets ( [ ] ), and their elements and size can be changed, while tuples are enclosed in parentheses ( ( ) ) and cannot be updated. Tuples can be thought of as read-only lists. Example: #!/usr/bin/python tuple = ( 'abcd', 786 , 2.23, 'john', 70.2 tinytuple = (123, 'john') print print print print print print tuple # tuple[0] # tuple[1:3] # tuple[2:] # tinytuple * 2 # tuple + tinytuple ) Prints complete list Prints first element of the list Prints elements starting from 2nd to 4th Prints elements starting from 3rd element Prints list two times # Prints concatenated lists This will produce following result: ('abcd', 786, 2.23, 'john', 70.200000000000003) abcd (786, 2.23) (2.23, 'john', 70.200000000000003) (123, 'john', 123, 'john') ('abcd', 786, 2.23, 'john', 70.200000000000003, 123, 'john') 3/22/2011 5:21 PM
- 24. Python - VariableTypes 5 of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Following is invalid with tuple, because we attempted to update a tuple,which is not allowed. Similar case is possible with lists: #!/usr/bin/python tuple = ( 'abcd', 786 , 2.23, 'john', 70.2 ) list = [ 'abcd', 786 , 2.23, 'john', 70.2 ] tuple[2] = 1000 # Invalid syntax with tuple list[2] = 1000 # Valid syntax with list Python Dictionary: Python 's dictionaries are hash table type. They work like associative arrays or hashes found in Perl and consist of key-value pairs. Keys can be almost any Python type, but are usually numbers or strings. Values, on the other hand, can be any arbitrary Python object. Dictionaries are enclosed by curly braces ( { } ) and values can be assigned and accessed using square braces ( [] ). Example: #!/usr/bin/python dict = {} dict['one'] = "This is one" dict[2] = "This is two" tinydict = {'name': 'john','code':6734, 'dept': 'sales'} print print print print print dict['one'] dict[2] tinydict tinydict.keys() tinydict.values() # # # # # Prints Prints Prints Prints Prints value for 'one' key value for 2 key complete dictionary all the keys all the values This will produce following result: This is one This is two {'dept': 'sales', 'code': 6734, 'name': 'john'} ['dept', 'code', 'name'] ['sales', 6734, 'john'] Dictionaries have no concept of order among elements. It is incorrect to say that the elements are "out of order"; they are simply unordered. Data Type Conversion: Sometimes you may beed to perform conversions between the built-in types. To convert between types you simply use the type name as a function. There are several built-in functions to perform conversion from one data type to another. These functions return a new object representing the converted value. 3/22/2011 5:21 PM
- 25. Python - VariableTypes 6 of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Function Description int(x [,base]) Converts x to an integer. base specifies the base if x is a string. long(x [,base] ) Converts x to a long integer. base specifies the base if x is a string. float(x) Converts x to a floating-point number. complex(real [,imag]) Creates a complex number. str(x) Converts object x to a string representation. repr(x) Converts object x to an expression string. eval(str) Evaluates a string and returns an object. tuple(s) Converts s to a tuple. list(s) Converts s to a list. set(s) Converts s to a set. dict(d) Creates a dictionary. d must be a sequence of (key,value) tuples. frozenset(s) Converts s to a frozen set. chr(x) Converts an integer to a character. unichr(x) Converts an integer to a Unicode character. ord(x) Converts a single character to its integer value. hex(x) Converts an integer to a hexadecimal string. oct(x) Converts an integer to an octal string. 3/22/2011 5:21 PM
- 26. Python - VariableTypes 7 of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com 3/22/2011 5:21 PM
- 27. Python - BasicOperators 1 of 5 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Basic Operators What is an operator? Simple answer can be given using expression 4 + 5 is equal to 9. Here 4 and 5 are called operands and + is called operator. Python language supports following type of operators. Arithmetic Operators Comparision Operators Logical (or Relational) Operators Assignment Operators Conditional (or ternary) Operators Lets have a look on all operators one by one. Python Arithmetic Operators: Assume variable a holds 10 and variable b holds 20 then: Operator Description Example + Addition - Adds values on either side of the operator a + b will give 30 - Subtraction - Subtracts right hand operand from left hand operand a - b will give -10 * Multiplication - Multiplies values on either side of the operator a * b will give 200 / Division - Divides left hand operand by right hand operand b / a will give 2 % Modulus - Divides left hand operand by right hand operand and returns remainder b % a will give 0 ** Exponent - Performs exponential (power) calculation on operators a**b will give 10 to the power 20 // Floor Division - The division of operands where the result is the quotient in which the digits after the decimal point are removed. 9//2 is equal to 4 and 9.0//2.0 is equal to 4.0 Python Comparison Operators: Assume variable a holds 10 and variable b holds 20 then: Operator == Description Checks if the value of two operands are equal or not, if yes then condition becomes true. Example (a == b) is not true. 3/22/2011 5:21 PM
- 28. Python - BasicOperators 2 of 5 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... != Checks if the value of two operands are equal or not, if values are not equal then condition becomes true. (a != b) is true. <> Checks if the value of two operands are equal or not, if values are not equal then condition becomes true. (a <> b) is true. This is similar to != operator. > Checks if the value of left operand is greater than the value of right operand, if yes then condition becomes true. (a > b) is not true. < Checks if the value of left operand is less than the value of right operand, if yes then condition becomes true. (a < b) is true. >= Checks if the value of left operand is greater than or equal to the value of right operand, if yes then condition becomes true. (a >= b) is not true. <= Checks if the value of left operand is less than or equal to the value of right operand, if yes then condition becomes true. (a <= b) is true. Python Assignment Operators: Assume variable a holds 10 and variable b holds 20 then: Operator Description Example = Simple assignment operator, Assigns values from right side operands to left side operand c = a + b will assigne value of a + b into c += Add AND assignment operator, It adds right operand to the left operand and assign the result to left operand c += a is equivalent to c = c + a -= Subtract AND assignment operator, It subtracts right operand from the left operand and assign the result to left operand c -= a is equivalent to c = c - a *= Multiply AND assignment operator, It multiplies right operand with the left operand and assign the result to left operand c *= a is equivalent to c = c * a /= Divide AND assignment operator, It divides left operand with the right operand and assign the result to left operand c /= a is equivalent to c = c / a %= Modulus AND assignment operator, It takes modulus using two operands and assign the result to left operand c %= a is equivalent to c = c % a **= Exponent AND assignment operator, Performs exponential (power) calculation on operators and assign value to the left operand c **= a is equivalent to c = c ** a 3/22/2011 5:21 PM
- 29. Python - BasicOperators 3 of 5 //= http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Floor Dividion and assigns a value, Performs floor division on operators and assign value to the left operand c //= a is equivalent to c = c // a Python Bitwise Operators: Bitwise operator works on bits and perform bit by bit operation. Assume if a = 60; and b = 13; Now in binary format they will be as follows: a = 0011 1100 b = 0000 1101 ----------------a&b = 0000 1100 a|b = 0011 1101 a^b = 0011 0001 ~a = 1100 0011 There are following Bitwise operators supported by Python language Operator Description Example & Binary AND Operator copies a bit to the result (a & b) will give 12 which is 0000 1100 if it exists in both operands. | Binary OR Operator copies a bit if it exists in eather operand. (a | b) will give 61 which is 0011 1101 ^ Binary XOR Operator copies the bit if it is set in one operand but not both. (a ^ b) will give 49 which is 0011 0001 ~ Binary Ones Complement Operator is unary and has the efect of 'flipping' bits. (~a ) will give -60 which is 1100 0011 << Binary Left Shift Operator. The left operands value is moved left by the number of bits specified by the right operand. a << 2 will give 240 which is 1111 0000 >> Binary Right Shift Operator. The left operands value is moved right by the number of bits a >> 2 will give 15 which is 0000 1111 specified by the right operand. Python Logical Operators: There are following logical operators supported by Python language Assume variable a holds 10 and variable b holds 20 then: Operator Description Example and Called Logical AND operator. If both the operands are true then then condition becomes true. (a and b) is true. or Called Logical OR Operator. If any of the two operands are non zero then then condition becomes true. (a or b) is true. 3/22/2011 5:21 PM
- 30. Python - BasicOperators 4 of 5 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Called Logical NOT Operator. Use to reverses the logical state of its operand. If a condition is true then Logical NOT operator will make false. not not(a and b) is false. Python Membership Operators: In addition to the operators discussed previously, Python has membership operators, which test for membership in a sequence, such as strings, lists, or tuples. There are two membership operators explained below: Operator Description Example in Evaluates to true if it finds a variable in the specified sequence and false otherwise. x in y, here in results in a 1 if x is a member of sequence y. not in Evaluates to true if it does not finds a variable in the specified sequence and false otherwise. x not in y, here not in results in a 1 if x is a member of sequence y. Python Identity Operators: Identity operators compare the memory locations of two objects. There are two Identity operators explained below: Operator Description Example is Evaluates to true if the variables on either side of the operator point to the same object and false otherwise. x is y, here is results in 1 if id(x) equals id(y). is not Evaluates to false if the variables on either side of the operator point to the same object and true otherwise. x is not y, here is not results in 1 if id(x) is not equal to id(y). Python Operators Precedence The following table lists all operators from highest precedence to lowest. Operator Description ** Exponentiation (raise to the power) ~+- Ccomplement, unary plus and minus (method names for the last two are +@ and -@) * / % // Multiply, divide, modulo and floor division +- Addition and subtraction >> << Right and left bitwise shift & Bitwise 'AND' ^| Bitwise exclusive `OR' and regular `OR' <= < > >= Comparison operators <> == != Equality operators 3/22/2011 5:21 PM
- 31. Python - BasicOperators 5 of 5 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... = %= /= //= -= += *= **= Assignment operators is is not Identity operators in not in Membership operators not or and Logical operators Copyright © tutorialspoint.com 3/22/2011 5:21 PM
- 32. Python - IF...ELIF...ELSEand Nested IF Statements 1 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - IF...ELIF...ELSE Statement Conditional constructs are used to incorporate decision making into programs. The result of this decision making determines the sequence in which a program will execute instructions. You can control the flow of a program by using conditional constructs. This tutorial will discuss the programming conditional constructs available in Python, such as if, if...else, elif, and nested if. The if statement: The if statement of Python is similar to that of other languages. The if statement contains a logical expression using which data is compared, and a decision is made based on the result of the comparison. The syntax of the if statement is: if expression: statement(s) Here if statement, condition is evaluated first. If condition is true that is, if its value is nonzero then the statement(s) block are executed. Otherwise, the next statement following the statement(s) block is executed. Note: In Python, all the statements indented by the same number of character spaces after a programming construct are considered to be part of a single block of code. Python uses indentation as its method of grouping statements. Example: #!/usr/bin/python var1 = 100 if var1: print "1 - Got a true expression value" print var1 var2 = 0 if var2: print "2 - Got a true expression value" print var2 print "Good bye!" This will produce following result: 1 - Got a true expression value 100 Good bye! The else Statement: 3/22/2011 5:22 PM
- 33. Python - IF...ELIF...ELSEand Nested IF Statements 2 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... An else statement can be combined with an if statement. An else statement contains the block of code that executes if the conditional expression in the if statement resolves to 0 or a false value. The else statement is an optional statement and there could be at most only one else statement following if . The syntax of the if...else statement is: if expression: statement(s) else: statement(s) Example: #!/usr/bin/python var1 = 100 if var1: print "1 - Got a true expression value" print var1 else: print "1 - Got a false expression value" print var1 var2 = 0 if var2: print print else: print print "2 - Got a true expression value" var2 "2 - Got a false expression value" var2 print "Good bye!" This will produce following result: 1 - Got a true expression value 100 2 - Got a false expression value 0 Good bye! The elif Statement The elif statement allows you to check multiple expressions for truth value and execute a block of code as soon as one of the conditions evaluates to true. Like the else, the elif statement is optional. However, unlike else, for which there can be at most one statement, there can be an arbitrary number of elif statements following an if. The syntax of the if...elif statement is: if expression1: statement(s) elif expression2: statement(s) 3/22/2011 5:22 PM
- 34. Python - IF...ELIF...ELSEand Nested IF Statements 3 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... elif expression3: statement(s) else: statement(s) Note: Python does not currently support switch or case statements as in other languages. Example: #!/usr/bin/python var = 100 if var == 200: print "1 - Got print var elif var == 150: print "2 - Got print var2 elif var == 100: print "3 - Got print var else: print "4 - Got print var a true expression value" a true expression value" a true expression value" a false expression value" print "Good bye!" This will produce following result: 3 - Got a true expression value 100 Good bye! The Nested if...elif...else Construct There may be a situation when you want to check for another condition after a condition resolves to true. In such a situation, you can use the nested if construct. In a nested if construct, you can have an if...elif...else construct inside another if...elif...else construct. The syntax of the nested if...elif...else construct may be: if expression1: statement(s) if expression2: statement(s) elif expression3: statement(s) else statement(s) elif expression4: statement(s) else: statement(s) Example: 3/22/2011 5:22 PM
- 35. Python - IF...ELIF...ELSEand Nested IF Statements 4 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... #!/usr/bin/python var = 100 if var < 200: print "Expression value is less than 200" if var == 150: print "Which is 150" elif var == 100: print "Which is 100" elif var == 50: print "Which is 50" elif var < 50: print "Expression value is less than 50" else: print "Could not find true expression" print "Good bye!" This will produce following result: Expression value is less than 200 Which is 100 Good bye! Single Statement Suites: If the suite of an if clause consists only of a single line, it may go on the same line as the header statement: Here is an example of a one-line if clause: if ( expression == 1 ) : print "Value of expression is 1" Copyright © tutorialspoint.com 3/22/2011 5:22 PM
- 36. Python - whileLoop Statements 1 of 2 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - while Loop Statements A loop is a construct that causes a section of a program to be repeated a certain number of times. The repetition continues while the condition set for the loop remains true. When the condition becomes false, the loop ends and the program control is passed to the statement following the loop. This tutorial will discuss the while loop construct available in Python. The while Loop: The while loop is one of the looping constructs available in Python. The while loop continues until the expression becomes false. The expression has to be a logical expression and must return either a true or a false value The syntax of the while loop is: while expression: statement(s) Here expression statement is evaluated first. If expression is true that is, then the statement(s) block is executed repeatedly until expression becomes false. Otherwise, the next statement following the statement(s) block is executed. Note: In Python, all the statements indented by the same number of character spaces after a programming construct are considered to be part of a single block of code. Python uses indentation as its method of grouping statements. Example: #!/usr/bin/python count = 0 while (count < 9): print 'The count is:', count count = count + 1 print "Good bye!" This will produce following result: The count The count The count The count The count The count The count The count The count Good bye! is: is: is: is: is: is: is: is: is: 0 1 2 3 4 5 6 7 8 3/22/2011 5:22 PM
- 37. Python - whileLoop Statements 2 of 2 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... The block here, consisting of the print and increment statements, is executed repeatedly until count is no longer less than 9. With each iteration, the current value of the index count is displayed and then increased by 1. The Infinite Loops: You must use caution when using while loops because of the possibility that this condition never resolves to a false value. This results in a loop that never ends. Such a loop is called an infinite loop. An infinite loop might be useful in client/server programming where the server needs to run continuously so that client programs can communicate with it as and when required. Example: Following loop will continue till you enter CTRL+C : #!/usr/bin/python var = 1 while var == 1 : # This constructs an infinite loop num = raw_input("Enter a number :") print "You entered: ", num print "Good bye!" This will produce following result: Enter a number :20 You entered: 20 Enter a number :29 You entered: 29 Enter a number :3 You entered: 3 Enter a number between :Traceback (most recent call last): File "test.py", line 5, in <module> num = raw_input("Enter a number :") KeyboardInterrupt Above example will go in an infite loop and you would need to use CTRL+C to come out of the program. Single Statement Suites: Similar to the if statement syntax, if your while clause consists only of a single statement, it may be placed on the same line as the while header. Here is the syntax of a one-line while clause: while expression : statement Copyright © tutorialspoint.com 3/22/2011 5:22 PM
- 38. Python - forLoop Statements 1 of 2 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - for Loop Statements A loop is a construct that causes a section of a program to be repeated a certain number of times. The repetition continues while the condition set for the loop remains true. When the condition becomes false, the loop ends and the program control is passed to the statement following the loop. This tutorial will discuss the for loop construct available in Python. The for Loop: The for loop in Python has the ability to iterate over the items of any sequence, such as a list or a string. The syntax of the loop look is: for iterating_var in sequence: statements(s) If a sequence contains an expression list, it is evaluated first. Then, the first item in the sequence is assigned to the iterating variable iterating_var. Next, the statements block is executed. Each item in the list is assigned to iterating_var, and the statements(s) block is executed until the entire sequence is exhausted. Note: In Python, all the statements indented by the same number of character spaces after a programming construct are considered to be part of a single block of code. Python uses indentation as its method of grouping statements. Example: #!/usr/bin/python for letter in 'Python': # First Example print 'Current Letter :', letter fruits = ['banana', 'apple', 'mango'] for fruit in fruits: # Second Example print 'Current fruit :', fruit print "Good bye!" This will produce following result: Current Current Current Current Current Current Current Current Current Letter : P Letter : y Letter : t Letter : h Letter : o Letter : n fruit : banana fruit : apple fruit : mango 3/22/2011 5:22 PM
- 39. Python - forLoop Statements 2 of 2 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Good bye! Iterating by Sequence Index: An alternative way of iterating through each item is by index offset into the sequence itself: Example: #!/usr/bin/python fruits = ['banana', 'apple', 'mango'] for index in range(len(fruits)): print 'Current fruit :', fruits[index] print "Good bye!" This will produce following result: Current fruit : banana Current fruit : apple Current fruit : mango Good bye! Here we took the assistance of the len() built-in function, which provides the total number of elements in the tuple as well as the range() built-in function to give us the actual sequence to iterate over. Copyright © tutorialspoint.com 3/22/2011 5:22 PM
- 40. Python Loop Control- break, continue and pass Statements 1 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python break,continue and pass Statements You might face a situation in which you need to exit a loop completely when an external condition is triggered or there may also be a situation when you want to skip a part of the loop and start next execution. Python provides break and continue statements to handle such situations and to have good control on your loop. This tutorial will discuss the break, continue and pass statements available in Python. The break Statement: The break statement in Python terminates the current loop and resumes execution at the next statement, just like the traditional break found in C. The most common use for break is when some external condition is triggered requiring a hasty exit from a loop. The break statement can be used in both while and for loops. Example: #!/usr/bin/python for letter in 'Python': # First Example if letter == 'h': break print 'Current Letter :', letter var = 10 # Second Example while var > 0: print 'Current variable value :', var var = var -1 if var == 5: break print "Good bye!" This will produce following result: Current Letter : Current Letter : Current Letter : Current variable Current variable Current variable Current variable Current variable Good bye! P y t value value value value value : : : : : 10 9 8 7 6 The continue Statement: 3/22/2011 5:22 PM
- 41. Python Loop Control- break, continue and pass Statements 2 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... The continue statement in Python returns the control to the beginning of the while loop. The continue statement rejects all the remaining statements in the current iteration of the loop and moves the control back to the top of the loop. The continue statement can be used in both while and for loops. Example: #!/usr/bin/python for letter in 'Python': # First Example if letter == 'h': continue print 'Current Letter :', letter var = 10 # Second Example while var > 0: print 'Current variable value :', var var = var -1 if var == 5: continue print "Good bye!" This will produce following result: Current Letter : Current Letter : Current Letter : Current Letter : Current Letter : Current variable Current variable Current variable Current variable Current variable Current variable Current variable Current variable Current variable Current variable Good bye! P y t o n value value value value value value value value value value : : : : : : : : : : 10 9 8 7 6 5 4 3 2 1 The else Statement Used with Loops Python supports to have an else statement associated with a loop statements. If the else statement is used with a for loop, the else statement is executed when the loop has exhausted iterating the list. If the else statement is used with a while loop, the else statement is executed when the condition becomes false. Example: The following example illustrates the combination of an else statement with a for statement that searches for prime numbers from 10 through 20. 3/22/2011 5:22 PM
- 42. Python Loop Control- break, continue and pass Statements 3 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... #!/usr/bin/python for num in range(10,20): #to iterate between 10 to 20 for i in range(2,num): #to iterate on the factors of the number if num%i == 0: #to determine the first factor j=num/i #to calculate the second factor print '%d equals %d * %d' % (num,i,j) break #to move to the next number, the #first FOR else: # else part of the loop print num, 'is a prime number' This will produce following result: 10 11 12 13 14 15 16 17 18 19 equals 2 * is a prime equals 2 * is a prime equals 2 * equals 3 * equals 2 * is a prime equals 2 * is a prime 5 number 6 number 7 5 8 number 9 number Similar way you can use else statement with while loop. The pass Statement: The pass statement in Python is used when a statement is required syntactically but you do not want any command or code to execute. The pass statement is a null operation; nothing happens when it executes. The pass is also useful in places where your code will eventually go, but has not been written yet (e.g., in stubs for example): Example: #!/usr/bin/python for letter in 'Python': if letter == 'h': pass print 'This is pass block' print 'Current Letter :', letter print "Good bye!" This will produce following result: Current Letter : P Current Letter : y Current Letter : t This is pass block Current Letter : h Current Letter : o Current Letter : n Good bye! 3/22/2011 5:22 PM
- 43. Python Loop Control- break, continue and pass Statements 4 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... The preceding code does not execute any statement or code if the value of letter is 'h'. The pass statement is helpful when you have created a code block but it is no longer required. You can then remove the statements inside the block but let the block remain with a pass statement so that it doesn't interfere with other parts of the code. Copyright © tutorialspoint.com 3/22/2011 5:22 PM
- 44. Python - Numberswith built-in functions 1 of 3 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Numbers Number data types store numeric values. They are immutable data types, which means that changing the value of a number data type results in a newly allocated object. Number objects are created when you assign a value to them. For example: var1 = 1 var2 = 10 You can also delete the reference to a number object by using the del statement. The syntax of the del statement is: del var1[,var2[,var3[....,varN]]]] You can delete a single object or multiple objects by using the del statement. For example: del var del var_a, var_b Python supports four different numerical types: int (signed integers): often called just integers or ints, are positive or negative whole numbers with no decimal point. long (long integers ): or longs, are integers of unlimited size, written like integers and followed by an uppercase or lowercase L. float (floating point real values) : or floats, represent real numbers and are written with a decimal point dividing the integer and fractional parts. Floats may also be in scientific notation, with E or e indicating the power of 10 (2.5e2 = 2.5 x 102 = 250). complex (complex numbers) : are of the form a + bJ, where a and b are floats and J (or j) represents the square root of -1 (which is an imaginary number). a is the real part of the number, and b is the imaginary part. Complex numbers are not used much in Python programming. Examples: Here are some examples of numbers: int long float complex 10 51924361L 0.0 3.14j 100 -0x19323L 15.20 45.j -786 0122L -21.9 9.322e-36j 080 0xDEFABCECBDAECBFBAEl 32.3+e18 .876j -0490 535633629843L -90. -.6545+0J 3/22/2011 5:22 PM
- 45. Python - Numberswith built-in functions 2 of 3 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... -0x260 -052318172735L -32.54e100 3e+26J 0x69 -4721885298529L 70.2-E12 4.53e-7j Python allows you to use a lowercase L with long, but it is recommended that you use only an uppercase L to avoid confusion with the number 1. Python displays long integers with an uppercase L. A complex number consists of an ordered pair of real floatingpoint numbers denoted by a + bj, where a is the real part and b is the imaginary part of the complex number. Number Type Conversion: Python converts numbers internally in an expression containing mixed types to a common type for evaluation. But sometimes, you'll need to coerce a number explicitly from one type to another to satisfy the requirements of an operator or function parameter. Type int(x)to convert x to a plain integer. Type long(x) to convert x to a long integer. Type float(x) to convert x to a floating-point number. Type complex(x) to convert x to a complex number with real part x and imaginary part zero. Type complex(x, y) to convert x and y to a complex number with real part x and imaginary part y. x and y are numeric expressions Built-in Number Functions: Mathematical Functions: Python includes following functions that perform mathematical calculations. Function Returns ( description ) abs(x) The absolute value of x: the (positive) distance between x and zero. ceil(x) The ceiling of x: the smallest integer not less than x cmp(x, y) -1 if x < y, 0 if x == y, or 1 if x > y exp(x) The exponential of x: ex fabs(x) The absolute value of x. floor(x) The floor of x: the largest integer not greater than x log(x) The natural logarithm of x, for x> 0 log10(x) The base-10 logarithm of x for x> 0 . max(x1, x2,...) The largest of its arguments: the value closest to positive infinity min(x1, x2,...) The smallest of its arguments: the value closest to negative infinity modf(x) The fractional and integer parts of x in a two-item tuple. Both parts have the same sign as x. The integer part is returned as a float. pow(x, y) The value of x**y. round(x [,n]) x rounded to n digits from the decimal point. Python rounds away from zero as a tie-breaker: round(0.5) is 1.0 and round(-0.5) is -1.0. sqrt(x) The square root of x for x > 0 3/22/2011 5:22 PM
- 46. Python - Numberswith built-in functions 3 of 3 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Random Number Functions: Random numbers are used for games, simulations, testing, security, and privacy applications. Python includes following functions that are commonly used. Function Returns ( description ) choice(seq) A random item from a list, tuple, or string. randrange ([start,] stop [,step]) A randomly selected element from range(start, stop, step) random() A random float r, such that 0 is less than or equal to r and r is less than 1 seed([x]) Sets the integer starting value used in generating random numbers. Call this function before calling any other random module function. Returns None. shuffle(lst) Randomizes the items of a list in place. Returns None. uniform(x, y) A random float r, such that x is less than or equal to r and r is less than y Trigonometric Functions: Python includes following functions that perform trigonometric calculations. Function Description acos(x) Return the arc cosine of x, in radians. asin(x) Return the arc sine of x, in radians. atan(x) Return the arc tangent of x, in radians. atan2(y, x) Return atan(y / x), in radians. cos(x) Return the cosine of x radians. hypot(x, y) Return the Euclidean norm, sqrt(x*x + y*y). sin(x) Return the sine of x radians. tan(x) Return the tangent of x radians. degrees(x) Converts angle x from radians to degrees. radians(x) Converts angle x from degrees to radians. Mathematical Constants: The module also defines two mathematical constants: Constant Description pi The mathematical constant pi. e The mathematical constant e. Copyright © tutorialspoint.com 3/22/2011 5:22 PM
- 47. Python - Stringswith built-in Methods 1 of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Strings Strings are amongst the most popular types in Python. We can create them simply by enclosing characters in quotes. Python treats single quotes the same as double quotes. Creating strings is as simple as assigning a value to a variable. For example: var1 = 'Hello World!' var2 = "Python Programming" Accessing Values in Strings: Python does not support a character type; these are treated as strings of length one, thus also considered a substring. To access substrings, use the square brackets for slicing along with the index or indices to obtain your substring: Example: #!/usr/bin/python var1 = 'Hello World!' var2 = "Python Programming" print "var1[0]: ", var1[0] print "var2[1:5]: ", var2[1:5] This will produce following result: var1[0]: H var2[1:5]: ytho Updating Strings: You can "update" an existing string by (re)assigning a variable to another string. The new value can be related to its previous value or to a completely different string altogether. Example: #!/usr/bin/python var1 = 'Hello World!' print "Updated String :- ", var1[:6] + 'Python' This will produce following result: 3/22/2011 5:23 PM
- 48. Python - Stringswith built-in Methods 2 of 7 Updated String :- http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Hello Python Escape Characters: Following table is a list of escape or non-printable characters that can be represented with backslash notation. NOTE: In a doublequoted string, an escape character is interpreted; in a singlequoted string, an escape character is preserved. Backslash notation Hexadecimal character Description a 0x07 Bell or alert b 0x08 Backspace cx Control-x C-x Control-x e 0x1b Escape f 0x0c Formfeed M-C-x n Meta-Control-x 0x0a nnn Newline Octal notation, where n is in the range 0.7 r 0x0d Carriage return s 0x20 Space t 0x09 Tab v 0x0b Vertical tab x Character x xnn Hexadecimal notation, where n is in the range 0.9, a.f, or A.F String Special Operators: Assume string variable a holds 'Hello' and variable b holds 'Python' then: Operator Description Example + Concatenation - Adds values on either side of the operator a + b will give HelloPython * Repetition - Creates new strings, concatenating multiple copies of the same string a*2 will give -HelloHello [] Slice - Gives the character from the given index a[1] will give e [:] Range Slice - Gives the characters from the given range a[1:4] will give ell in Membership - Returns true if a character exists in the given string H in a will give 1 3/22/2011 5:23 PM
- 49. Python - Stringswith built-in Methods 3 of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... not in Membership - Returns true if a character does not exist in the given string M not in a will give 1 r/R Raw String - Suppress actual meaning of Escape characters. The syntax for raw strings is exactly the same as for normal strings with the exception of the raw string operator, the letter "r," which precedes the quotation marks. The "r" can be lowercase (r) or uppercase (R) and must be placed immediately preceding the first quote mark. print r'n' prints n and print R'n' prints n % Format - Performs String formatting See at next section String Formatting Operator: One of Python's coolest features is the string format operator %. This operator is unique to strings and makes up for the pack of having functions from C's printf() family. Example: #!/usr/bin/python print "My name is %s and weight is %d kg!" % ('Zara', 21) This will produce following result: My name is Zara and weight is 21 kg! Here is the list of complete set of symbols which can be used along with %: Format Symbol Conversion %c character %s string conversion via str() prior to formatting %i signed decimal integer %d signed decimal integer %u unsigned decimal integer %o octal integer %x hexadecimal integer (lowercase letters) %X hexadecimal integer (UPPERcase letters) %e exponential notation (with lowercase 'e') %E exponential notation (with UPPERcase 'E') %f floating point real number %g the shorter of %f and %e %G the shorter of %f and %E Other supported symbols and functionality are listed in the following table: 3/22/2011 5:23 PM
- 50. Python - Stringswith built-in Methods 4 of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Symbol Functionality * argument specifies width or precision - left justification + display the sign <sp> leave a blank space before a positive number # add the octal leading zero ( '0' ) or hexadecimal leading '0x' or '0X', depending on whether 'x' or 'X' were used. 0 pad from left with zeros (instead of spaces) % '%%' leaves you with a single literal '%' (var) mapping variable (dictionary arguments) m.n. m is the minimum total width and n is the number of digits to display after the decimal point (if appl.) Triple Quotes: Python's triple quotes comes to the rescue by allowing strings to span multiple lines, including verbatim NEWLINEs, TABs, and any other special characters. The syntax for triple quotes consists of three consecutive single or double quotes. #!/usr/bin/python para_str = """this is a long string that is made up of several lines and non-printable characters such as TAB ( t ) and they will show up that way when displayed. NEWLINEs within the string, whether explicitly given like this within the brackets [ n ], or just a NEWLINE within the variable assignment will also show up. """ print para_str; This will produce following result. Note how every single special character has been converted to its printed form, right down to the last NEWLINE at the end of the string between the "up." and closing triple quotes. Also note that NEWLINEs occur either with an explicit carriage return at the end of a line or its escape code (n): this is a long string that is made up of several lines and non-printable characters such as TAB ( ) and they will show up that way when displayed. NEWLINEs within the string, whether explicitly given like this within the brackets [ ], or just a NEWLINE within the variable assignment will also show up. Raw String: Raw strings don't treat the backslash as a special character at all. Every character you put into a raw string stays the way you wrote it: #!/usr/bin/python 3/22/2011 5:23 PM
- 51. Python - Stringswith built-in Methods 5 of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... print 'C:nowhere' This would print following result: C:nowhere Now let's make use of raw string. We would put expression in r'expression' as follows: #!/usr/bin/python print r'C:nowhere' This would print following result: C:nowhere Unicode String: Normal strings in Python are stored internally as 8-bit ASCII, while Unicode strings are stored as 16-bit Unicode. This allows for a more varied set of characters, including special characters from most languages in the world. I'll restrict my treatment of Unicode strings to the following: #!/usr/bin/python print u'Hello, world!' This would print following result: Hello, world! As you can see, Unicode strings use the prefix u, just as raw strings use the prefix r. Built-in String Methods: Python includes following string method: SN Methods with Description 1 capitalize() Capitalizes first letter of string 2 center(width, fillchar) Returns a space-padded string with the original string centered to a total of width columns 3 count(str, beg= 0,end=len(string)) Counts how many times str occurs in string, or in a substring of string if starting index beg and ending index end are given 3 decode(encoding='UTF-8',errors='strict') Decodes the string using the codec registered for encoding. encoding defaults to the default string encoding. 3/22/2011 5:23 PM
- 52. Python - Stringswith built-in Methods 6 of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... 4 encode(encoding='UTF-8',errors='strict') Returns encoded string version of string; on error, default is to raise a ValueError unless errors is given with 'ignore' or 'replace'. 5 endswith(suffix, beg=0, end=len(string)) Determines if string or a substring of string (if starting index beg and ending index end are given) ends with suffix; Returns true if so, and false otherwise 6 expandtabs(tabsize=8) Expands tabs in string to multiple spaces; defaults to 8 spaces per tab if tabsize not provided 7 find(str, beg=0 end=len(string)) Determine if str occurs in string, or in a substring of string if starting index beg and ending index end are given; returns index if found and -1 otherwise 8 index(str, beg=0, end=len(string)) Same as find(), but raises an exception if str not found 9 isa1num() Returns true if string has at least 1 character and all characters are alphanumeric and false otherwise 10 isalpha() Returns true if string has at least 1 character and all characters are alphabetic and false otherwise 11 isdigit() Returns true if string contains only digits and false otherwise 12 islower() Returns true if string has at least 1 cased character and all cased characters are in lowercase and false otherwise 13 isnumeric() Returns true if a unicode string contains only numeric characters and false otherwise 14 isspace() Returns true if string contains only whitespace characters and false otherwise 15 istitle() Returns true if string is properly "titlecased" and false otherwise 16 isupper() Returns true if string has at least one cased character and all cased characters are in uppercase and false otherwise 17 join(seq) Merges (concatenates) the string representations of elements in sequence seq into a string, with separator string 18 len(string) Returns the length of the string 19 ljust(width[, fillchar]) Returns a space-padded string with the original string left-justified to a total of width columns 20 lower() Converts all uppercase letters in string to lowercase 21 lstrip() Removes all leading whitespace in string 22 maketrans() Returns a translation table to be used in translate function. 23 max(str) Returns the max alphabetical character from the string str 3/22/2011 5:23 PM
- 53. Python - Stringswith built-in Methods 7 of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... 24 min(str) Returns the min alphabetical character from the string str 25 replace(old, new [, max]) Replaces all occurrences of old in string with new, or at most max occurrences if max given 26 rfind(str, beg=0,end=len(string)) Same as find(), but search backwards in string 27 rindex( str, beg=0, end=len(string)) Same as index(), but search backwards in string 28 rjust(width,[, fillchar]) Returns a space-padded string with the original string right-justified to a total of width columns. 29 rstrip() Removes all trailing whitespace of string 30 split(str="", num=string.count(str)) Splits string according to delimiter str (space if not provided) and returns list of substrings; split into at most num substrings if given 31 splitlines( num=string.count('n')) Splits string at all (or num) NEWLINEs and returns a list of each line with NEWLINEs removed 32 startswith(str, beg=0,end=len(string)) Determines if string or a substring of string (if starting index beg and ending index end are given) starts with substring str; Returns true if so, and false otherwise 33 strip([chars]) Performs both lstrip() and rstrip() on string 34 swapcase() Inverts case for all letters in string 35 title() Returns "titlecased" version of string, that is, all words begin with uppercase, and the rest are lowercase 36 translate(table, deletechars="") Translates string according to translation table str(256 chars), removing those in the del string 37 upper() Converts lowercase letters in string to uppercase 38 zfill (width) Returns original string leftpadded with zeros to a total of width characters; intended for numbers, zfill() retains any sign given (less one zero) 39 isdecimal() Returns true if a unicode string contains only decimal characters and false otherwise Copyright © tutorialspoint.com 3/22/2011 5:23 PM
- 54. Python - ListData Types 1 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Lists Few words about Python Sequences: The most basic data structure in Python is the sequence. Each element of a sequence is assigned a number - its position, or index. The first index is zero, the second index is one, and so forth. Python has six built-in types of sequences, but the most common ones are lists and tuples which we would see in this tutorial. There are certain things you can do with all sequence types. These operations include indexing, slicing, adding, multiplying, and checking for membership. In addition, Python has built-in functions for finding the length of a sequence, and for finding its largest and smallest elements. Python Lists: The list is a most versatile datatype available in Python, which can be written as a list of commaseparated values (items) between square brackets. Good thing about a list that items in a list need not all have the same type: Creating a list is as simple as putting different comma-separated values between squere brackets. For example: list1 = ['physics', 'chemistry', 1997, 2000]; list2 = [1, 2, 3, 4, 5 ]; list3 = ["a", "b", "c", "d"]; Like string indices, list indices start at 0, and lists can be sliced, concatenated and so on. Accessing Values in Lists: To access values in lists, use the square brackets for slicing along with the index or indices to obtain value available at that index: Example: #!/usr/bin/python list1 = ['physics', 'chemistry', 1997, 2000]; list2 = [1, 2, 3, 4, 5, 6, 7 ]; print "list1[0]: ", list1[0] print "list2[1:5]: ", list2[1:5] This will produce following result: list1[0]: physics list2[1:5]: [2, 3, 4, 5] 3/22/2011 5:23 PM
- 55. Python - ListData Types 2 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Updating Lists: You can update single or multiple elements of lists by giving the slice on the left-hand side of the assignment operator, and you can add to elements in a list with the append() method: Example: #!/usr/bin/python list1 = ['physics', 'chemistry', 1997, 2000]; print "Value available at index 2 : " print list1[2]; list1[2] = 2001; print "New value available at index 2 : " print list1[2]; Note: append() method is discussed in subsequent section. This will produce following result: Value available at index 2 : 1997 New value available at index 2 : 2001 Delete List Elements: To remove a list element, you can use either the del statement if you know exactly which element(s) you are deleting or the remove() method if you do not know. Example: #!/usr/bin/python list1 = ['physics', 'chemistry', 1997, 2000]; print list1; del list1[2]; print "After deleting value at index 2 : " print list1; This will produce following result: ['physics', 'chemistry', 1997, 2000] After deleting value at index 2 : ['physics', 'chemistry', 2000] Note: remove() method is discussed in subsequent section. Basic List Operations: Lists respond to the + and * operators much like strings; they mean concatenation and repetition here too, except that the result is a new list, not a string. In fact, lists respond to all of the general sequence operations we used on strings in the prior chapter : 3/22/2011 5:23 PM
- 56. Python - ListData Types 3 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Python Expression Results Description len([1, 2, 3]) 3 Length [1, 2, 3] + [4, 5, 6] [1, 2, 3, 4, 5, 6] Concatenation ['Hi!'] * 4 ['Hi!', 'Hi!', 'Hi!', 'Hi!'] Repetition 3 in [1, 2, 3] True Membership for x in [1, 2, 3]: print x, 123 Iteration Indexing, Slicing, and Matrixes: Because lists are sequences, indexing and slicing work the same way for lists as they do for strings. Assuming following input: L = ['spam', 'Spam', 'SPAM!'] Python Expression Results Description L[2] 'SPAM!' Offsets start at zero L[-2] 'Spam' Negative: count from the right L[1:] ['Spam', 'SPAM!'] Slicing fetches sections Built-in List Functions & Methods: Python includes following list functions SN Function with Description 1 cmp(list1, list2) Compares elements of both lists. 2 len(list) Gives the total length of the list. 3 max(list) Returns item from the list with max value. 4 min(list) Returns item from the list with min value. 5 list(seq) Converts a tuple into list. Python includes following list methods SN Methods with Description 1 list.append(obj) Appends object obj to list 2 list.count(obj) Returns count of how many times obj occurs in list 3 list.extend(seq) Appends the contents of seq to list 3/22/2011 5:23 PM
- 57. Python - ListData Types 4 of 4 4 list.index(obj) Returns the lowest index in list that obj appears 5 list.insert(index, obj) Inserts object obj into list at offset index 6 list.pop(obj=list[-1]) Removes and returns last object or obj from list 7 list.remove(obj) Removes object obj from list 8 list.reverse() Reverses objects of list in place 9 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... list.sort([func]) Sorts objects of list, use compare func if given Copyright © tutorialspoint.com 3/22/2011 5:23 PM
- 58. Python - TuplesData Type 1 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Tuples A tuple is a sequence of immutable Python objects. Tuples are sequences, just like lists. The only difference is that tuples can't be changed ie. tuples are immutable and tuples use parentheses and lists use square brackets. Creating a tuple is as simple as putting different comma-separated values and optionally you can put these comma-separated values between parentheses also. For example: tup1 = ('physics', 'chemistry', 1997, 2000); tup2 = (1, 2, 3, 4, 5 ); tup3 = "a", "b", "c", "d"; The empty tuple is written as two parentheses containing nothing: tup1 = (); To write a tuple containing a single value you have to include a comma, even though there is only one value: tup1 = (50,); Like string indices, tuple indices start at 0, and tuples can be sliced, concatenated and so on. Accessing Values in Tuples: To access values in tuple, use the square brackets for slicing along with the index or indices to obtain value available at that index: Example: #!/usr/bin/python tup1 = ('physics', 'chemistry', 1997, 2000); tup2 = (1, 2, 3, 4, 5, 6, 7 ); print "tup1[0]: ", tup1[0] print "tup2[1:5]: ", tup2[1:5] This will produce following result: tup1[0]: physics tup2[1:5]: [2, 3, 4, 5] Updating Tuples: Tuples are immutable which means you cannot update them or change values of tuple elements. But we 3/22/2011 5:23 PM
- 59. Python - TuplesData Type 2 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... able able to take portions of an existing tuples to create a new tuples as follows: Example: #!/usr/bin/python tup1 = (12, 34.56); tup2 = ('abc', 'xyz'); # Following action is not valid for tuples # tup1 += tup2; # So let's create a new tuple as follows tup3 = tup1 + tup2; print tup3; This will produce following result: (12, 34.56, 'abc', 'xyz') Delete Tuple Elements: Removing individual tuple elements is not possible. There is, of course, nothing wrong with putting together another tuple with the undesired elements discarded. To explicitly remove an entire tuple, just use the del statement: Example: #!/usr/bin/python tup = ('physics', 'chemistry', 1997, 2000); print tup; del tup; print "After deleting tup : " print tup; This will produce following result. Note an exception raised, this is because after del tup tuple does not exist any more: ('physics', 'chemistry', 1997, 2000) After deleting tup : Traceback (most recent call last): File "test.py", line 9, in <module> print tup; NameError: name 'tup' is not defined Basic Tuples Operations: Tuples respond to the + and * operators much like strings; they mean concatenation and repetition here too, except that the result is a new tuple, not a string. In fact, tuples respond to all of the general sequence operations we used on strings in the prior chapter : 3/22/2011 5:23 PM
- 60. Python - TuplesData Type 3 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Python Expression Results Description len((1, 2, 3)) 3 Length (1, 2, 3) + (4, 5, 6) (1, 2, 3, 4, 5, 6) Concatenation ['Hi!'] * 4 ('Hi!', 'Hi!', 'Hi!', 'Hi!') Repetition 3 in (1, 2, 3) True Membership for x in (1, 2, 3): print x, 123 Iteration Indexing, Slicing, and Matrixes: Because tuples are sequences, indexing and slicing work the same way for tuples as they do for strings. Assuming following input: L = ('spam', 'Spam', 'SPAM!') Python Expression Results Description L[2] 'SPAM!' Offsets start at zero L[-2] 'Spam' Negative: count from the right L[1:] ['Spam', 'SPAM!'] Slicing fetches sections No Enclosing Delimiters: Any set of multiple objects, comma-separated, written without identifying symbols, i.e., brackets for lists, parentheses for tuples, etc., default to tuples, as indicated in these short examples: #!/usr/bin/python print 'abc', -4.24e93, 18+6.6j, 'xyz'; x, y = 1, 2; print "Value of x , y : ", x,y; print var; This will reduce following result: abc -4.24e+93 (18+6.6j) xyz Value of x , y : 1 2 Built-in Tuple Functions: Python includes following tuple functions SN Function with Description 1 cmp(tuple1, tuple2) Compares elements of both tuples. 2 len(tuple) Gives the total length of the tuple. 3/22/2011 5:23 PM
- 61. Python - TuplesData Type 4 of 4 3 max(tuple) Returns item from the tuple with max value. 4 min(tuple) Returns item from the tuple with min value. 5 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... tuple(seq) Converts a list into tuple. Copyright © tutorialspoint.com 3/22/2011 5:23 PM
- 62. Python - DictionaryData Type 1 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Dictionary A dictionary is mutable and is another container type that can store any number of Python objects, including other container types. Dictionaries consist of pairs (called items) of keys and their corresponding values. Python dictionaries are also known as associative arrays or hash tables. The general syntax of a dictionary is as follows: dict = {'Alice': '2341', 'Beth': '9102', 'Cecil': '3258'} You can create dictionary in the following way as well: dict1 = { 'abc': 456 }; dict2 = { 'abc': 123, 98.6: 37 }; Each key is separated from its value by a colon (:), the items are separated by commas, and the whole thing is enclosed in curly braces. An empty dictionary without any items is written with just two curly braces, like this: {}. Keys are unique within a dictionary while values may not be. The values of a dictionary can be of any type, but the keys must be of an immutable data type such as strings, numbers, or tuples. Accessing Values in Dictionary: To access dictionary elements, you use the familiar square brackets along with the key to obtain its value: Example: #!/usr/bin/python dict = {'Name': 'Zara', 'Age': 7, 'Class': 'First'}; print "dict['Name']: ", dict['Name']; print "dict['Age']: ", dict['Age']; This will produce following result: dict['Name']: Zara dict['Age']: 7 If we attempt to access a data item with a key which is not part of the dictionary, we get an error as follows: #!/usr/bin/python 3/22/2011 5:23 PM
- 63. Python - DictionaryData Type 2 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... dict = {'Name': 'Zara', 'Age': 7, 'Class': 'First'}; print "dict['Alice']: ", dict['Alice']; This will produce following result: dict['Zara']: Traceback (most recent call last): File "test.py", line 4, in <module> print "dict['Alice']: ", dict['Alice']; KeyError: 'Alice' Updating Dictionary: You can update a dictionary by adding a new entry or item (i.e., a key-value pair), modifying an existing entry, or deleting an existing entry as shown below: Example: #!/usr/bin/python dict = {'Name': 'Zara', 'Age': 7, 'Class': 'First'}; dict['Age'] = 8; # update existing entry dict['School'] = "DPS School"; # Add new entry print "dict['Age']: ", dict['Age']; print "dict['School']: ", dict['School']; This will produce following result: dict['Age']: 8 dict['School']: DPS School Delete Dictionary Elements: You can either remove individual dictionary elements or clear the entire contents of a dictionary. You can also delete entire dictionary in a single operation. To explicitly remove an entire dictionary, just use the del statement: Example: #!/usr/bin/python dict = {'Name': 'Zara', 'Age': 7, 'Class': 'First'}; del dict['Name']; # remove entry with key 'Name' dict.clear(); # remove all entries in dict del dict ; # delete entire dictionary print "dict['Age']: ", dict['Age']; print "dict['School']: ", dict['School']; 3/22/2011 5:23 PM
- 64. Python - DictionaryData Type 3 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... This will produce following result. Note an exception raised, this is because after del dict dictionary does not exist any more: dict['Age']: Traceback (most recent call last): File "test.py", line 8, in <module> print "dict['Age']: ", dict['Age']; TypeError: 'type' object is unsubscriptable Note: del() method is discussed in subsequent section. Properties of Dictionary Keys: Dictionary values have no restrictions. They can be any arbitrary Python object, either standard objects or user-defined objects. However, same is not true for the keys. There are two important points to remember about dictionary keys: (a) More than one entry per key not allowed. Which means no duplicate key is allowed. When duplicate keys encountered during assignment, the last assignment wins. Example: #!/usr/bin/python dict = {'Name': 'Zara', 'Age': 7, 'Name': 'Manni'}; print "dict['Name']: ", dict['Name']; This will produce following result: dict['Name']: Manni (b) Keys must be immutable. Which means you can use strings, numbers, or tuples as dictionary keys but something like ['key'] is not allowed. Example: #!/usr/bin/python dict = {['Name']: 'Zara', 'Age': 7}; print "dict['Name']: ", dict['Name']; This will produce following result. Note an exception raised: Traceback (most recent call last): File "test.py", line 3, in <module> dict = {['Name']: 'Zara', 'Age': 7}; TypeError: list objects are unhashable Built-in Dictionary Functions & Methods: Python includes following dictionary functions 3/22/2011 5:23 PM
- 65. Python - DictionaryData Type 4 of 4 SN http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Function with Description 1 cmp(dict1, dict2) Compares elements of both dict. 2 len(dict) Gives the total length of the dictionary. This would be equal to the number of items in the dictionary. 3 str(dict) Produces a printable string representation of a dictionary 4 type(variable) Returns the type of the passed variable. If passed variable is dictionary then it would return a dictionary type. Python includes following dictionary methods SN Methods with Description 1 dict.clear() Removes all elements of dictionary dict 2 dict.copy() Returns a shallow copy of dictionary dict 2 dict.fromkeys() Create a new dictionary with keys from seq and values set to value. 3 dict.get(key, default=None) For key key, returns value or default if key not in dictionary 4 dict.has_key(key) Returns true if key in dictionary dict, false otherwise 5 dict.items() Returns a list of dict's (key, value) tuple pairs 6 dict.keys() Returns list of dictionary dict's keys 7 dict.setdefault(key, default=None) Similar to get(), but will set dict[key]=default if key is not already in dict 8 dict.update(dict2) Adds dictionary dict2's key-values pairs to dict 9 dict.values() Returns list of dictionary dict2's values Copyright © tutorialspoint.com 3/22/2011 5:23 PM
- 66. Python - Dateand Time 1 of 5 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Date and Time A Python program can handle date & time in several ways. Converting between date formats is a common chore for computers. Python's time and calendar modules help track dates and times. What is Tick? Time intervals are floating-point numbers in units of seconds. Particular instants in time are expressed in seconds since 12:00am, January 1, 1970(epoch). There is a popular time module available in Python which provides functions for working with times, and for converting between representations. The function time.time() returns the current system time in ticks since 12:00am, January 1, 1970(epoch). Example: #!/usr/bin/python import time; # This is required to include time module. ticks = time.time() print "Number of ticks since 12:00am, January 1, 1970:", ticks This would produce a result something as follows: Number of ticks since 12:00am, January 1, 1970: 7186862.73399 Date arithmetic is easy to do with ticks. However, dates before the epoch cannot be represented in this form. Dates in the far future also cannot be represented this way - the cutoff point is sometime in 2038 for UNIX and Windows. What is TimeTuple? Many of Python's time functions handle time as a tuple of 9 numbers, as shown below: Index Field Values 0 4-digit year 2008 1 Month 1 to 12 2 Day 1 to 31 3 Hour 0 to 23 4 Minute 0 to 59 5 Second 0 to 61 (60 or 61 are leap-seconds) 6 Day of Week 0 to 6 (0 is Monday) 7 Day of year 1 to 366 (Julian day) 8 Daylight savings -1, 0, 1, -1 means library determines DST 3/22/2011 5:24 PM
- 67. Python - Dateand Time 2 of 5 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... The above tuple is equivalent to struct_time structure. This structure has following attributes: Index Attributes Values 0 tm_year 2008 1 tm_mon 1 to 12 2 tm_mday 1 to 31 3 tm_hour 0 to 23 4 tm_min 0 to 59 5 tm_sec 0 to 61 (60 or 61 are leap-seconds) 6 tm_wday 0 to 6 (0 is Monday) 7 tm_yday 1 to 366 (Julian day) 8 tm_isdst -1, 0, 1, -1 means library determines DST Example I: Getting current time -: To translate a time instant from a seconds since the epoch floating-point value into a time-tuple, pass the floating-point value to a function (e.g., localtime) that returns a time-tuple with all nine items valid: #!/usr/bin/python localtime = time.localtime(time.time()) print "Local current time :", localtime This would produce following result which could be formatted in any other presentable form: Local current time : (2008, 5, 15, 12, 55, 32, 0, 136, 1) Example II: Getting formatted time -: You can format any time as per your requirement, but simple method to get time in readable format is asctime(): #!/usr/bin/python import time; localtime = time.asctime( time.localtime(time.time()) ) print "Local current time :", localtime This would produce following result: Local current time : Tue Jan 13 10:17:09 2009 Example III: Getting calendar for a month -: The calendar module gives a wide range of methods to play with yearly and monthly calendars. Here we print a calendar for a given month ( Jan 2008 ): #!/usr/bin/python import calendar 3/22/2011 5:24 PM
- 68. Python - Dateand Time 3 of 5 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... cal = calendar.month(2008, 1) print "Here is the calendar:" print cal; This would produce following result: Here is the January Mo Tu We Th 1 2 3 7 8 9 10 14 15 16 17 21 22 23 24 28 29 30 31 calendar: 2008 Fr Sa Su 4 5 6 11 12 13 18 19 20 25 26 27 The time Module: There is a popular time module available in Python which provides functions for working with times, and for converting between representations. Here is the list of all available methods: SN Function with Description 1 time.altzone The offset of the local DST timezone, in seconds west of UTC, if one is defined. This is negative if the local DST timezone is east of UTC (as in Western Europe, including the UK). Only use this if daylight is nonzero. 2 time.asctime([tupletime]) Accepts a time-tuple and returns a readable 24-character string such as 'Tue Dec 11 18:07:14 2008'. 3 time.clock( ) Returns the current CPU time as a floating-point number of seconds. To measure computational costs of different approaches, the value of time.clock is more useful than that of time.time(). 4 time.ctime([secs]) Like asctime(localtime(secs)) and without arguments is like asctime( ) 5 time.gmtime([secs]) Accepts an instant expressed in seconds since the epoch and returns a time-tuple t with the UTC time. Note : t.tm_isdst is always 0 6 time.localtime([secs]) Accepts an instant expressed in seconds since the epoch and returns a time-tuple t with the local time (t.tm_isdst is 0 or 1, depending on whether DST applies to instant secs by local rules). 7 time.mktime(tupletime) Accepts an instant expressed as a time-tuple in local time and returns a floating-point value with the instant expressed in seconds since the epoch. 8 time.sleep(secs) Suspends the calling thread for secs seconds. 9 time.strftime(fmt[,tupletime]) Accepts an instant expressed as a time-tuple in local time and returns a string representing the instant as specified by string fmt. 10 time.strptime(str,fmt='%a %b %d %H:%M:%S %Y') Parses str according to format string fmt and returns the instant in time-tuple format. 3/22/2011 5:24 PM
- 69. Python - Dateand Time 4 of 5 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... 11 time.time( ) Returns the current time instant, a floating-point number of seconds since the epoch. 12 time.tzset() Resets the time conversion rules used by the library routines. The environment variable TZ specifies how this is done. There are following two important attributes available with time module: SN Attribute with Description 1 time.timezone Attribute time.timezone is the offset in seconds of the local time zone (without DST) from UTC (>0 in the Americas; <=0 in most of Europe, Asia, Africa). 2 time.tzname Attribute time.tzname is a pair of locale-dependent strings, which are the names of the local time zone without and with DST, respectively. The calendar Module The calendar module supplies calendar-related functions, including functions to print a text calendar for a given month or year. By default, calendar takes Monday as the first day of the week and Sunday as the last one. To change this, call calendar.setfirstweekday() function. Here is a list of functions available with the calendar module: SN Function with Description 1 calendar.calendar(year,w=2,l=1,c=6) Returns a multiline string with a calendar for year year formatted into three columns separated by c spaces. w is the width in characters of each date; each line has length 21*w+18+2*c. l is the number of lines for each week. 2 calendar.firstweekday( ) Returns the current setting for the weekday that starts each week. By default, when calendar is first imported, this is 0, meaning Monday. 3 calendar.isleap(year) Returns True if year is a leap year; otherwise, False. 4 calendar.leapdays(y1,y2) Returns the total number of leap days in the years within range(y1,y2). 5 calendar.month(year,month,w=2,l=1) Returns a multiline string with a calendar for month month of year year, one line per week plus two header lines. w is the width in characters of each date; each line has length 7*w+6. l is the number of lines for each week. 6 calendar.monthcalendar(year,month) Returns a list of lists of ints. Each sublist denotes a week. Days outside month month of year year are set to 0; days within the month are set to their day-of-month, 1 and up. 7 calendar.monthrange(year,month) Returns two integers. The first one is the code of the weekday for the first day of the month month in year year; the second one is the number of days in the month. Weekday codes are 0 (Monday) to 6 (Sunday); month numbers are 1 to 12. 8 calendar.prcal(year,w=2,l=1,c=6) Like print calendar.calendar(year,w,l,c). 3/22/2011 5:24 PM
- 70. Python - Dateand Time 5 of 5 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... 9 calendar.prmonth(year,month,w=2,l=1) Like print calendar.month(year,month,w,l). 10 calendar.setfirstweekday(weekday) Sets the first day of each week to weekday code weekday. Weekday codes are 0 (Monday) to 6 (Sunday). 11 calendar.timegm(tupletime) The inverse of time.gmtime: accepts a time instant in time-tuple form and returns the same instant as a floating-point number of seconds since the epoch. 12 calendar.weekday(year,month,day) Returns the weekday code for the given date. Weekday codes are 0 (Monday) to 6 (Sunday); month numbers are 1 (January) to 12 (December). Other Modules & Functions: If you are intrested then here you would find a list of other important modules and functions to play with date & time in Python: The datetime Module The pytz Module The dateutil Module Copyright © tutorialspoint.com 3/22/2011 5:24 PM
- 71. Python - Functions 1of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Functions A function is a block of organized, reusable code that is used to perform a single, related action. Functions provides better modularity for your application and a high degree of code reusing. As you already know, Python gives you many built-in functions like print() etc. but you can also create your own functions. These functions are called user-defined functions. Defining a Function You can define functions to provide the required functionality. Here are simple rules to define a function in Python: Function blocks begin with the keyword def followed by the function name and parentheses ( ( ) ). Any input parameters or arguments should be placed within these parentheses. You can also define parameters inside these parentheses. The first statement of a function can be an optional statement - the documentation string of the function or docstring. The code block within every function starts with a colon (:) and is indented. The statement return [expression] exits a function, optionally passing back an expression to the caller. A return statement with no arguments is the same as return None. Syntax: def functionname( parameters ): "function_docstring" function_suite return [expression] By default, parameters have a positional behavior, and you need to inform them in the same order that they were defined. Example: Here is the simplest form of a Python function. This function takes a string as input parameter and prints it on standard screen. def printme( str ): "This prints a passed string into this function" print str return Calling a Function Defining a function only gives it a name, specifies the parameters that are to be included in the function, and structures the blocks of code. Once the basic structure of a function is finalized, you can execute it by calling it from another function or 3/22/2011 5:24 PM
- 72. Python - Functions 2of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... directly from the Python prompt. Following is the example to call printme() function: #!/usr/bin/python # Function definition is here def printme( str ): "This prints a passed string into this function" print str; return; # Now you can call printme function printme("I'm first call to user defined function!"); printme("Again second call to the same function"); This would produce following result: I'm first call to user defined function! Again second call to the same function Pass by reference vs value All parameters (arguments) in the Python language are passed by reference. It means if you change what a parameter refers to within a function, the change also reflects back in the calling function. For example: #!/usr/bin/python # Function definition is here def changeme( mylist ): "This changes a passed list into this function" mylist.append([1,2,3,4]); print "Values inside the function: ", mylist return # Now you can call changeme function mylist = [10,20,30]; changeme( mylist ); print "Values outside the function: ", mylist Here we are maintaining reference of the passed object and appending values in the same object. So this would produce following result: Values inside the function: [10, 20, 30, [1, 2, 3, 4]] Values outside the function: [10, 20, 30, [1, 2, 3, 4]] There is one more example where argument is being passed by reference but inside the function, but the reference is being over-written. #!/usr/bin/python # Function definition is here def changeme( mylist ): "This changes a passed list into this function" mylist = [1,2,3,4]; # This would assig new reference in mylist 3/22/2011 5:24 PM
- 73. Python - Functions 3of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... print "Values inside the function: ", mylist return # Now you can call changeme function mylist = [10,20,30]; changeme( mylist ); print "Values outside the function: ", mylist The parameter mylist is local to the function changeme. Changing mylist within the function does not affect mylist. The function accomplishes nothing and finally this would produce following result: Values inside the function: [1, 2, 3, 4] Values outside the function: [10, 20, 30] Function Arguments: You can call a function by using the following types of formal arguments:: Required arguments Keyword arguments Default arguments Variable-length arguments Required arguments: Required arguments are the arguments passed to a function in correct positional order. Here the number of arguments in the function call should match exactly with the function definition. To call the function printme() you definitely need to pass one argument otherwise it would give a syntax error as follows: #!/usr/bin/python # Function definition is here def printme( str ): "This prints a passed string into this function" print str; return; # Now you can call printme function printme(); This would produce following result: Traceback (most recent call last): File "test.py", line 11, in <module> printme(); TypeError: printme() takes exactly 1 argument (0 given) Keyword arguments: Keyword arguments are related to the function calls. When you use keyword arguments in a function call, the caller identifies the arguments by the parameter name. This allows you to skip arguments or place them out of order because the Python interpreter is able to use the keywords provided to match the values with parameters. You can also make keyword calls to the printme() function in the following ways: 3/22/2011 5:24 PM
- 74. Python - Functions 4of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... #!/usr/bin/python # Function definition is here def printme( str ): "This prints a passed string into this function" print str; return; # Now you can call printme function printme( str = "My string"); This would produce following result: My string Following example gives more clear picture. Note, here order of the parameter does not matter: #!/usr/bin/python # Function definition is here def printinfo( name, age ): "This prints a passed info into this function" print "Name: ", name; print "Age ", age; return; # Now you can call printinfo function printinfo( age=50, name="miki" ); This would produce following result: Name: miki Age 50 Default arguments: A default argument is an argument that assumes a default value if a value is not provided in the function call for that argument. Following example gives idea on default arguments, it would print default age if it is not passed: #!/usr/bin/python # Function definition is here def printinfo( name, age = 35 ): "This prints a passed info into this function" print "Name: ", name; print "Age ", age; return; # Now you can call printinfo function printinfo( age=50, name="miki" ); printinfo( name="miki" ); This would produce following result: 3/22/2011 5:24 PM
- 75. Python - Functions 5of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Name: miki Age 50 Name: miki Age 35 Variable-length arguments: You may need to process a function for more arguments than you specified while defining the function. These arguments are called variable-length arguments and are not named in the function definition, unlike required and default arguments. The general syntax for a function with non-keyword variable arguments is this: def functionname([formal_args,] *var_args_tuple ): "function_docstring" function_suite return [expression] An asterisk (*) is placed before the variable name that will hold the values of all nonkeyword variable arguments. This tuple remains empty if no additional arguments are specified during the function call. For example: #!/usr/bin/python # Function definition is here def printinfo( arg1, *vartuple ): "This prints a variable passed arguments" print "Output is: " print arg1 for var in vartuple: print var return; # Now you can call printinfo function printinfo( 10 ); printinfo( 70, 60, 50 ); This would produce following result: Output is: 10 Output is: 70 60 50 The Anonymous Functions: You can use the lambda keyword to create small anonymous functions. These functions are called anonymous because they are not declared in the standard manner by using the def keyword. Lambda forms can take any number of arguments but return just one value in the form of an expression. They cannot contain commands or multiple expressions. An anonymous function cannot be a direct call to print because lambda requires an expression. Lambda functions have their own local namespace and cannot access variables other than those in 3/22/2011 5:24 PM
- 76. Python - Functions 6of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... their parameter list and those in the global namespace. Although it appears that lambda's are a one-line version of a function, they are not equivalent to inline statements in C or C++, whose purpose is by passing function stack allocation during invocation for performance reasons. Syntax: The syntax of lambda functions contains only a single statement, which is as follows: lambda [arg1 [,arg2,.....argn]]:expression Example: Following is the example to show how lembda form of function works: #!/usr/bin/python # Function definition is here sum = lambda arg1, arg2: arg1 + arg2; # Now you can call sum as a function print "Value of total : ", sum( 10, 20 ) print "Value of total : ", sum( 20, 20 ) This would produce following result: Value of total : Value of total : 30 40 The return Statement: The statement return [expression] exits a function, optionally passing back an expression to the caller. A return statement with no arguments is the same as return None All the above examples are not returning any value, but if you like you can return a value from a function as follows: #!/usr/bin/python # Function definition is here def sum( arg1, arg2 ): # Add both the parameters and return them." total = arg1 + arg2 print "Inside the function : ", total return total; # Now you can call sum function total = sum( 10, 20 ); print "Outside the function : ", total This would produce following result: 3/22/2011 5:24 PM
- 77. Python - Functions 7of 7 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Inside the function : 30 Outside the function : 30 Scope of Variables: All variables in a program may not be accessible at all locations in that program. This depends on where you have declared a variable. The scope of a variable determines the portion of the program where you can access a particular identifier. There are two basic scopes of variables in Python: Global variables Local variables Global vs. Local variables: Variables that are defined inside a function body have a local scope, and those defined outside have a global scope. This means that local variables can be accessed only inside the function in which they are declared whereas global variables can be accessed throughout the program body by all functions. When you call a function, the variables declared inside it are brought into scope. Example: #!/usr/bin/python total = 0; # This is global variable. # Function definition is here def sum( arg1, arg2 ): # Add both the parameters and return them." total = arg1 + arg2; # Here total is local variable. print "Inside the function local total : ", total return total; # Now you can call sum function sum( 10, 20 ); print "Outside the function global total : ", total This would produce following result: Inside the function local total : 30 Outside the function global total : 0 Copyright © tutorialspoint.com 3/22/2011 5:24 PM
- 78. Python - Modules 1of 5 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Modules A module allows you to logically organize your Python code. Grouping related code into a module makes the code easier to understand and use. A module is a Python object with arbitrarily named attributes that you can bind and reference. Simply, a module is a file consisting of Python code. A module can define functions, classes, and variables. A module can also include runnable code. Example: The Python code for a module named aname normally resides in a file named aname.py. Here's an example of a simple module, hello.py def print_func( par ): print "Hello : ", par return The import Statement: You can use any Python source file as a module by executing an import statement in some other Python source file. import has the following syntax: import module1[, module2[,... moduleN] When the interpreter encounters an import statement, it imports the module if the module is present in the search path. Asearch path is a list of directories that the interpreter searches before importing a module. Example: To import the module hello.py, you need to put the following command at the top of the script: #!/usr/bin/python # Import module hello import hello # Now you can call defined function that module as follows hello.print_func("Zara") This would produce following result: Hello : Zara A module is loaded only once, regardless of the number of times it is imported. This prevents the module execution from happening over and over again if multiple imports occur. 3/22/2011 5:25 PM
- 79. Python - Modules 2of 5 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... The from...import Statement Python's from statement lets you import specific attributes from a module into the current namespace: Syntax: from modname import name1[, name2[, ... nameN]] Example: For example, to import the function fibonacci from the module fib, use the following statement: from fib import fibonacci This statement does not import the entire module fib into the current namespace; it just introduces the item fibonacci from the module fib into the global symbol table of the importing module. The from...import * Statement: It is also possible to import all names from a module into the current namespace by using the following import statement: from modname import * This provides an easy way to import all the items from a module into the current namespace; however, this statement should be used sparingly. Locating Modules: When you import a module, the Python interpreter searches for the module in the following sequences: The current directory. If the module isn't found, Python then searches each directory in the shell variable PYTHONPATH. If all else fails, Python checks the default path. On UNIX, this default path is normally /usr/local /lib/python/. The module search path is stored in the system module sys as the sys.path variable. The sys.path variable contains the current directory, PYTHONPATH, and the installation-dependent default. The PYTHONPATH Variable: The PYTHONPATH is an environment variable, consisting of a list of directories. The syntax of PYTHONPATH is the same as that of the shell variable PATH. Here is a typical PYTHONPATH from a Windows system: set PYTHONPATH=c:python20lib; And here is a typical PYTHONPATH from a UNIX system: set PYTHONPATH=/usr/local/lib/python 3/22/2011 5:25 PM
- 80. Python - Modules 3of 5 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Namespaces and Scoping: Variables are names (identifiers) that map to objects. A namespace is a dictionary of variable names (keys) and their corresponding objects (values). A Python statement can access variables in a local namespace and in the global namespace. If a local and a global variable have the same name, the local variable shadows the global variable. Each function has its own local namespace. Class methods follow the same scoping rule as ordinary functions. Python makes educated guesses on whether variables are local or global. It assumes that any variable assigned a value in a function is local. Therefore, in order to assign a value to a global variable within a function, you must first use the global statement. The statement global VarName tells Python that VarName is a global variable. Python stops searching the local namespace for the variable. For example, we define a variable Money in the global namespace. Within the function Money, we assign Money a value . therefor Python assumes Money is a local variable. However, we access the value of the local variable Money before setting it, so an UnboundLocalError is the result. Uncommenting the global statement fixes the problem. #!/usr/bin/python Money = 2000 def AddMoney(): # Uncomment the following line to fix the code: # global Money Money = Money + 1 print Money AddMoney() print Money The dir( ) Function: The dir() built-in function returns a sorted list of strings containing the names defined by a module. The list contains the names of all the modules, variables, and functions that are defined in a module. Example: #!/usr/bin/python # Import built-in module math import math content = dir(math) print content; This would produce following result: ['__doc__', '__file__', '__name__', 'acos', 'asin', 'atan', 'atan2', 'ceil', 'cos', 'cosh', 'degrees', 'e', 'exp', 3/22/2011 5:25 PM
- 81. Python - Modules 4of 5 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... 'fabs', 'floor', 'fmod', 'frexp', 'hypot', 'ldexp', 'log', 'log10', 'modf', 'pi', 'pow', 'radians', 'sin', 'sinh', 'sqrt', 'tan', 'tanh'] Here the special string variable __name__ is the module's name, and __file__ is the filename from which the module was loaded. The globals() and locals() Functions: The globals() and locals() functions can be used to return the names in the global and local namespaces depending on the location from where they are called. If locals() is called from within a function, it will return all the names that can be accessed locally from that function. If globals() is called from within a function, it will return all the names that can be accessed globally from that function. The return type of both these functions is dictionary. Therefore, names can be extracted using the keys() function. The reload() Function: When the module is imported into a script, the code in the top-level portion of a module is executed only once. Therefore, if you want to reexecute the top-level code in a module, you can use the reload() function. The reload() function imports a previously imported module again. Syntax: The syntax of the reload() function is this: reload(module_name) Here module_name is the name of the module you want to reload and not the string containing the module name. For example to re-load hello module, do the following: reload(hello) Packages in Python: A package is a hierarchical file directory structure that defines a single Python application environment that consists of modules and subpackages and sub-subpackages, and so on. Example: Consider a file Pots.py available in Phone directory. This file has following line of source code: #!/usr/bin/python def Pots(): print "I'm Pots Phone" Similar way we have another two files having different functions with the same name as above: Phone/Isdn.py file having function Isdn() 3/22/2011 5:25 PM
- 82. Python - Modules 5of 5 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Phone/G3.py file having function G3() Now create one more file __init__.py in Phone directory : Phone/__init__.py To make all of your functions available when you've imported Phone, you need to put explicit import statements in __init__.py as follows: from Pots import Pots from Isdn import Isdn from G3 import G3 After you've added these lines to __init__.py, you have all of these classes available when you've imported the Phone package: #!/usr/bin/python # Now import your Phone Package. import Phone Phone.Pots() Phone.Isdn() Phone.G3() This would produce following result: I'm Pots Phone I'm 3G Phone I'm ISDN Phone Note: In the above example, we have taken example of a single functions in each file, but you can keep multiple functions in your files. You can also define different Python classes in those files and then you can create your packages out of those classes. Copyright © tutorialspoint.com 3/22/2011 5:25 PM
- 83. Python Files I/O 1of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python Files I/O This chapter will cover all the basic I/O functions available in Python. For more functions please refere to standard Python documentation. Printing to the Screen: The simplest way to produce output is using the print statement where you can pass zero or more expressions, separated by commas. This function converts the expressions you pass it to a string and writes the result to standard output as follows: #!/usr/bin/python print "Python is really a great language,", "isn't it?"; This would produce following result on your standard screen: Python is really a great language, isn't it? Reading Keyboard Input: Python provides two built-in functions to read a line of text from standard input, which by default comes from the keyboard. These functions are: raw_input input The raw_input Function: The raw_input([prompt]) function reads one line from standard input and returns it as a string (removing the trailing newline): #!/usr/bin/python str = raw_input("Enter your input: "); print "Received input is : ", str This would prompt you to enter any string and it would display same string on the screen. When I typed "Hello Python!", it output is like this: Enter your input: Hello Python Received input is : Hello Python The input Function: The input([prompt]) function is equivalent to raw_input, except that it assumes the input is a valid Python expression and returns the evaluated result to you: 3/22/2011 5:25 PM
- 84. Python Files I/O 2of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... #!/usr/bin/python str = input("Enter your input: "); print "Received input is : ", str This would produce following result against the entered input: Enter your input: [x*5 for x in range(2,10,2)] Recieved input is : [10, 20, 30, 40] Opening and Closing Files: Until now, you have been reading and writing to the standard input and output. Now we will see how to play with actual data files. Python provides basic functions and methods necessary to manipulate files by default. You can do your most of the file manipulation using a file object. The open Function: Before you can read or write a file, you have to open it using Python's built-in open() function. This function creates a file object which would be utilized to call other support methods associated with it. Syntax: file object = open(file_name [, access_mode][, buffering]) Here is paramters detail: file_name: The file_name argument is a string value that contains the name of the file that you want to access. access_mode: The access_mode determines the mode in which the file has to be opened ie. read, write append etc. A complete list of possible values is given below in the table. This is optional parameter and the default file access mode is read (r) buffering: If the buffering value is set to 0, no buffering will take place. If the buffering value is 1, line buffering will be performed while accessing a file. If you specify the buffering value as an integer greater than 1, then buffering action will be performed with the indicated buffer size. If negative, the buffer size is the system default(default behavior). Here is a list of the different modes of opening a file: Modes Description r Opens a file for reading only. The file pointer is placed at the beginning of the file. This is the default mode. rb Opens a file for reading only in binary format. The file pointer is placed at the beginning of the file. This is the default mode. r+ Opens a file for both reading and writing. The file pointer will be at the beginning of the file. rb+ Opens a file for both reading and writing in binary format. The file pointer will be at the beginning of the file. w Opens a file for writing only. Overwrites the file if the file exists. If the file does not exist, creates a new file for writing. 3/22/2011 5:25 PM
- 85. Python Files I/O 3of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... wb Opens a file for writing only in binary format. Overwrites the file if the file exists. If the file does not exist, creates a new file for writing. w+ Opens a file for both writing and reading. Overwrites the existing file if the file exists. If the file does not exist, creates a new file for reading and writing. wb+ Opens a file for both writing and reading in binary format. Overwrites the existing file if the file exists. If the file does not exist, creates a new file for reading and writing. a Opens a file for appending. The file pointer is at the end of the file if the file exists. That is, the file is in the append mode. If the file does not exist, it creates a new file for writing. ab Opens a file for appending in binary format. The file pointer is at the end of the file if the file exists. That is, the file is in the append mode. If the file does not exist, it creates a new file for writing. a+ Opens a file for both appending and reading. The file pointer is at the end of the file if the file exists. The file opens in the append mode. If the file does not exist, it creates a new file for reading and writing. ab+ Opens a file for both appending and reading in binary format. The file pointer is at the end of the file if the file exists. The file opens in the append mode. If the file does not exist, it creates a new file for reading and writing. The file object atrributes: Once a file is opened and you have one file object, you can get various information related to that file. Here is a list of all attributes related to file object: Attribute Description file.closed Returns true if file is closed, false otherwise. file.mode Returns access mode with which file was opened. file.name Returns name of the file. file.softspace Returns false if space explicitly required with print, true otherwise. Example: #!/usr/bin/python # Open a file fo = open("foo.txt", "wb") print "Name of the file: ", fo.name print "Closed or not : ", fo.closed print "Opening mode : ", fo.mode print "Softspace flag : ", fo.softspace This would produce following result: Name of the file: foo.txt Closed or not : False Opening mode : wb Softspace flag : 0 The close() Method: The close() method of a file object flushes any unwritten information and closes the file object, after which no more writing can be done. 3/22/2011 5:25 PM
- 86. Python Files I/O 4of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Python automatically closes a file when the reference object of a file is reassigned to another file. It is a good practice to use the close() method to close a file. Syntax: fileObject.close(); Example: #!/usr/bin/python # Open a file fo = open("foo.txt", "wb") print "Name of the file: ", fo.name # Close opend file fo.close() This would produce following result: Name of the file: foo.txt Reading and Writing Files: The file object provides a set of access methods to make our lives easier. We would see how to use read() and write() methods to read and write files. The write() Method: The write() method writes any string to an open file. It is important to note that Python strings can have binary data and not just text. The write() method does not add a newline character ('n') to the end of the string: Syntax: fileObject.write(string); Here passed parameter is the content to be written into the opend file. Example: #!/usr/bin/python # Open a file fo = open("foo.txt", "wb") fo.write( "Python is a great language.nYeah its great!!n"); # Close opend file fo.close() The above method would create foo.txt file and would write given content in that file and finally it would close that file. If you would open this file, it would have following content 3/22/2011 5:25 PM
- 87. Python Files I/O 5of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Python is a great language. Yeah its great!! The read() Method: The read() method read a string from an open file. It is important to note that Python strings can have binary data and not just text. Syntax: fileObject.read([count]); Here passed parameter is the number of bytes to be read from the opend file. This method starts reading from the beginning of the file and if count is missing then it tries to read as much as possible, may be until the end of file. Example: Let's take a file foo.txt which we have created above. #!/usr/bin/python # Open a file fo = open("foo.txt", "r+") str = fo.read(10); print "Read String is : ", str # Close opend file fo.close() This would produce following result: Read String is : Python is File Positions: The tell() method tells you the current position within the file in other words, the next read or write will occur at that many bytes from the beginning of the file: The seek(offset[, from]) method changes the current file position. The offset argument indicates the number of bytes to be moved. The from argument specifies the reference position from where the bytes are to be moved. If from is set to 0, it means use the beginning of the file as the reference position and 1 means use the current position as the reference position and if it is set to 2 then the end of the file would be taken as the reference position. Example: Let's take a file foo.txt which we have created above. #!/usr/bin/python # Open a file fo = open("foo.txt", "r+") str = fo.read(10); 3/22/2011 5:25 PM
- 88. Python Files I/O 6of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... print "Read String is : ", str # Check current position position = fo.tell(); print "Current file position : ", position # Reposition pointer at the beginning once again position = fo.seek(0, 0); str = fo.read(10); print "Again read String is : ", str # Close opend file fo.close() This would produce following result: Read String is : Python is Current file position : 10 Again read String is : Python is Renaming and Deleting Files: Python os module provides methods that help you perform file-processing operations, such as renaming and deleting files. To use this module you need to import it first and then you can all any related functions. The rename() Method: The rename() method takes two arguments, the current filename and the new filename. Syntax: os.rename(current_file_name, new_file_name) Example: Following is the example to rename an existing file test1.txt: #!/usr/bin/python import os # Rename a file from test1.txt to test2.txt os.rename( "test1.txt", "test2.txt" ) The delete() Method: You can use the delete() method to delete files by supplying the name of the file to be deleted as the argument. Syntax: os.delete(file_name) Example: 3/22/2011 5:25 PM
- 89. Python Files I/O 7of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Following is the example to delete an existing file test2.txt: #!/usr/bin/python import os # Delete file test2.txt os.delete("text2.txt") Directories in Python: All files are contained within various directories, and Python has no problem handling these too. The os module has several methods that help you create, remove, and change directories. The mkdir() Method: You can use the mkdir() method of the os module to create directories in the current directory. You need to supply an argument to this method, which contains the name of the directory to be created. Syntax: os.mkdir("newdir") Example: Following is the example to create a directory test in the current directory: #!/usr/bin/python import os # Create a directory "test" os.mkdir("test") The chdir() Method: You can use the chdir() method to change the current directory. The chdir() method takes an argument, which is the name of the directory that you want to make the current directory. Syntax: os.chdir("newdir") Example: Following is the example to go into "/home/newdir" directory: #!/usr/bin/python import os # Changing a directory to "/home/newdir" os.chdir("/home/newdir") The getcwd() Method: The getcwd() method displays the current working directory. 3/22/2011 5:25 PM
- 90. Python Files I/O 8of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Syntax: os.getcwd() Example: Following is the example to give current directory: #!/usr/bin/python import os # This would give location of the current directory os.getcwd() The rmdir() Method: The rmdir() method deletes the directory, which is passed as an argument in the method. Before removing a directory, all the contents in it should be removed. Syntax: os.rmdir('dirname') Example: Following is the example to remove "/tmp/test" directory. It is required to give fully qualified name of the directory otherwise it would search for that directory in the current directory. #!/usr/bin/python import os # This would remove "/tmp/test" os.rmdir( "/tmp/test" ) directory. File & Directory Related Methods: There are three important sources which provide a wide range of utility methods to handle and manipulate files & directories on Windows and Unix operating systems. They are as follows: File Object Methods: The file object provides functions to manipulate files. OS Object Methods.: This provides methods to process files as well as directories. Copyright © tutorialspoint.com 3/22/2011 5:25 PM
- 91. Python Exceptions Handling 1of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python Exceptions Handling Python provides two very important features to handle any unexpected error in your Python programs and to add debugging capabilities in them: Exception Handling: This would be covered in this tutorial. Assertions: This would be covered in Assertions in Python tutorial. What is Exception? An exception is an event, which occurs during the execution of a program, that disrupts the normal flow of the program's instructions. In general, when a Python script encounters a situation that it can't cope with, it raises an exception. An exception is a Python object that represents an error. When a Python script raises an exception, it must either handle the exception immediately otherwise it would terminate and come out. Handling an exception: If you have some suspicious code that may raise an exception, you can defend your program by placing the suspicious code in a try: block. After the try: block, include an except: statement, followed by a block of code which handles the problem as elegantly as possible. Syntax: Here is simple syntax of try....except...else blocks: try: You do your operations here; ...................... except ExceptionI: If there is ExceptionI, then execute this block. except ExceptionII: If there is ExceptionII, then execute this block. ...................... else: If there is no exception then execute this block. Here are few important points above the above mentioned syntax: A single try statement can have multiple except statements. This is useful when the try block contains statements that may throw different types of exceptions. You can also provide a generic except clause, which handles any exception. After the except clause(s), you can include an else-clause. The code in the else-block executes if the code in the try: block does not raise an exception. The else-block is a good place for code that does not need the try: block's protection. 3/22/2011 5:25 PM
- 92. Python Exceptions Handling 2of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Example: Here is simple example which opens a file and writes the content in the file and comes out gracefully because there is no problem at all: #!/usr/bin/python try: fh = open("testfile", "w") fh.write("This is my test file for exception handling!!") except IOError: print "Error: can't find file or read data" else: print "Written content in the file successfully" fh.close() This will produce following result: Written content in the file successfully Example: Here is one more simple example which tries to open a file where you do not have permission to write in the file so it raises an exception: #!/usr/bin/python try: fh = open("testfile", "w") fh.write("This is my test file for exception handling!!") except IOError: print "Error: can't find file or read data" else: print "Written content in the file successfully" This will produce following result: Error: can't find file or read data The except clause with no exceptions: You can also use the except statement with no exceptions defined as follows: try: You do your operations here; ...................... except: If there is any exception, then execute this block. ...................... else: If there is no exception then execute this block. This kind of a try-except statement catches all the exceptions that occur. Using this kind of try-except statement is not considered a good programming practice, though, because it catches all exceptions but does not make the programmer identify the root cause of the problem that may occur. 3/22/2011 5:25 PM
- 93. Python Exceptions Handling 3of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... The except clause with multiple exceptions: You can also use the same except statement to handle multiple exceptions as follows: try: You do your operations here; ...................... except(Exception1[, Exception2[,...ExceptionN]]]): If there is any exception from the given exception list, then execute this block. ...................... else: If there is no exception then execute this block. Standard Exceptions: Here is a list standard Exceptions available in Python: Standard Exceptions The try-finally clause: You can use a finally: block along with a try: block. The finally block is a place to put any code that must execute, whether the try-block raised an exception or not. The syntax of the try-finally statement is this: try: You do your operations here; ...................... Due to any exception, this may be skipped. finally: This would always be executed. ...................... Note that you can provide except clause(s), or a finally clause, but not both. You can not use else clause as well along with a finally clause. Example: #!/usr/bin/python try: fh = open("testfile", "w") fh.write("This is my test file for exception handling!!") finally: print "Error: can't find file or read data" If you do not have permission to open the file in writing mode then this will produce following result: Error: can't find file or read data Same example can be written more cleanly as follows: #!/usr/bin/python try: 3/22/2011 5:25 PM
- 94. Python Exceptions Handling 4of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... fh = open("testfile", "w") try: fh.write("This is my test file for exception handling!!") finally: fh.close() except IOError: print "Error: can't find file or read data" When an exception is thrown in the try block, the execution immediately passes to the finally block. After all the statements in the finally block are executed, the exception is raised again and is handled in the except statements if present in the next higher layer of the try-except statement. Argument of an Exception: An exception can have an argument, which is a value that gives additional information about the problem. The contents of the argument vary by exception. You capture an exception's argument by supplying a variable in the except clause as follows: try: You do your operations here; ...................... except ExceptionType, Argument: You can print value of Argument here... If you are writing the code to handle a single exception, you can have a variable follow the name of the exception in the except statement. If you are trapping multiple exceptions, you can have a variable follow the tuple of the exception. This variable will receive the value of the exception mostly containing the cause of the exception. The variable can receive a single value or multiple values in the form of a tuple. This tuple usually contains the error string, the error number, and an error location. Example: Following is an example for a single exception: #!/usr/bin/python # Define a function here. def temp_convert(var): try: return int(var) except ValueError, Argument: print "The argument does not contain numbersn", Argument # Call above function here. temp_convert("xyz"); This would produce following result: The argument does not contain numbers invalid literal for int() with base 10: 'xyz' Raising an exceptions: You can raise exceptions in several ways by using the raise statement. The general syntax for the raise statement. 3/22/2011 5:25 PM
- 95. Python Exceptions Handling 5of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Syntax: raise [Exception [, args [, traceback]]] Here Exception is the type of exception (for example, NameError) and argument is a value for the exception argument. The argument is optional; if not supplied, the exception argument is None. The final argument, traceback, is also optional (and rarely used in practice), and, if present, is the traceback object used for the exception Example: An exception can be a string, a class, or an object. Most of the exceptions that the Python core raises are classes, with an argument that is an instance of the class. Defining new exceptions is quite easy and can be done as follows: def functionName( level ): if level < 1: raise "Invalid level!", level # The code below to this would not be executed # if we raise the exception Note: In order to catch an exception, an "except" clause must refer to the same exception thrown either class object or simple string. For example to capture above exception we must write our except clause as follows: try: Business Logic here... except "Invalid level!": Exception handling here... else: Rest of the code here... User-Defined Exceptions: Python also allows you to create your own exceptions by deriving classes from the standard built-in exceptions. Here is an example related to RuntimeError. Here a class is created that is subclassed from RuntimeError. This is useful when you need to display more specific information when an exception is caught. In the try block, the user-defined exception is raised and caught in the except block. The variable e is used to create an instance of the class Networkerror. class Networkerror(RuntimeError): def __init__(self, arg): self.args = arg So once you defined above class, you can raise your exception as follows: try: raise Networkerror("Bad hostname") except Networkerror,e: print e.args 3/22/2011 5:25 PM
- 96. Python Exceptions Handling 6of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com 3/22/2011 5:25 PM
- 97. Python - ObjectOriented 1 of 9 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Object Oriented Python has been an object-oriented language from day one. Because of this, creating and using classes and objects are downright easy. This chapter helps you become an expert in using Python's objectoriented programming support. If you don't have any previous experience with object-oriented (OO) programming, you may want to consult an introductory course on it or at least a tutorial of some sort so that you have a grasp of the basic concepts. However, here is small introduction of Object-Oriented Programming (OOP) to bring you at speed: Overview of OOP Terminology Class: A user-defined prototype for an object that defines a set of attributes that characterize any object of the class. The attributes are data members (class variables and instance variables) and methods, accessed via dot notation. Class variable: A variable that is shared by all instances of a class. Class variables are defined within a class but outside any of the class's methods. Class variables aren't used as frequently as instance variables are. Data member: A class variable or instance variable that holds data associated with a class and its objects. Function overloading: The assignment of more than one behavior to a particular function. The operation performed varies by the types of objects (arguments) involved. Instance variable: A variable that is defined inside a method and belongs only to the current instance of a class. Inheritance : The transfer of the characteristics of a class to other classes that are derived from it. Instance: An individual object of a certain class. An object obj that belongs to a class Circle, for example, is an instance of the class Circle. Instantiation : The creation of an instance of a class. Method : A special kind of function that is defined in a class definition. Object : A unique instance of a data structure that's defined by its class. An object comprises both data members (class variables and instance variables) and methods. Operator overloading: The assignment of more than one function to a particular operator. Creating Classes: The class statement creates a new class definition. The name of the class immediately follows the keyword class followed by a colon as follows: class ClassName: 'Optional class documentation string' class_suite 3/22/2011 5:26 PM
- 98. Python - ObjectOriented 2 of 9 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... The class has a documentation string which can be access via ClassName.__doc__. The class_suite consists of all the component statements, defining class members, data attributes, and functions. Example: Following is the example of a simple Python class: class Employee: 'Common base class for all employees' empCount = 0 def __init__(self, name, salary): self.name = name self.salary = salary Employee.empCount += 1 def displayCount(self): print "Total Employee %d" % Employee.empCount def displayEmployee(self): print "Name : ", self.name, ", Salary: ", self.salary The variable empCount is a class variable whose value would be shared among all instances of a this class. This can be accessed as Employee.empCount from inside the class or outside the class. The first method __init__() is a special method which is called class constructor or initialization method that Python calls when you create a new instance of this class. You declare other class methods like normal functions with the exception that the first argument to each method is self. Python adds the self argument to the list for you; you don't need to include it when you call the methods. Creating instance objects: To create instances of a class, you call the class using class name and pass in whatever arguments its __init__ method accepts. "This would create first object of Employee class" emp1 = Employee("Zara", 2000) "This would create second object of Employee class" emp2 = Employee("Manni", 5000) Accessing attributes: You access the object's attributes using the dot operator with object. Class variable would be accessed using class name as follows: emp1.displayEmployee() emp2.displayEmployee() print "Total Employee %d" % Employee.empCount Now putting it all together: #!/usr/bin/python 3/22/2011 5:26 PM
- 99. Python - ObjectOriented 3 of 9 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... class Employee: 'Common base class for all employees' empCount = 0 def __init__(self, name, salary): self.name = name self.salary = salary Employee.empCount += 1 def displayCount(self): print "Total Employee %d" % Employee.empCount def displayEmployee(self): print "Name : ", self.name, ", Salary: ", self.salary "This would create first object of Employee class" emp1 = Employee("Zara", 2000) "This would create second object of Employee class" emp2 = Employee("Manni", 5000) emp1.displayEmployee() emp2.displayEmployee() print "Total Employee %d" % Employee.empCount This would produce following result: Name : Zara ,Salary: 2000 Name : Manni ,Salary: 5000 Total Employee 2 You can add, remove, or modify attributes of classes and objects at any time: emp1.age = 7 emp1.age = 8 del emp1.age # Add an 'age' attribute. # Modify 'age' attribute. # Delete 'age' attribute. Instead of using the normal statements to access attributes, you can use following functions: The getattr(obj, name[, default]) : to access the attribute of object. The hasattr(obj,name) : to check if an attribute exists or not. The setattr(obj,name,value) : to set an attribute. If attribute does not exist then it would be created. The delattr(obj, name) : to delete an attribute. hasattr(emp1, getattr(emp1, setattr(emp1, delattr(empl, 'age') # 'age') # 'age', 8) # 'age') # Returns true if 'age' attribute exists Returns value of 'age' attribute Set attribute 'age' at 8 Delete attribute 'age' Built-In Class Attributes: Every Python class keeps following built-in attributes and they can be accessed using dot operator like any other attribute: __dict__ : Dictionary containing the class's namespace. 3/22/2011 5:26 PM
- 100. Python - ObjectOriented 4 of 9 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... __doc__ : Class documentation string, or None if undefined. __name__: Class name. __module__: Module name in which the class is defined. This attribute is "__main__" in interactive mode. __bases__ : A possibly empty tuple containing the base classes, in the order of their occurrence in the base class list. For the above class let's try to access all these attributes: print print print print print "Employee.__doc__:", Employee.__doc__ "Employee.__name__:", Employee.__name__ "Employee.__module__:", Employee.__module__ "Employee.__bases__:", Employee.__bases__ "Employee.__dict__:", Employee.__dict__ This would produce following result: Employee.__doc__: Common base class for all employees Employee.__name__: Employee Employee.__module__: __main__ Employee.__bases__: () Employee.__dict__: {'__module__': '__main__', 'displayCount': <function displayCount at 0xb7c84994>, 'empCount': 2, 'displayEmployee': <function displayEmployee at 0xb7c8441c>, '__doc__': 'Common base class for all employees', '__init__': <function __init__ at 0xb7c846bc>} Destroying Objects (Garbage Collection): Python deletes unneeded objects (built-in types or class instances) automatically to free memory space. The process by which Python periodically reclaims blocks of memory that no longer are in use is termed garbage collection. Python's garbage collector runs during program execution and is triggered when an object's reference count reaches zero. An object's reference count changes as the number of aliases that point to it changes: An object's reference count increases when it's assigned a new name or placed in a container (list, tuple, or dictionary). The object's reference count decreases when it's deleted with del, its reference is reassigned, or its reference goes out of scope. When an object's reference count reaches zero, Python collects it automatically. a = 40 b = a c = [b] # Create object <40> # Increase ref. count # Increase ref. count of <40> of <40> del a b = 100 c[0] = -1 # Decrease ref. count # Decrease ref. count # Decrease ref. count of <40> of <40> of <40> You normally won't notice when the garbage collector destroys an orphaned instance and reclaims its space. But a class can implement the special method __del__(), called a destructor, that is invoked when the instance is about to be destroyed. This method might be used to clean up any nonmemory resources used by an instance. Example: 3/22/2011 5:26 PM
- 101. Python - ObjectOriented 5 of 9 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... This __del__() destructor prints the class name of an instance that is about to be destroyed: #!/usr/bin/python class Point: def __init( self, x=0, y=0): self.x = x self.y = y def __del__(self): class_name = self.__class__.__name__ print class_name, "destroyed" pt1 = Point() pt2 = pt1 pt3 = pt1 print id(pt1), id(pt2), id(pt3) # prints the ids of the obejcts del pt1 del pt2 del pt3 This would produce following result: 3083401324 3083401324 3083401324 Point destroyed Note: Ideally, you should define your classes in separate file then you should import them in your main program file using import statement. Kindly check Python - Modules chapter for more detail on importing modules and classes. Class Inheritance: Instead of starting from scratch, you can create a class by deriving it from a preexisting class by listing the parent class in parentheses after the new class name: The child class inherits the attributes of its parent class, and you can use those attributes as if they were defined in the child class. A child class can also override data members and methods from the parent. Syntax: Derived classes are declared much like their parent class; however, a list of base classes to inherit from are given after the class name: class SubClassName (ParentClass1[, ParentClass2, ...]): 'Optional class documentation string' class_suite Example: #!/usr/bin/python class Parent: # define parent class parentAttr = 100 def __init__(self): print "Calling parent constructor" def parentMethod(self): 3/22/2011 5:26 PM
- 102. Python - ObjectOriented 6 of 9 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... print 'Calling parent method' def setAttr(self, attr): Parent.parentAttr = attr def getAttr(self): print "Parent attribute :", Parent.parentAttr class Child(Parent): # define child class def __init__(self): print "Calling child constructor" def childMethod(self): print 'Calling child method' c = Child() c.childMethod() c.parentMethod() c.setAttr(200) c.getAttr() # # # # # instance of child child calls its method calls parent's method again call parent's method again call parent's method This would produce following result: Calling child constructor Calling child method Calling parent method Parent attribute : 200 Similar way you can drive a class from multiple parent classes as follows: class A: ..... # define your class A class B: ..... # define your calss B class C(A, B): ..... # subclass of A and B You can use issubclass() or isinstance() functions to check a relationships of two classes and instances: The issubclass(sub, sup) boolean function returns true if the given subclass sub is indeed a subclass of the superclass sup. The isinstance(obj, Class) boolean function returns true if obj is an instance of class Class or is an instance of a subclass of Class Overriding Methods: You can always override your parent class methods. One reason for overriding parent's methods is because you may want special or different functionality in your subclass. Example: #!/usr/bin/python class Parent: # define parent class 3/22/2011 5:26 PM
- 103. Python - ObjectOriented 7 of 9 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... def myMethod(self): print 'Calling parent method' class Child(Parent): # define child class def myMethod(self): print 'Calling child method' c = Child() c.myMethod() # instance of child # child calls overridden method This would produce following result: Calling child method Base Overloading Methods: Following table lists some generic functionality that you can override in your own classes: SN Method, Description & Sample Call 1 __init__ ( self [,args...] ) Constructor (with any optional arguments) Sample Call : obj = className(args) 2 __del__( self ) Destructor, deletes an object Sample Call : dell obj 3 __repr__( self ) Evaluatable string representation Sample Call : repr(obj) 4 __str__( self ) Printable string representation Sample Call : str(obj) 5 __cmp__ ( self, x ) Object comparison Sample Call : cmp(obj, x) Overloading Operators: Suppose you've created a Vector class to represent two-dimensional vectors. What happens when you use the plus operator to add them? Most likely Python will yell at you. You could, however, define the __add__ method in your class to perform vector addition, and then the plus operator would behave as per expectation: Example: #!/usr/bin/python class Vector: def __init__(self, a, b): self.a = a self.b = b def __str__(self): return 'Vector (%d, %d)' % (self.a, self.b) 3/22/2011 5:26 PM
- 104. Python - ObjectOriented 8 of 9 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... def __add__(self,other): return Vector(self.a + other.a, self.b + other.b) v1 = Vector(2,10) v2 = Vector(5,-2) print v1 + v2 This would produce following result: Vector(7,8) Data Hiding: An object's attributes may or may not be visible outside the class definition. For these cases, you can name attributes with a double underscore prefix, and those attributes will not be directly visible to outsiders: Example: #!/usr/bin/python class JustCounter: __secretCount = 0 def count(self): self.__secretCount += 1 print self.__secretCount counter = JustCounter() counter.count() counter.count() print counter.__secretCount This would produce following result: 1 2 Traceback (most recent call last): File "test.py", line 12, in <module> print counter.__secretCount AttributeError: JustCounter instance has no attribute '__secretCount' Python protects those members by internally changing the name to include the class name. You can access such attributes as object._className__attrName. If you would replace your last line as following, then it would work for you: ......................... print counter._JustCounter__secretCount This would produce following result: 1 3/22/2011 5:26 PM
- 105. Python - ObjectOriented 9 of 9 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... 2 2 Copyright © tutorialspoint.com 3/22/2011 5:26 PM
- 106. Python - RegularExpressions 1 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Regular Expressions A regular expression is a special sequence of characters that helps you match or find other strings or sets of strings, using a specialized syntax held in a pattern. Regular expressions are widely used in UNIX world. The module re provides full support for Perl-like regular expressions in Python. The re module raises the exception re.error if an error occurs while compiling or using a regular expression. We would cover two important functions which would be used to handle regular expressions. But a small thing first: There are various characters which would have special meaning when they are used in regular expression. To avoid any confusion while dealing with regular expressions we would use Raw Strings as r'expression'. The match Function This function attempts to match RE pattern to string with optional flags. Here is the syntax for this function: re.match(pattern, string, flags=0) Here is the description of the parameters: Parameter Description pattern This is the regular expression to be matched. string This is the string which would be searched to match the pattern flags You can specifiy different flags using exclusive OR (|). These are modifiers which are listed in the table below. The re.match function returns a match object on success, None on failure. We would use group(num) or groups() function of match object to get matched expression. Match Object Methods Description group(num=0) This methods returns entire match (or specific subgroup num) groups() This method return all matching subgroups in a tuple (empty if there weren't any) Example: #!/usr/bin/python import re line = "Cats are smarter than dogs"; matchObj = re.match( r'(.*) are(.*)', line, re.M|re.I) 3/22/2011 5:26 PM
- 107. Python - RegularExpressions 2 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... if matchObj: print "matchObj.group() : ", matchObj.group() print "matchObj.group(1) : ", matchObj.group(1) print "matchObj.group(2) : ", matchObj.group(2) else: print "No match!!" This will produce following result: matchObj.group(): Cats are matchObj.group(1) : Cats matchObj.group(2) : The search Function This function search for first occurrence of RE pattern within string with optional flags. Here is the syntax for this function: re.search(pattern, string, flags=0) Here is the description of the parameters: Parameter Description pattern This is the regular expression to be matched. string This is the string which would be searched to match the pattern flags You can specifiy different flags using exclusive OR (|). These are modifiers which are listed in the table below. The re.search function returns a match object on success, None on failure. We would use group(num) or groups() function of match object to get matched expression. Match Object Methods Description group(num=0) This methods returns entire match (or specific subgroup num) groups() This method return all matching subgroups in a tuple (empty if there weren't any) Example: #!/usr/bin/python import re line = "Cats are smarter than dogs"; matchObj = re.search( r'(.*) are(.*)', line, re.M|re.I) if matchObj: print "matchObj.group() : ", matchObj.group() print "matchObj.group(1) : ", matchObj.group(1) print "matchObj.group(2) : ", matchObj.group(2) else: print "No match!!" 3/22/2011 5:26 PM
- 108. Python - RegularExpressions 3 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... This will produce following result: matchObj.group(): Cats are matchObj.group(1) : Cats matchObj.group(2) : Matching vs Searching: Python offers two different primitive operations based on regular expressions: match checks for a match only at the beginning of the string, while search checks for a match anywhere in the string (this is what Perl does by default). Example: #!/usr/bin/python import re line = "Cats are smarter than dogs"; matchObj = re.match( r'dogs', line, re.M|re.I) if matchObj: print "match --> matchObj.group() : ", matchObj.group() else: print "No match!!" matchObj = re.search( r'dogs', line, re.M|re.I) if matchObj: print "search --> matchObj.group() : ", matchObj.group() else: print "No match!!" This will produce following result: No match!! search --> matchObj.group() : dogs Search and Replace: Some of the most important re methods that use regular expressions is sub. Syntax: re.sub(pattern, repl, string, max=0) This method replace all occurrences of the RE pattern in string with repl, substituting all occurrences unless max provided. This method would return modified string. Example: Following is the example: #!/usr/bin/python phone = "2004-959-559 #This is Phone Number" 3/22/2011 5:26 PM
- 109. Python - RegularExpressions 4 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... # Delete Python-style comments num = re.sub(r'#.*$', "", phone) print "Phone Num : ", num # Remove anything other than digits num = re.sub(r'D', "", phone) print "Phone Num : ", num This will produce following result: Phone Num : Phone Num : 2004-959-559 2004959559 Regular-expression Modifiers - Option Flags Regular expression literals may include an optional modifier to control various aspects of matching. The modifier are specified as an optional flag. You can provide multiple modified using exclusive OR (|), as shown previously and may be represented by one of these: Modifier Description re.I Performs case-insensitive matching. re.L Interprets words according to the current locale.This interpretation affects the alphabetic group (w and W), as well as word boundary behavior (b and B). re.M Makes $ match the end of a line (not just the end of the string) and makes ^ match the start of any line (not just the start of the string). re.S Makes a period (dot) match any character, including a newline. re.U Interprets letters according to the Unicode character set. This flag affects the behavior of w, W, b, B. re.X Permits "cuter" regular expression syntax. It ignores whitespace (except inside a set [] or when escaped by a backslash), and treats unescaped # as a comment marker. Regular-expression patterns: Except for control characters, (+ ? . * ^ $ ( ) [ ] { } | ), all characters match themselves. You can escape a control character by preceding it with a backslash. Following table lists the regular expression syntax that is available in Python. Pattern Description ^ Matches beginning of line. $ Matches end of line. . Matches any single character except newline. Using m option allows it to match newline as well. [...] Matches any single character in brackets. [^...] Matches any single character not in brackets re* Matches 0 or more occurrences of preceding expression. 3/22/2011 5:26 PM
- 110. Python - RegularExpressions 5 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... re+ Matches 1 or more occurrence of preceding expression. re? Matches 0 or 1 occurrence of preceding expression. re{ n} Matches exactly n number of occurrences of preceding expression. re{ n,} Matches n or more occurrences of preceding expression. re{ n, m} Matches at least n and at most m occurrences of preceding expression. a| b Matches either a or b. (re) Groups regular expressions and remembers matched text. (?imx) Temporarily toggles on i, m, or x options within a regular expression. If in parentheses, only that area is affected. (?-imx) Temporarily toggles off i, m, or x options within a regular expression. If in parentheses, only that area is affected. (?: re) Groups regular expressions without remembering matched text. (?imx: re) Temporarily toggles on i, m, or x options within parentheses. (?-imx: re) Temporarily toggles off i, m, or x options within parentheses. (?#...) Comment. (?= re) Specifies position using a pattern. Doesn't have a range. (?! re) Specifies position using pattern negation. Doesn't have a range. (?> re) Matches independent pattern without backtracking. w Matches word characters. W Matches nonword characters. s Matches whitespace. Equivalent to [tnrf]. S Matches nonwhitespace. d Matches digits. Equivalent to [0-9]. D Matches nondigits. A Matches beginning of string. Z Matches end of string. If a newline exists, it matches just before newline. z Matches end of string. G Matches point where last match finished. b Matches word boundaries when outside brackets. Matches backspace (0x08) when inside brackets. B Matches nonword boundaries. n, t, etc. Matches newlines, carriage returns, tabs, etc. 1...9 Matches nth grouped subexpression. 10 Matches nth grouped subexpression if it matched already. Otherwise refers to the octal representation of a character code. Regular-expression Examples: Literal characters: 3/22/2011 5:26 PM
- 111. Python - RegularExpressions 6 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Example python Description Match "python". Character classes: Example Description [Pp]ython Match "Python" or "python" rub[ye] Match "ruby" or "rube" [aeiou] Match any one lowercase vowel [0-9] Match any digit; same as [0123456789] [a-z] Match any lowercase ASCII letter [A-Z] Match any uppercase ASCII letter [a-zA-Z0-9] Match any of the above [^aeiou] Match anything other than a lowercase vowel [^0-9] Match anything other than a digit Special Character Classes: Example Description . Match any character except newline d Match a digit: [0-9] D Match a nondigit: [^0-9] s Match a whitespace character: [ trnf] S Match nonwhitespace: [^ trnf] w Match a single word character: [A-Za-z0-9_] W Match a nonword character: [^A-Za-z0-9_] Repetition Cases: Example Description ruby? Match "rub" or "ruby": the y is optional ruby* Match "rub" plus 0 or more ys ruby+ Match "rub" plus 1 or more ys d{3} Match exactly 3 digits d{3,} Match 3 or more digits d{3,5} Match 3, 4, or 5 digits Nongreedy repetition: This matches the smallest number of repetitions: Example <.*> Description Greedy repetition: matches "<python>perl>" 3/22/2011 5:26 PM
- 112. Python - RegularExpressions 7 of 8 <.*?> http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Nongreedy: matches "<python>" in "<python>perl>" Grouping with parentheses: Example Description Dd+ No group: + repeats d (Dd)+ Grouped: + repeats Dd pair ([Pp]ython(, )?)+ Match "Python", "Python, python, python", etc. Backreferences: This matches a previously matched group again: Example Description ([Pp])ython&1ails Match python&rails or Python&Rails (['"])[^1]*1 Single or double-quoted string. 1 matches whatever the 1st group matched . 2 matches whatever the 2nd group matched, etc. Alternatives: Example Description python|perl Match "python" or "perl" rub(y|le)) Match "ruby" or "ruble" Python(!+|?) "Python" followed by one or more ! or one ? Anchors: This need to specify match position Example Description ^Python Match "Python" at the start of a string or internal line Python$ Match "Python" at the end of a string or line APython Match "Python" at the start of a string PythonZ Match "Python" at the end of a string bPythonb Match "Python" at a word boundary brubB B is nonword boundary: match "rub" in "rube" and "ruby" but not alone Python(?=!) Match "Python", if followed by an exclamation point Python(?!!) Match "Python", if not followed by an exclamation point Special syntax with parentheses: Example Description R(?#comment) Matches "R". All the rest is a comment R(?i)uby Case-insensitive while matching "uby" R(?i:uby) Same as above 3/22/2011 5:26 PM
- 113. Python - RegularExpressions 8 of 8 rub(?:y|le)) http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Group only without creating 1 backreference Copyright © tutorialspoint.com 3/22/2011 5:26 PM
- 114. Python - CGIProgramming 1 of 12 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - CGI Programming What is CGI ? The Common Gateway Interface, or CGI, is a set of standards that define how information is exchanged between the web server and a custom script. The CGI specs are currently maintained by the NCSA and NCSA defines CGI is as follows: The Common Gateway Interface, or CGI, is a standard for external gateway programs to interface with information servers such as HTTP servers. The current version is CGI/1.1 and CGI/1.2 is under progress. Web Browsing To understand the concept of CGI, lets see what happens when we click a hyper link to browse a particular web page or URL. Your browser contacts the HTTP web server and demand for the URL ie. filename. Web Server will parse the URL and will look for the filename in if it finds that file then sends back to the browser otherwise sends an error message indicating that you have requested a wrong file. Web browser takes response from web server and displays either the received file or error message. However, it is possible to set up the HTTP server so that whenever a file in a certain directory is requested that file is not sent back; instead it is executed as a program, and whatever that program outputs is sent back for your browser to display. This function is called the Common Gateway Interface or CGI and the programs are called CGI scripts. These CGI programs can be a Python Script, PERL Script, Shell Script, C or C++ program etc. CGI Architecture Diagram Web Server Support & Configuration Before you proceed with CGI Programming, make sure that your Web Server supports CGI and it is configured to handle CGI Programs. All the CGI Programs to be executed by the HTTP server are kept in a pre-configured directory. This directory is called CGI Directory and by convention it is named as /var/www/cgi-bin. By convention CGI files will have extention as .cgi but you can keep your files with python extension .py as well. 3/22/2011 5:26 PM
- 115. Python - CGIProgramming 2 of 12 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... By default, the Linux server is configured to run only the scripts in the cgi-bin directory in /var/www. If you want to specify any other directory to run your CGI scripts, comment the following lines in the httpd.conf file: <Directory "/var/www/cgi-bin"> AllowOverride None Options ExecCGI Order allow,deny Allow from all </Directory> <Directory "/var/www/cgi-bin"> Options All </Directory> Here I assumed that you have Web Server up and running successfully and you are able to run any other CGI program like Perl or Sheel etc. First CGI Program Here is a simple link which is linked to a CGI script called hello.py. This file is being kept in /var/www /cgi-bin directory and it has following content. Before running your CGI program make sure you have chage mode of file using chmod 755 hello.py UNIX command to make file executable. #!/usr/bin/python print print print print print print print print print "Content-type:text/htmlrnrn" '<html>' '<head>' '<title>Hello Word - First CGI Program</title>' '</head>' '<body>' '<h2>Hello Word! This is my first CGI program</h2>' '</body>' '</html>' If you click hello.py then this produces following output: Hello Word! This is my first CGI program This hello.py script is a simple Python script which is writing its output on STDOUT file ie. screen. There is one important and extra feature available which is first line to be printed Content-type:text/htmlr nrn. This line is sent back to the browser and specifiy the content type to be displayed on the browser screen. Now you must have understood basic concept of CGI and you can write many complicated CGI programs using Python. This script can interact with any other exertnal system also to exchange information such as RDBMS. HTTP Header The line Content-type:text/htmlrnrn is part of HTTP header which is sent to the browser to understand the content. All the HTTP header will be in the following form HTTP Field Name: Field Content For Example Content-type: text/htmlrnrn 3/22/2011 5:26 PM
- 116. Python - CGIProgramming 3 of 12 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... There are few other important HTTP headers which you will use frequently in your CGI Programming. Header Description Content-type: A MIME string defining the format of the file being returned. Example is Contenttype:text/html Expires: Date The date the information becomes invalid. This should be used by the browser to decide when a page needs to be refreshed. A valid date string should be in the format 01 Jan 1998 12:00:00 GMT. Location: URL The URL that should be returned instead of the URL requested. You can use this filed to redirect a request to any file. Last-modified: Date The date of last modification of the resource. Content-length: N The length, in bytes, of the data being returned. The browser uses this value to report the estimated download time for a file. Set-Cookie: String Set the cookie passed through the string CGI Environment Variables All the CGI program will have access to the following environment variables. These variables play an important role while writing any CGI program. Variable Name Description CONTENT_TYPE The data type of the content. Used when the client is sending attached content to the server. For example file upload etc. CONTENT_LENGTH The length of the query information. It's available only for POST requests HTTP_COOKIE Return the set cookies in the form of key & value pair. HTTP_USER_AGENT The User-Agent request-header field contains information about the user agent originating the request. Its name of the web browser. PATH_INFO The path for the CGI script. QUERY_STRING The URL-encoded information that is sent with GET method request. REMOTE_ADDR The IP address of the remote host making the request. This can be useful for logging or for authentication purpose. REMOTE_HOST The fully qualified name of the host making the request. If this information is not available then REMOTE_ADDR can be used to get IR address. REQUEST_METHOD The method used to make the request. The most common methods are GET and POST. SCRIPT_FILENAME The full path to the CGI script. SCRIPT_NAME The name of the CGI script. SERVER_NAME The server's hostname or IP Address SERVER_SOFTWARE The name and version of the software the server is running. Here is small CGI program to list out all the CGI variables. Click this link to see the result Get Environment 3/22/2011 5:26 PM
- 117. Python - CGIProgramming 4 of 12 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... #!/usr/bin/python import os print "Content-type: text/htmlrnrn"; print "<font size=+1>Environment</font><br>"; for param in os.environ.keys(): print "<b>%20s</b>: %s<br>" % (param,os.environ[param]) GET and POST Methods You must have come across many situations when you need to pass some information from your browser to web server and ultimately to your CGI Program. Most frequently browser uses two methods two pass this information to web server. These methods are GET Method and POST Method. Passing Information using GET method: The GET method sends the encoded user information appended to the page request. The page and the encoded information are separated by the ? character as follows: http://www.test.com/cgi-bin/hello.py?key1=value1&key2=value2 The GET method is the defualt method to pass information from browser to web server and it produces a long string that appears in your browser's Location:box. Never use the GET method if you have password or other sensitive information to pass to the server. The GET method has size limtation: only 1024 characters can be in a request string. This information is passed using QUERY_STRING header and will be accessible in your CGI Program through QUERY_STRING environment variable You can pass information by simply concatenating key and value pairs alongwith any URL or you can use HTML <FORM> tags to pass information using GET method. Simple URL Example : Get Method Here is a simple URL which will pass two values to hello_get.py program using GET method. /cgi-bin/hello_get.py?first_name=ZARA&last_name=ALI Below is hello_get.py script to handle input given by web browser. We are going to use cgi module which makes it very easy to access passed information: #!/usr/bin/python # Import modules for CGI handling import cgi, cgitb # Create instance of FieldStorage form = cgi.FieldStorage() # Get data from fields first_name = form.getvalue('first_name') last_name = form.getvalue('last_name') print print print print "Content-type:text/htmlrnrn" "<html>" "<head>" "<title>Hello - Second CGI Program</title>" 3/22/2011 5:26 PM
- 118. Python - CGIProgramming 5 of 12 print print print print print http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... "</head>" "<body>" "<h2>Hello %s %s</h2>" % (first_name, last_name) "</body>" "</html>" This would generate following result: Hello ZARA ALI Simple FORM Example: GET Method Here is a simple example which passes two values using HTML FORM and submit button. We are going to use same CGI script hello_get.py to handle this imput. <form action="/cgi-bin/hello_get.py" method="get"> First Name: <input type="text" name="first_name"> <br /> Last Name: <input type="text" name="last_name" /> <input type="submit" value="Submit" /> </form> Here is the actual output of the above form, You enter First and Last Name and then click submit button to see the result. First Name: Last Name: Passing Information using POST method: A generally more reliable method of passing information to a CGI program is the POST method. This packages the information in exactly the same way as GET methods, but instead of sending it as a text string after a ? in the URL it sends it as a separate message. This message comes into the CGI script in the form of the standard input. Below is same hello_get.py script which handles GET as well as POST method. #!/usr/bin/python # Import modules for CGI handling import cgi, cgitb # Create instance of FieldStorage form = cgi.FieldStorage() # Get data from fields first_name = form.getvalue('first_name') last_name = form.getvalue('last_name') print print print print print print "Content-type:text/htmlrnrn" "<html>" "<head>" "<title>Hello - Second CGI Program</title>" "</head>" "<body>" 3/22/2011 5:26 PM
- 119. Python - CGIProgramming 6 of 12 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... print "<h2>Hello %s %s</h2>" % (first_name, last_name) print "</body>" print "</html>" Let us take again same examle as above, which passes two values using HTML FORM and submit button. We are going to use same CGI script hello_get.py to handle this imput. <form action="/cgi-bin/hello_get.py" method="post"> First Name: <input type="text" name="first_name"><br /> Last Name: <input type="text" name="last_name" /> <input type="submit" value="Submit" /> </form> Here is the actual output of the above form, You enter First and Last Name and then click submit button to see the result. First Name: Last Name: Passing Checkbox Data to CGI Program Checkboxes are used when more than one option is required to be selected. Here is example HTML code for a form with two checkboxes <form action="/cgi-bin/checkbox.cgi" method="POST" target="_blank"> <input type="checkbox" name="maths" value="on" /> Maths <input type="checkbox" name="physics" value="on" /> Physics <input type="submit" value="Select Subject" /> </form> The result of this code is the following form Maths Physics Below is checkbox.cgi script to handle input given by web browser for checkbox button. #!/usr/bin/python # Import modules for CGI handling import cgi, cgitb # Create instance of FieldStorage form = cgi.FieldStorage() # Get data from fields if form.getvalue('maths'): math_flag = "ON" else: math_flag = "OFF" if form.getvalue('physics'): physics_flag = "ON" else: 3/22/2011 5:26 PM
- 120. Python - CGIProgramming 7 of 12 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... physics_flag = "OFF" print print print print print print print print print print "Content-type:text/htmlrnrn" "<html>" "<head>" "<title>Checkbox - Third CGI Program</title>" "</head>" "<body>" "<h2> CheckBox Maths is : %s</h2>" % math_flag "<h2> CheckBox Physics is : %s</h2>" % physics_flag "</body>" "</html>" Passing Radio Button Data to CGI Program Radio Buttons are used when only one option is required to be selected. Here is example HTML code for a form with two radio button: <form action="/cgi-bin/radiobutton.py" method="post" target="_blank"> <input type="radio" name="subject" value="maths" /> Maths <input type="radio" name="subject" value="physics" /> Physics <input type="submit" value="Select Subject" /> </form> The result of this code is the following form Maths Physics Below is radiobutton.py script to handle input given by web browser for radio button. #!/usr/bin/python # Import modules for CGI handling import cgi, cgitb # Create instance of FieldStorage form = cgi.FieldStorage() # Get data from fields if form.getvalue('subject'): subject = form.getvalue('subject') else: subject = "Not set" print print print print print print print print print "Content-type:text/htmlrnrn" "<html>" "<head>" "<title>Radio - Fourth CGI Program</title>" "</head>" "<body>" "<h2> Selected Subject is %s</h2>" % subject "</body>" "</html>" Passing Text Area Data to CGI Program TEXTAREA element is used when multiline text has to be passed to the CGI Program. 3/22/2011 5:26 PM
- 121. Python - CGIProgramming 8 of 12 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Here is example HTML code for a form with a TEXTAREA box: <form action="/cgi-bin/textarea.py" method="post" target="_blank"> <textarea name="textcontent" cols="40" rows="4"> Type your text here... </textarea> <input type="submit" value="Submit" /> </form> The result of this code is the following form Below is textarea.cgi script to handle input given by web browser. #!/usr/bin/python # Import modules for CGI handling import cgi, cgitb # Create instance of FieldStorage form = cgi.FieldStorage() # Get data from fields if form.getvalue('textcontent'): text_content = form.getvalue('textcontent') else: text_content = "Not entered" print print print print print print print print "Content-type:text/htmlrnrn" "<html>" "<head>"; "<title>Text Area - Fifth CGI Program</title>" "</head>" "<body>" "<h2> Entered Text Content is %s</h2>" % text_content "</body>" Passing Drop Down Box Data to CGI Program Drop Down Box is used when we have many options available but only one or two will be selected. Here is example HTML code for a form with one drop down box <form action="/cgi-bin/dropdown.py" method="post" target="_blank"> <select name="dropdown"> <option value="Maths" selected>Maths</option> <option value="Physics">Physics</option> </select> <input type="submit" value="Submit"/> </form> The result of this code is the following form 3/22/2011 5:26 PM
- 122. Python - CGIProgramming 9 of 12 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Below is dropdown.py script to handle input given by web browser. #!/usr/bin/python # Import modules for CGI handling import cgi, cgitb # Create instance of FieldStorage form = cgi.FieldStorage() # Get data from fields if form.getvalue('dropdown'): subject = form.getvalue('dropdown') else: subject = "Not entered" print print print print print print print print print "Content-type:text/htmlrnrn" "<html>" "<head>" "<title>Dropdown Box - Sixth CGI Program</title>" "</head>" "<body>" "<h2> Selected Subject is %s</h2>" % subject "</body>" "</html>" Using Cookies in CGI HTTP protocol is a stateless protocol. But for a commercial website it is required to maintain session information among different pages. For example one user registration ends after completing many pages. But how to maintain user's session information across all the web pages. In many situations, using cookies is the most efficient method of remembering and tracking preferences, purchases, commissions, and other information required for better visitor experience or site statistics. How It Works Your server sends some data to the visitor's browser in the form of a cookie. The browser may accept the cookie. If it does, it is stored as a plain text record on the visitor's hard drive. Now, when the visitor arrives at another page on your site, the cookie is available for retrieval. Once retrieved, your server knows/remembers what was stored. Cookies are a plain text data record of 5 variable-length fields: Expires : The date the cookie will expire. If this is blank, the cookie will expire when the visitor quits the browser. Domain : The domain name of your site. Path : The path to the directory or web page that set the cookie. This may be blank if you want to retrieve the cookie from any directory or page. Secure : If this field contains the word "secure" then the cookie may only be retrieved with a secure server. If this field is blank, no such restriction exists. Name=Value : Cookies are set and retrviewed in the form of key and value pairs. Setting up Cookies 3/22/2011 5:26 PM
- 123. Python - CGIProgramming 10 of 12 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... This is very easy to send cookies to browser. These cookies will be sent along with HTTP Header before to Content-type filed. Assuming you want to set UserID and Password as cookies. So cookies setting will be done as follows #!/usr/bin/python print "Set-Cookie:UserID=XYZ;rn" print "Set-Cookie:Password=XYZ123;rn" print "Set-Cookie:Expires=Tuesday, 31-Dec-2007 23:12:40 GMT";rn" print "Set-Cookie:Domain=www.tutorialspoint.com;rn" print "Set-Cookie:Path=/perl;n" print "Content-type:text/htmlrnrn" ...........Rest of the HTML Content.... From this example you must have understood how to set cookies. We use Set-Cookie HTTP header to set cookies. Here it is optional to set cookies attributes like Expires, Domain, and Path. It is notable that cookies are set before sending magic line "Content-type:text/htmlrnrn. Retrieving Cookies This is very easy to retrieve all the set cookies. Cookies are stored in CGI environment variable HTTP_COOKIE and they will have following form. key1=value1;key2=value2;key3=value3.... Here is an example of how to retrieving cookies. #!/usr/bin/python # Import modules for CGI handling from os import environ import cgi, cgitb if environ.has_key('HTTP_COOKIE'): for cookie in map(strip, split(environ['HTTP_COOKIE'], ';')): (key, value ) = split(cookie, '='); if key == "UserID": user_id = value if key == "Password": password = value print "User ID = %s" % user_id print "Password = %s" % password This will produce following result for the cookies set by above script: User ID = XYZ Password = XYZ123 File Upload Example: To upload a file the HTML form must have the enctype attribute set to multipart/form-data. The input tag with the file type will create a "Browse" button. 3/22/2011 5:26 PM
- 124. Python - CGIProgramming 11 of 12 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... <html> <body> <form enctype="multipart/form-data" action="save_file.py" method="post"> <p>File: <input type="file" name="filename" /></p> <p><input type="submit" value="Upload" /></p> </form> </body> </html> The result of this code is the following form: File: Note: Above example has been disabled intentionally to save people uploading file on our server. But you can try above code with your server. Here is the script save_file.py to handle file upload: #!/usr/bin/python import cgi, os import cgitb; cgitb.enable() form = cgi.FieldStorage() # Get filename here. fileitem = form['filename'] # Test if the file was uploaded if fileitem.filename: # strip leading path from file name to avoid # directory traversal attacks fn = os.path.basename(fileitem.filename) open('/tmp/' + fn, 'wb').write(fileitem.file.read()) message = 'The file "' + fn + '" was uploaded successfully' else: message = 'No file was uploaded' print """ Content-Type: text/htmln <html> <body> <p>%s</p> </body> </html> """ % (message,) Note: If you are running above script on Unix/Linux then you would have to take care of replacing file separator as follows, otherwise on your windows machine above open() statement should work fine. fn = os.path.basename(fileitem.filename.replace("", "/" )) 3/22/2011 5:26 PM
- 125. Python - CGIProgramming 12 of 12 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... How To Raise a "File Download" Dialog Box ? Sometime it is desired that you want to give option where a user will click a link and it will pop up a "File Download" dialogue box to the user instead of displaying actual content. This is very easy and will be achived through HTTP header. This HTTP header will be different from the header mentioned in previous section. For example,if you want make a FileName file downloadable from a given link then its syntax will be as follows. #!/usr/bin/python # HTTP Header print "Content-Type:application/octet-stream; name="FileName"rn"; print "Content-Disposition: attachment; filename="FileName"rnn"; # Actual File Content will go hear. fo = open("foo.txt", "rb") str = fo.read(); print str # Close opend file fo.close() Hope you enjoyed this tutorial. If yes, please send me your feedback at: Contact Us Copyright © tutorialspoint.com 3/22/2011 5:26 PM
- 126. Python - MySQLDatabase Access 1 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - MySQL Database Access The Python standard for database interfaces is the Python DB-API. Most Python database interfaces adhere to this standard. You can choose the right database for your application. Python Database API supports a wide range of database servers: GadFly mSQL MySQL PostgreSQL Microsoft SQL Server 2000 Informix Interbase Oracle Sybase Here is the list of available Python databases interfaces: Python Database Interfaces and APIs You must download a separate DB API module for each database you need to access. For example, if you need to access an Oracle database as well as a MySQL database, you must download both the Oracle and the MySQL database modules. The DB API provides a minimal standard for working with databases, using Python structures and syntax wherever possible. This API includes the following: Importing the api module. Acquiring a connection with the database. Issuing SQL statements and stored procedures. Closing the connection We would learn all the concepts using MySQL so let's talk about MySQLdb module only. What is MySQLdb? MySQLdb is an interface for connecting to a MySQL database server from Python. It implements the Python Database API v2.0, and is built on top of the MySQL C API. How do I install the MySQLdb? Before proceeding you make sure you have MySQLdb installed on your machine. Just type the following in your Python script and execute it: #!/usr/bin/python import MySQLdb 3/22/2011 5:27 PM
- 127. Python - MySQLDatabase Access 2 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... If it produces following result then it means MySQLdb module is not installed: Traceback (most recent call last): File "test.py", line 3, in <module> import MySQLdb ImportError: No module named MySQLdb To install MySQLdb module, download it from MySQLdb Download page and proceed as follows: $ $ $ $ $ gunzip MySQL-python-1.2.2.tar.gz tar -xvf MySQL-python-1.2.2.tar cd MySQL-python-1.2.2 python setup.py build python setup.py install Note: Make sure you have root privilege to install above module. Database Connection: Before connecting to a MySQL database make sure followings: You have created a database TESTDB. You have created a table EMPLOYEE in TESTDB. This table is having fields FIRST_NAME, LAST_NAME, AGE, SEX and INCOME. User ID "testuser" and password "test123" are set to access TESTDB Python module MySQLdb is installed properly on your machine. You have gone through MySQL tutorial to understand MySQL Basics. Example: Following is the example of connecting with MySQL database "TESTDB" #!/usr/bin/python import MySQLdb # Open database connection db = MySQLdb.connect("localhost","testuser","test123","TESTDB" ) # prepare a cursor object using cursor() method cursor = db.cursor() # execute SQL query using execute() method. cursor.execute("SELECT VERSION()") # Fetch a single row using fetchone() method. data = cursor.fetchone() print "Database version : %s " % data # disconnect from server db.close() While running this script, its producing following result at my Linux machine. 3/22/2011 5:27 PM
- 128. Python - MySQLDatabase Access 3 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Database version : 5.0.45 If a connection is established with the datasource then a Connection Object is returned and saved into db for further use otherwise db is set to None. Next db object is used to create a cursor object which in turn is used to execute SQL queries. Finally before coming out it ensures that database connection is closed and resources are released. Creating Database Table: Once a database connection is established, we are ready to create tables or records into the database tables using execute method of the created cursor. Example: First let's create Database table EMPLOYEE: #!/usr/bin/python import MySQLdb # Open database connection db = MySQLdb.connect("localhost","testuser","test123","TESTDB" ) # prepare a cursor object using cursor() method cursor = db.cursor() # Drop table if it already exist using execute() method. cursor.execute("DROP TABLE IF EXISTS EMPLOYEE") # Create table as per requirement sql = """CREATE TABLE EMPLOYEE ( FIRST_NAME CHAR(20) NOT NULL, LAST_NAME CHAR(20), AGE INT, SEX CHAR(1), INCOME FLOAT )""" cursor.execute(sql) # disconnect from server db.close() INSERT Operation: INSERT operation is required when you want to create your records into a database table. Example: Following is the example which executes SQL INSERT statement to create a record into EMPLOYEE table. #!/usr/bin/python import MySQLdb # Open database connection db = MySQLdb.connect("localhost","testuser","test123","TESTDB" ) 3/22/2011 5:27 PM
- 129. Python - MySQLDatabase Access 4 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... # prepare a cursor object using cursor() method cursor = db.cursor() # Prepare SQL query to INSERT a record into the database. sql = """INSERT INTO EMPLOYEE(FIRST_NAME, LAST_NAME, AGE, SEX, INCOME) VALUES ('Mac', 'Mohan', 20, 'M', 2000)""" try: # Execute the SQL command cursor.execute(sql) # Commit your changes in the database db.commit() except: # Rollback in case there is any error db.rollback() # disconnect from server db.close() Above example can be written as follows to create SQL queries dynamically: #!/usr/bin/python import MySQLdb # Open database connection db = MySQLdb.connect("localhost","testuser","test123","TESTDB" ) # prepare a cursor object using cursor() method cursor = db.cursor() # Prepare SQL query to INSERT a record into the database. sql = "INSERT INTO EMPLOYEE(FIRST_NAME, LAST_NAME, AGE, SEX, INCOME) VALUES ('%s', '%s', '%d', '%c', '%d' )" % ('Mac', 'Mohan', 20, 'M', 2000) try: # Execute the SQL command cursor.execute(sql) # Commit your changes in the database db.commit() except: # Rollback in case there is any error db.rollback() # disconnect from server db.close() Example: Following code segment is another form of execute where you can pass parameters directly: .................................. user_id = "test123" password = "password" con.execute('insert into Login values("%s", "%s")' % (user_id, password)) 3/22/2011 5:27 PM
- 130. Python - MySQLDatabase Access 5 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... .................................. READ Operation: READ Operation on any databasse means to fetch some useful information from the database. Once our database connection is established, we are ready to make a query into this database. We can use either fetchone() method to fetch single record or fetchall method to fetech multiple values from a database table. fetchone(): This method fetches the next row of a query result set. A result set is an object that is returned when a cursor object is used to query a table. fetchall(): This method fetches all the rows in a result set. If some rows have already been extracted from the result set, the fetchall() method retrieves the remaining rows from the result set. rowcount: This is a read-only attribute and returns the number of rows that were affected by an execute() method. Example: Following is the procedure to query all the records from EMPLOYEE table having salary more than 1000. #!/usr/bin/python import MySQLdb # Open database connection db = MySQLdb.connect("localhost","testuser","test123","TESTDB" ) # prepare a cursor object using cursor() method cursor = db.cursor() # Prepare SQL query to INSERT a record into the database. sql = "SELECT * FROM EMPLOYEE WHERE INCOME > '%d'" % (1000) try: # Execute the SQL command cursor.execute(sql) # Fetch all the rows in a list of lists. results = cursor.fetchall() for row in results: fname = row[0] lname = row[1] age = row[2] sex = row[3] income = row[4] # Now print fetched result print "fname=%s,lname=%s,age=%d,sex=%s,income=%d" % (fname, lname, age, sex, income ) except: print "Error: unable to fecth data" # disconnect from server db.close() This will produce following result: fname=Mac, lname=Mohan, age=20, sex=M, income=2000 3/22/2011 5:27 PM
- 131. Python - MySQLDatabase Access 6 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Update Operation: UPDATE Operation on any databasse means to update one or more records which are already available in the database. Following is the procedure to update all the records having SEX as 'M'. Here we will increase AGE of all the males by one year. Example: #!/usr/bin/python import MySQLdb # Open database connection db = MySQLdb.connect("localhost","testuser","test123","TESTDB" ) # prepare a cursor object using cursor() method cursor = db.cursor() # Prepare SQL query to UPDATE required records sql = "UPDATE EMPLOYEE SET AGE = AGE + 1 WHERE SEX = '%c'" % ('M') try: # Execute the SQL command cursor.execute(sql) # Commit your changes in the database db.commit() except: # Rollback in case there is any error db.rollback() # disconnect from server db.close() DELETE Operation: DELETE operation is required when you want to delete some records from your database. Following is the procedure to delete all the records from EMPLOYEE where AGE is more than 20. Example: #!/usr/bin/python import MySQLdb # Open database connection db = MySQLdb.connect("localhost","testuser","test123","TESTDB" ) # prepare a cursor object using cursor() method cursor = db.cursor() # Prepare SQL query to DELETE required records sql = "DELETE FROM EMPLOYEE WHERE AGE > '%d'" % (20) try: # Execute the SQL command cursor.execute(sql) # Commit your changes in the database db.commit() except: 3/22/2011 5:27 PM
- 132. Python - MySQLDatabase Access 7 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... # Rollback in case there is any error db.rollback() # disconnect from server db.close() Performing Transactions: Transactions are a mechanism that ensures data consistency. Transactions should have the following four properties: Atomicity: Either a transaction completes or nothing happens at all. Consistency: A transaction must start in a consistent state and leave the system is a consistent state. Isolation: Intermediate results of a transaction are not visible outside the current transaction. Durability: Once a transaction was committed, the effects are persistent, even after a system failure. The Python DB API 2.0 provides two methods to either commit or rollback a transaction. Example: You already have seen how we have implemented transations. Here is again similar example: # Prepare SQL query to DELETE required records sql = "DELETE FROM EMPLOYEE WHERE AGE > '%d'" % (20) try: # Execute the SQL command cursor.execute(sql) # Commit your changes in the database db.commit() except: # Rollback in case there is any error db.rollback() COMMIT Operation: Commit is the operation which gives a green signal to database to finalize the changes and after this operation no change can be reverted back. Here is a simple example to call commit method. db.commit() ROLLBACK Operation: If you are not satisfied with one or more of the changes and you want to revert back those changes completely then use rollback method. Here is a simple example to call rollback metho. db.rollback() 3/22/2011 5:27 PM
- 133. Python - MySQLDatabase Access 8 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Disconnecting Database: To disconnect Database connection, use close() method. db.close() If the connection to a database is closed by the user with the close() method, any outstanding transactions are rolled back by the DB. However, instead of depending on any of DB lower level implementation details, your application would be better off calling commit or rollback explicitly. Handling Errors: There are many sources of errors. A few examples are a syntax error in an executed SQL statement, a connection failure, or calling the fetch method for an already canceled or finished statement handle. The DB API defines a number of errors that must exist in each database module. The following table lists these exceptions. Exception Description Warning Used for non-fatal issues. Must subclass StandardError. Error Base class for errors. Must subclass StandardError. InterfaceError Used for errors in the database module, not the database itself. Must subclass Error. DatabaseError Used for errors in the database. Must subclass Error. DataError Subclass of DatabaseError that refers to errors in the data. OperationalError Subclass of DatabaseError that refers to errors such as the loss of a connection to the database. These errors are generally outside of the control of the Python scripter. IntegrityError Subclass of DatabaseError for situations that would damage the relational integrity, such as uniqueness constraints or foreign keys. InternalError Subclass of DatabaseError that refers to errors internal to the database module, such as a cursor no longer being active. ProgrammingError Subclass of DatabaseError that refers to errors such as a bad table name and other things that can safely be blamed on you. NotSupportedError Subclass of DatabaseError that refers to trying to call unsupported functionality. Your Python scripts should handle these errors but before using any of the above exceptions, make sure your MySQLdb has support for that exception. You can get more information about them by reading the DB API 2.0 specification. Copyright © tutorialspoint.com 3/22/2011 5:27 PM
- 134. Python - NetworkProgramming 1 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Network Programming Python provides two levels of access to network services. At a low level, you can access the basic socket support in the underlying operating system, which allows you to implement clients and servers for both connection-oriented and connectionless protocols. Python also has libraries that provide higher-level access to specific application-level network protocols, such as FTP, HTTP, and so on. This tutorial gives you understanding on most famous concept in Networking - Socket Programming What is Sockets? Sockets are the endpoints of a bidirectional communications channel. Sockets may communicate within a process, between processes on the same machine, or between processes on different continents. Sockets may be implemented over a number of different channel types: Unix domain sockets, TCP, UDP, and so on. The socket library provides specific classes for handling the common transports as well as a generic interface for handling the rest. Sockets have their own vocabulary: Term Description domain The family of protocols that will be used as the transport mechanism. These values are constants such as AF_INET, PF_INET, PF_UNIX, PF_X25, and so on. type The type of communications between the two endpoints, typically SOCK_STREAM for connection-oriented protocols and SOCK_DGRAM for connectionless protocols. protocol Typically zero, this may be used to identify a variant of a protocol within a domain and type. The identifier of a network interface: hostname port A string, which can be a host name, a dotted-quad address, or an IPV6 address in colon (and possibly dot) notation A string "<broadcast>", which specifies an INADDR_BROADCAST address. A zero-length string, which specifies INADDR_ANY, or An Integer, interpreted as a binary address in host byte order. Each server listens for clients calling on one or more ports. A port may be a Fixnum port number, a string containing a port number, or the name of a service. The socket Module: To create a socket, you must use the socket.socket() function available in socket module, which has the general syntax: s = socket.socket (socket_family, socket_type, protocol=0) Here is the description of the parameters: socket_family: This is either AF_UNIX or AF_INET, as explained earlier. 3/22/2011 5:27 PM
- 135. Python - NetworkProgramming 2 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... socket_type: This is either SOCK_STREAM or SOCK_DGRAM. protocol: This is usually left out, defaulting to 0. Once you have socket object, then you can use required functions to create your client or server program. Following is the list of functions required: Server Socket Methods: Method Description s.bind() This method binds address (hostname, port number pair) to socket. s.listen() This method sets up and start TCP listener. s.accept() This passively accept TCP client connection, waiting until connection arrives (blocking). Client Socket Methods: Method s.connect() Description This method actively initiates TCP server connection. General Socket Methods: Method Description s.recv() This method receives TCP message s.send() This method transmits TCP message s.recvfrom() This method receives UDP message s.sendto() This method transmits UDP message s.close() This method closes socket socket.gethostname() Returns the hostname. A Simple Server: To write Internet servers, we use the socket function available in socket module to create a socket object. A socket object is then used to call other functions to setup a socket server. Now call bind(hostname, port function to specify a port for your service on the given host. Next, call the accept method of the returned object. This method waits until a client connects to the port you specified, and then returns a connection object that represents the connection to that client. #!/usr/bin/python # This is server.py file import socket # Import socket module s = socket.socket() host = socket.gethostname() port = 12345 s.bind((host, port)) # # # # Create a socket object Get local machine name Reserve a port for your service. Bind to the port s.listen(5) # Now wait for client connection. while True: c, addr = s.accept() # Establish connection with client. print 'Got connection from', addr 3/22/2011 5:27 PM
- 136. Python - NetworkProgramming 3 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... c.send('Thank you for connecting') c.close() # Close the connection A Simple Client: Now we will write a very simple client program which will open a connection to a given port 12345 and given host. This is very simple to create a socket client using Python's socket module function. The socket.connect(hosname, port ) opens a TCP connection to hostname on the port. Once you have a socket open, you can read from it like any IO object. When done, remember to close it, as you would close a file. The following code is a very simple client that connects to a given host and port, reads any available data from the socket, and then exits: #!/usr/bin/python # This is client.py file import socket # Import socket module s = socket.socket() # Create a socket object host = socket.gethostname() # Get local machine name port = 12345 # Reserve a port for your service. s.connect((host, port)) print s.recv(1024) s.close # Close the socket when done Now run this server.py in background and then run above client.py to see the result. # Following would start a server in background. $ python server.py & # Once server is started run client as follows: $ python client.py This would produce following result: Got connection from ('127.0.0.1', 48437) Thank you for connecting Python Internet modules A list of some important modules which could be used in Python Network/Internet programming. Protocol Common function Port No Python module HTTP Web pages 80 httplib, urllib, xmlrpclib NNTP Usenet news 119 nntplib FTP File transfers 20 ftplib, urllib SMTP Sending email 25 smtplib POP3 Fetching email 110 poplib 3/22/2011 5:27 PM
- 137. Python - NetworkProgramming 4 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... IMAP4 Fetching email 143 imaplib Telnet Command lines 23 telnetlib Gopher Document transfers 70 gopherlib, urllib Please check all the libraries mentioned above to work with FTP, SMTP, POP, and IMAP protocols. Further Readings: I have given you a quick start with Socket Programming. It's a big subject so its recommended to go through the following link to find more detail on: Unix Socket Programming. Python Socket Library and Modules. Copyright © tutorialspoint.com 3/22/2011 5:27 PM
- 138. Python - SendingEmail using SMTP 1 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Sending Email using SMTP Simple Mail Transfer Protocol (SMTP) is a protocol which handles sending e-mail and routing e-mail between mail servers. Python provides smtplib module which defines an SMTP client session object that can be used to send mail to any Internet machine with an SMTP or ESMTP listener daemon. Here is a simple syntax to create one SMTP object which can later be used to send an email: import smtplib smtpObj = smtplib.SMTP( [host [, port [, local_hostname]]] ) Here is the detail of the parameters: host: This is the host running your SMTP server. You can specifiy IP address of the host or a domain name like tutorialspoint.com. This is optional argument. port: If you are providing host argument then you need to specifiy a port where SMTP server is listening. Usually this port would be 25. local_hostname: If your SMTP server is running on your local machine then you can specify just localhost as of this option. An SMTP object has an instance method called sendmail, which will typically be used to do the work of mailing a message. It takes three parameters: The sender - A string with the address of the sender. The receivers - A list of strings, one for each recipient. The message - A message as a string formatted as specified in the various RFCs. Example: Here is a simple way to send one email using Python script. Try it once: #!/usr/bin/python import smtplib sender = '[email protected]' receivers = ['[email protected]'] message = """From: From Person <[email protected]> To: To Person <[email protected]> Subject: SMTP e-mail test This is a test e-mail message. """ 3/22/2011 5:27 PM
- 139. Python - SendingEmail using SMTP 2 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... try: smtpObj = smtplib.SMTP('localhost') smtpObj.sendmail(sender, receivers, message) print "Successfully sent email" except SMTPException: print "Error: unable to send email" Here you have placed a basic e-mail in message, using a triple quote, taking care to format the headers correctly. An e-mails requires a From, To, and Subject header, separated from the body of the e-mail with a blank line. To send the mail you use smtpObj to connect to the SMTP server on the local machine and then use the sendmail method along with the message, the from address, and the destination address as parameters (even though the from and to addresses are within the e-mail itself, these aren't always used to route mail). If you're not running an SMTP server on your local machine, you can use smtplib client to communicate with a remote SMTP server. Unless you're using a webmail service (such as Hotmail or Yahoo! Mail), your e-mail provider will have provided you with outgoing mail server details that you can supply them, as follows: smtplib.SMTP('mail.your-domain.com', 25) Sending an HTML email using Python: When you send a text message using Python then all the content will be treated as simple text. Even if you will include HTML tags in a text message, it will be displayed as simple text and HTML tags will not be formatted according to HTML syntax. But Python provides option to send an HTML message as actual HTML message. While sending an email message you can specify a Mime version, content type and character set to send an HTML email. Example: Following is the example to send HTML content as an email. Try it once: #!/usr/bin/python import smtplib message = """From: From Person <[email protected]> To: To Person <[email protected]> MIME-Version: 1.0 Content-type: text/html Subject: SMTP HTML e-mail test This is an e-mail message to be sent in HTML format <b>This is HTML message.</b> <h1>This is headline.</h1> """ try: smtpObj = smtplib.SMTP('localhost') smtpObj.sendmail(sender, receivers, message) print "Successfully sent email" except SMTPException: print "Error: unable to send email" 3/22/2011 5:27 PM
- 140. Python - SendingEmail using SMTP 3 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Sending Attachements as an e-mail: To send an email with mixed content requires to set Content-type header to multipart/mixed. Then text and attachment sections can be specified within boundaries. A boundary is started with two hyphens followed by a unique number which can not appear in the message part of the email. A final boundary denoting the email's final section must also end with two hyphens. Attached files should be encoded with the pack("m") function to have base64 encoding before transmission. Example: Following is the example which will send a file /tmp/test.txt as an attachment. Try it once: #!/usr/bin/python import smtplib import base64 filename = "/tmp/test.txt" # Read a file and encode it into base64 format fo = open(filename, "rb") filecontent = fo.read() encodedcontent = base64.b64encode(filecontent) # base64 sender = '[email protected]' reciever = '[email protected]' marker = "AUNIQUEMARKER" body =""" This is a test email to send an attachement. """ # Define the main headers. part1 = """From: From Person <[email protected]> To: To Person <[email protected]> Subject: Sending Attachement MIME-Version: 1.0 Content-Type: multipart/mixed; boundary=%s --%s """ % (marker, marker) # Define the message action part2 = """Content-Type: text/plain Content-Transfer-Encoding:8bit %s --%s """ % (body,marker) # Define the attachment section part3 = """Content-Type: multipart/mixed; name="%s" Content-Transfer-Encoding:base64 Content-Disposition: attachment; filename=%s %s --%s-- 3/22/2011 5:27 PM
- 141. Python - SendingEmail using SMTP 4 of 4 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... """ %(filename, filename, encodedcontent, marker) message = part1 + part2 + part3 try: smtpObj = smtplib.SMTP('localhost') smtpObj.sendmail(sender, reciever, message) print "Successfully sent email" except Exception: print "Error: unable to send email" Copyright © tutorialspoint.com 3/22/2011 5:27 PM
- 142. Python - MultithreadedProgramming 1 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Multithreaded Programming Running several threads is similar to running several different programs concurrently, but with the following benefits: Multiple threads within a process share the same data space with the main thread and can therefore share information or communicate with each other more easily than if they were separate processes. Threads sometimes called light-weight processes and they do not require much memory overhead; theycare cheaper than processes. A thread has a beginning, an execution sequence, and a conclusion. It has an instruction pointer that keeps track of where within its context it is currently running. It can be pre-empted (interrupted) It can temporarily be put on hold (also known as sleeping) while other threads are running - this is called yielding. Starting a New Thread: To spawn another thread, you need to call following method available in thread module: thread.start_new_thread ( function, args[, kwargs] ) This method call enables a fast and efficient way to create new threads in both Linux and Windows. The method call returns immediately and the child thread starts and calls function with the passed list of agrs. When function returns, the thread terminates. Here args is a tuple of arguments; use an empty tuple to call function without passing any arguments. kwargs is an optional dictionary of keyword arguments. Example: #!/usr/bin/python import thread import time # Define a function for the thread def print_time( threadName, delay): count = 0 while count < 5: time.sleep(delay) count += 1 print "%s: %s" % ( threadName, time.ctime(time.time()) ) # Create two threads as follows try: thread.start_new_thread( print_time, ("Thread-1", 2, ) ) 3/22/2011 5:28 PM
- 143. Python - MultithreadedProgramming 2 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... thread.start_new_thread( print_time, ("Thread-2", 4, ) ) except: print "Error: unable to start thread" while 1: pass This would produce following result: Thread-1: Thread-1: Thread-2: Thread-1: Thread-2: Thread-1: Thread-1: Thread-2: Thread-2: Thread-2: Thu Thu Thu Thu Thu Thu Thu Thu Thu Thu Jan Jan Jan Jan Jan Jan Jan Jan Jan Jan 22 22 22 22 22 22 22 22 22 22 15:42:17 15:42:19 15:42:19 15:42:21 15:42:23 15:42:23 15:42:25 15:42:27 15:42:31 15:42:35 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 Although it is very effective for low-level threading, but the thread module is very limited compared to the newer threading module. The Threading Module: The newer threading module included with Python 2.4 provides much more powerful, high-level support for threads than the thread module discussed in the previous section. The threading module exposes all the methods of the thread module and provides some additional methods: threading.activeCount(): Returns the number of thread objects that are active. threading.currentThread(): Returns the number of thread objects in the caller's thread control. threading.enumerate(): Returns a list of all thread objects that are currently active. In addition to the methods, the threading module has the Thread class that implements threading. The methods provided by the Thread class are as follows: run(): The run() method is the entry point for a thread. start(): The start() method starts a thread by calling the run method. join([time]): The join() waits for threads to terminate. isAlive(): The isAlive() method checks whether a thread is still executing. getName(): The getName() method returns the name of a thread. setName(): The setName() method sets the name of a thread. Creating Thread using Threading Module: To implement a new thread using the threading module, you have to do the following: Define a new subclass of the Thread class. Override the __init__(self [,args]) method to add additional arguments. Then override the run(self [,args]) method to implement what the thread should do when started. 3/22/2011 5:28 PM
- 144. Python - MultithreadedProgramming 3 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Once you have created the new Thread subclass, you can create an instance of it and then start a new thread by invoking the start() or run() methods. Example: #!/usr/bin/python import threading import time exitFlag = 0 class myThread (threading.Thread): def __init__(self, threadID, name, counter): self.threadID = threadID self.name = name self.counter = counter threading.Thread.__init__(self) def run(self): print "Starting " + self.name print_time(self.name, self.counter, 5) print "Exiting " + self.name def print_time(threadName, delay, counter): while counter: if exitFlag: thread.exit() time.sleep(delay) print "%s: %s" % (threadName, time.ctime(time.time())) counter -= 1 # Create new threads thread1 = myThread(1, "Thread-1", 1) thread2 = myThread(2, "Thread-2", 2) # Start new Threads thread1.start() thread2.run() while thread2.isAlive(): if not thread1.isAlive(): exitFlag = 1 pass print "Exiting Main Thread" This would produce following result: Starting Thread-2 Starting Thread-1 Thread-1: Thu Jan Thread-2: Thu Jan Thread-1: Thu Jan Thread-1: Thu Jan Thread-2: Thu Jan Thread-1: Thu Jan Thread-1: Thu Jan Exiting Thread-1 Thread-2: Thu Jan Thread-2: Thu Jan 22 22 22 22 22 22 22 15:53:05 15:53:06 15:53:06 15:53:07 15:53:08 15:53:08 15:53:09 2009 2009 2009 2009 2009 2009 2009 22 15:53:10 2009 22 15:53:12 2009 3/22/2011 5:28 PM
- 145. Python - MultithreadedProgramming 4 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Thread-2: Thu Jan 22 15:53:14 2009 Exiting Thread-2 Exiting Main Thread Synchronizing Threads: The threading module provided with Python includes a simple-to-implement locking mechanism that will allow you to synchronize threads. A new lock is created by calling the Lock() method, which returns the new lock. The acquire(blocking) method the new lock object would be used to force threads to run synchronously. The optional blocking parameter enables you to control whether the thread will wait to acquire the lock. If blocking is set to 0, the thread will return immediately with a 0 value if the lock cannot be acquired and with a 1 if the lock was acquired. If blocking is set to 1, the thread will block and wait for the lock to be released. The release() method of the the new lock object would be used to release the lock when it is no longer required. Example: #!/usr/bin/python import threading import time class myThread (threading.Thread): def __init__(self, threadID, name, counter): self.threadID = threadID self.name = name self.counter = counter threading.Thread.__init__(self) def run(self): print "Starting " + self.name # Get lock to synchronize threads threadLock.acquire() print_time(self.name, self.counter, 3) # Free lock to release next thread threadLock.release() def print_time(threadName, delay, counter): while counter: time.sleep(delay) print "%s: %s" % (threadName, time.ctime(time.time())) counter -= 1 threadLock = threading.Lock() threads = [] # Create new threads thread1 = myThread(1, "Thread-1", 1) thread2 = myThread(2, "Thread-2", 2) # Start new Threads thread1.start() thread2.start() # Add threads to thread list threads.append(thread1) 3/22/2011 5:28 PM
- 146. Python - MultithreadedProgramming 5 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... threads.append(thread2) # Wait for all threads to complete for t in threads: t.join() print "Exiting Main Thread" This would produce following result: Starting Thread-1 Starting Thread-2 Thread01: Thu Jan 22 Thread01: Thu Jan 22 Thread01: Thu Jan 22 Thread02: Thu Jan 22 Thread02: Thu Jan 22 Thread02: Thu Jan 22 Exiting Main Thread 16:04:38 16:04:39 16:04:40 16:04:42 16:04:44 16:04:46 2009 2009 2009 2009 2009 2009 Multithreaded Priority Queue: The Queue module allows you to create a new queue object that can hold a specific number of items. There are following methods to control the Queue: get(): The get() removes and returns an item from the queue. put(): The put adds item to a queue. qsize() : The qsize() returns the number of items that are currently in the queue. empty(): The empty( ) returns True if queue is empty; otherwise, False. full(): the full() returns True if queue is full; otherwise, False. Example: #!/usr/bin/python import Queue import threading import time exitFlag = 0 class myThread (threading.Thread): def __init__(self, threadID, name, q): self.threadID = threadID self.name = name self.q = q threading.Thread.__init__(self) def run(self): print "Starting " + self.name process_data(self.name, self.q) print "Exiting " + self.name def process_data(threadName, q): while not exitFlag: queueLock.acquire() if not workQueue.empty(): 3/22/2011 5:28 PM
- 147. Python - MultithreadedProgramming 6 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... data = q.get() queueLock.release() print "%s processing %s" % (threadName, data) else: queueLock.release() time.sleep(1) threadList = ["Thread-1", "Thread-2", "Thread-3"] nameList = ["One", "Two", "Three", "Four", "Five"] queueLock = threading.Lock() workQueue = Queue.Queue(10) threads = [] threadID = 1 # Create new threads for tName in threadList: thread = myThread(threadID, tName, workQueue) thread.start() threads.append(thread) threadID += 1 # Fill the queue queueLock.acquire() for word in nameList: workQueue.put(word) queueLock.release() # Wait for queue to empty while not workQueue.empty(): pass # Notify threads it's time to exit exitFlag = 1 # Wait for all threads to complete for t in threads: t.join() print "Exiting Main Thread" This would produce following result: Starting Thread-2 Starting Thread-1 Starting Thread-3 Thread-2 processing Thread-1 processing Thread-3 processing Thread-2 processing Thread-1 processing Exiting Thread-3 Exiting Thread-2 Exiting Thread-1 Exiting Main Thread One Two Three Four Five Copyright © tutorialspoint.com 3/22/2011 5:28 PM
- 148. Python - XMLProcessing 1 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - XML Processing What is XML ? The Extensible Markup Language (XML) is a markup language much like HTML or SGML. This is recommended by the World Wide Web Consortium and available as an open standard. XML is a portable, open source language that allows programmers to develop applications that can be read by other applications, regardless of operating system and/or developmental language. XML is extremely useful for keeping track of small to medium amounts of data without requiring a SQL-based backbone. XML Parser Architectures and APIs: The Python standard library provides a minimal but useful set of interfaces to work with XML. The two most basic and broadly used APIs to XML data are the SAX and DOM interfaces. Simple API for XML (SAX) : Here you register callbacks for events of interest and then let the parser proceed through the document. This is useful when your documents are large or you have memory limitations, it parses the file as it reads it from disk, and the entire file is never stored in memory. Document Object Model (DOM) API : This is World Wide Web Consortium recommendation wherein the entire file is read into memory and stored in a hierarchical (tree-based) form to represent all the features of an XML document. SAX obviously can't process information as fast as DOM can when working with large files. On the other hand, using DOM exclusively can really kill your resources, especially if used on a lot of small files. SAX is read-only, while DOM allows changes to the XML file. Since these two different APIs literally complement each other there is no reason why you can't use them both for large projects. For all our XML code examples, let's use a simple XML file movies.xml as an input: <collection shelf="New Arrivals"> <movie title="Enemy Behind"> <type>War, Thriller</type> <format>DVD</format> <year>2003</year> <rating>PG</rating> <stars>10</stars> <description>Talk about a US-Japan war</description> </movie> <movie title="Transformers"> <type>Anime, Science Fiction</type> <format>DVD</format> <year>1989</year> <rating>R</rating> <stars>8</stars> <description>A schientific fiction</description> </movie> 3/22/2011 5:28 PM
- 149. Python - XMLProcessing 2 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... <movie title="Trigun"> <type>Anime, Action</type> <format>DVD</format> <episodes>4</episodes> <rating>PG</rating> <stars>10</stars> <description>Vash the Stampede!</description> </movie> <movie title="Ishtar"> <type>Comedy</type> <format>VHS</format> <rating>PG</rating> <stars>2</stars> <description>Viewable boredom</description> </movie> </collection> Parsing XML with SAX APIs: SAX is a standard interface for event-driven XML parsing. Parsing XML with SAX generally requires you to create your own ContentHandler, by subclassing xml.sax.ContentHandler. Your ContentHandler handles the particular tags and attributes of your flavor(s) of XML. A ContentHandler object provides methods to handle various parsing events. Its owning parser calls ContentHandler methods as it parses the XML file. The methods startDocument and endDocument are called at the start and the end of the XML file. The method characters(text) is passed character data of the XML file via the parameter text. The ContentHandler is called at the start and end of each element. If the parser is not in namespace mode, the methods startElement(tag, attributes) and endElement(tag) are called; otherwise, the corresponding methods startElementNS and endElementNS are called. Here, tag is the element tag, and attributes is an Attributes object. Here are other important methods to understand before proceeding: The make_parser Method: Following method creates a new parser object and returns it. The parser object created will be of the first parser type the system finds. xml.sax.make_parser( [parser_list] ) Here is the detail of the parameters: parser_list: The optional argument consisting of a list of parsers to use, which must all implement the make_parser method. The parse Method: Following method creates a SAX parser and use it to parse a document. xml.sax.parse( xmlfile, contenthandler[, errorhandler]) Here is the detail of the parameters: xmlfile: This is the name of the XML file to read from. contenthandler: This must be a ContentHandler object. 3/22/2011 5:28 PM
- 150. Python - XMLProcessing 3 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... errorhandler: If specified, errorhandler must be a SAX ErrorHandler object. The parseString Method: There is one more method to create a SAX parser and to parse the specified XML string. xml.sax.parseString(xmlstring, contenthandler[, errorhandler]) Here is the detail of the parameters: xmlstring: This is the name of the XML string to read from. contenthandler: This must be a ContentHandler object. errorhandler: If specified, errorhandler must be a SAX ErrorHandler object. Example: #!/usr/bin/python import xml.sax class MovieHandler( xml.sax.ContentHandler ): def __init__(self): self.CurrentData = "" self.type = "" self.format = "" self.year = "" self.rating = "" self.stars = "" self.description = "" # Call when an element starts def startElement(self, tag, attributes): self.CurrentData = tag if tag == "movie": print "*****Movie*****" title = attributes["title"] print "Title:", title # Call when an elements ends def endElement(self, tag): if self.CurrentData == "type": print "Type:", self.type elif self.CurrentData == "format": print "Format:", self.format elif self.CurrentData == "year": print "Year:", self.year elif self.CurrentData == "rating": print "Rating:", self.rating elif self.CurrentData == "stars": print "Stars:", self.stars elif self.CurrentData == "description": print "Description:", self.description self.CurrentData = "" # Call when a character is read def characters(self, content): if self.CurrentData == "type": self.type = content 3/22/2011 5:28 PM
- 151. Python - XMLProcessing 4 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... elif self.CurrentData == "format": self.format = content elif self.CurrentData == "year": self.year = content elif self.CurrentData == "rating": self.rating = content elif self.CurrentData == "stars": self.stars = content elif self.CurrentData == "description": self.description = content if ( __name__ == "__main__"): # create an XMLReader parser = xml.sax.make_parser() # turn off namepsaces parser.setFeature(xml.sax.handler.feature_namespaces, 0) # override the default ContextHandler Handler = MovieHandler() parser.setContentHandler( Handler ) parser.parse("movies.xml") This would produce following result: *****Movie***** Title: Enemy Behind Type: War, Thriller Format: DVD Year: 2003 Rating: PG Stars: 10 Description: Talk about a US-Japan war *****Movie***** Title: Transformers Type: Anime, Science Fiction Format: DVD Year: 1989 Rating: R Stars: 8 Description: A schientific fiction *****Movie***** Title: Trigun Type: Anime, Action Format: DVD Rating: PG Stars: 10 Description: Vash the Stampede! *****Movie***** Title: Ishtar Type: Comedy Format: VHS Rating: PG Stars: 2 Description: Viewable boredom For a complete detail on SAX API documentation, please refer to standard Python SAX APIs. Parsing XML with DOM APIs: 3/22/2011 5:28 PM
- 152. Python - XMLProcessing 5 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... The Document Object Model, or "DOM," is a cross-language API from the World Wide Web Consortium (W3C) for accessing and modifying XML documents. The DOM is extremely useful for random-access applications. SAX only allows you a view of one bit of the document at a time. If you are looking at one SAX element, you have no access to another. Here is the easiest way to quickly load an XML document and to create a minidom object using the xml.dom module. The minidom object provides a simple parser method that will quickly create a DOM tree from the XML file. The sample phrase calls the parse( file [,parser] ) function of the minidom object to parse the XML file designated by file into a DOM tree object. #!/usr/bin/python from xml.dom.minidom import parse import xml.dom.minidom # Open XML document using minidom parser DOMTree = xml.dom.minidom.parse("text.xml") collection = DOMTree.documentElement if collection.hasAttribute("shelf"): print "Root element : %s" % collection.getAttribute("shelf") # Get all the movies in the collection movies = collection.getElementsByTagName("movie") # Print detail of each movie. for movie in movies: print "*****Movie*****" if movie.hasAttribute("title"): print "Title: %s" % movie.getAttribute("title") type = movie.getElementsByTagName('type')[0] print "Type: %s" % type.childNodes[0].data format = movie.getElementsByTagName('format')[0] print "Format: %s" % format.childNodes[0].data rating = movie.getElementsByTagName('rating')[0] print "Rating: %s" % rating.childNodes[0].data description = movie.getElementsByTagName('description')[0] print "Description: %s" % description.childNodes[0].data This would produce following result: Root element : New Arrivals *****Movie***** Title: Enemy Behind Type: War, Thriller Format: DVD Rating: PG Description: Talk about a US-Japan war *****Movie***** Title: Transformers Type: Anime, Science Fiction Format: DVD Rating: R Description: A schientific fiction *****Movie***** Title: Trigun Type: Anime, Action 3/22/2011 5:28 PM
- 153. Python - XMLProcessing 6 of 6 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Format: DVD Rating: PG Description: Vash the Stampede! *****Movie***** Title: Ishtar Type: Comedy Format: VHS Rating: PG Description: Viewable boredom For a complete detail on DOM API documentation, please refer to standard Python DOM APIs. Copyright © tutorialspoint.com 3/22/2011 5:28 PM
- 154. Python - GUIProgramming (Tkinter) 1 of 3 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - GUI Programming (Tkinter) Python provides various options for developing graphical user interfaces (GUIs). Most important are listed below: Tkinter: Tkinter is the Python interface to the Tk GUI toolkit shipped with Python. We would look this option in this tutorial. wxPython: This is an open-source Python interface for wxWindows http://wxpython.org. JPython: JPython is a Python port for Java, which gives Python scripts seamless access to Java class libraries on the local machine http://www.jython.org. There are many other interfaces available which I'm not listing here. You can find them over the net. Tkinter Programming: Tkinter is the standard GUI library for Python. Python when combined with Tkinter provides a fast and easy way to create GUI applications. Tkinter provides a powerful object-oriented interface to the Tk GUI toolkit. Creating a GUI application using Tkinter is an easy task. All you need to do is perform the following steps: Import the Tkinter module. Create the GUI application main window. Add one or more of the above mentioned widgets to the GUI application. Enter the main event loop to take action against each event triggered by the user. Example: #!/usr/bin/python import Tkinter top = Tkinter.Tk() # Code to add widgets will go here... top.mainloop() This would create a following window: 3/22/2011 5:28 PM
- 155. Python - GUIProgramming (Tkinter) 2 of 3 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Tkinter Widgets: Tkinter provides various controls, such as buttons, labels, and text boxes, used in a GUI application. These controls are commonly called widgets. There are currently 15 types of widgets in Tkinter. We present these widgets as well as a brief description in the following table: Operator Description Button The Button widget is used to display buttons in your application. Canvas The Canvas widget is used to draw shapes, such as lines, ovals, polygons, and rectangles, in your application. Checkbutton The Checkbutton widget is used to display a number of options as checkboxes. The user can select multiple options at a time. Entry The Entry widget is used to display a single-line text field for accepting values from a user. Frame The Frame widget is used as a container widget to organize other widgets. Label The Label widget is used to provide a single-line caption for other widgets. It can also contain images. Listbox The Listbox widget is used to provide a list of options to a user. Menubutton The Menubutton widget is used to display menus in your application. Menu The Menu widget is used to provide various commands to a user. These commands are contained inside Menubutton. Message The Message widget is used to display multiline text fields for accepting values from a user. Radiobutton The Radiobutton widget is used to display a number of options as radio buttons. The user can select only one option at a time. Scale The Scale widget is used to provide a slider widget. Scrollbar The Scrollbar widget is used to add scrolling capability to various widgets, such as list boxes. Text The Text widget is used to display text in multiple lines. Toplevel The Toplevel widget is used to provide a separate window container. 3/22/2011 5:28 PM
- 156. Python - GUIProgramming (Tkinter) 3 of 3 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Spinbox The Spinbox widget is a variant of the standard Tkinter Entry widget, which can be used to select from a fixed number of values. PanedWindow A PanedWindow is a container widget that may contain any number of panes, arranged horizontally or vertically. LabelFrame A labelframe is a simple container widget. Its primary purpose is to act as a spacer or container for complex window layouts. tkMessageBox This module is used to display message boxes in your applications. Standard attributes: Let's take a look at how some of their common attributes.such as sizes, colors and fonts are specified. Dimensions Colors Fonts Anchors Relief styles Bitmaps Cursors Geometry Management: All Tkinter widgets have access to specific geometry management methods, which have the purpose of organizing widgets throughout the parent widget area. Tkinter exposes the following geometry manager classes: pack, grid, and place. The pack() Method - This geometry manager organizes widgets in blocks before placing them in the parent widget. The grid() Method - This geometry manager organizes widgets in a table-like structure in the parent widget. The place() Method -This geometry manager organizes widgets by placing them in a specific position in the parent widget. Copyright © tutorialspoint.com 3/22/2011 5:28 PM
- 157. Python - ExtensionProgramming with C 1 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Further Extensions using C Any code that you write using any compiled language like C, C++ or Java can be integrated or imported into another Python script. This code is considered as an "extension". A Python extension module is nothing more than a normal C library. On Unix machines, these libraries usually end in .so (for shared object). On Windows machines, you typically see .dll (for dynamically linked library). Pre-Requisite: To start writing your extension you are going to need the Python header files. On Unix machines, this usually requires installing a developer-specific package such as python2.5-dev. Windows users get these headers as part of the package when they use the binary Python installer. Additionally, it is assumed that you have good knowledge of C or C++ to write any Python Extension using C programming. First look at a Python extension: For your first look at a Python extension module, you'll be grouping your code into four parts: The header file Python.h. The C functions you want to expose as the interface from your module. A table mapping the names of your functions as Python developers will see them to C functions inside the extension module. An initialization function. The header file Python.h Start including Python.h header file in your C source file, which will give you access to the internal Python API used to hook your module into the interpreter. Be sure to include Python.h before any other headers you might need. You'll follow the includes with the functions you want to call from Python. The C functions: The signatures of the C implementations of your functions will always take one of the following three forms: static PyObject *MyFunction( PyObject *self, PyObject *args ); static PyObject *MyFunctionWithKeywords(PyObject *self, PyObject *args, PyObject *kw); static PyObject *MyFunctionWithNoArgs( PyObject *self ); 3/22/2011 5:29 PM
- 158. Python - ExtensionProgramming with C 2 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Each one of the preceding declarations returns a Python object. There's no such thing as a void function in Python as there is in C. If you don't want your functions to return a value, return the C equivalent of Python's None value. The Python headers define a macro, Py_RETURN_NONE, that does this for us. The names of your C functions can be whatever you like as they will never be seen outside of the extension module. So they would be defined as static function. Your C functions usually are named by combining the Python module and function names together, as shown here: static PyObject *module_func(PyObject *self, PyObject *args) { /* Do your stuff here. */ Py_RETURN_NONE; } This would be a Python function called func inside of the module module. You'll be putting pointers to your C functions into the method table for the module that usually comes next in your source code. The method mapping table: This method table is a simple array of PyMethodDef structures. That structure looks something like this: struct PyMethodDef { char *ml_name; PyCFunction ml_meth; int ml_flags; char *ml_doc; }; Here is the description of the members of this structure: ml_name: This is the name of the function as the Python interpreter will present it when it is used in Python programs. ml_meth: This must be the address to a function that has any one of the signatures described in previous seection. ml_flags: This tells the interpreter which of the three signatures ml_meth is using. This flag will usually have a value of METH_VARARGS. This flag can be bitwise or'ed with METH_KEYWORDS if you want to allow keyword arguments into your function. This can also have a value of METH_NOARGS that indicates you don't want to accept any arguments. ml_doc: This is the docstring for the function, which could be NULL if you don't feel like writing one This table needs to be terminated with a sentinel that consists of NULL and 0 values for the appropriate members. Example: For the above defined function, we would have following method mapping table: static PyMethodDef module_methods[] = { { "func", (PyCFunction)module_func, METH_NOARGS, NULL }, 3/22/2011 5:29 PM
- 159. Python - ExtensionProgramming with C 3 of 8 }; http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... { NULL, NULL, 0, NULL } The initialization function: The last part of your extension module is the initialization function. This function is called by the Python interpreter when the module is loaded. It's required that the function be named initModule, where Module is the name of the module. The initialization function needs to be exported from the library you'll be building. The Python headers define PyMODINIT_FUNC to include the appropriate incantations for that to happen for the particular environment in which we're compiling. All you have to do is use it when defining the function. Your C initialization function generally has the following overall structure: PyMODINIT_FUNC initModule() { Py_InitModule3(func, module_methods, "docstring..."); } Here is the description of Py_InitModule3 function: func: This is the function to be exported. module_methods: This is the mapping table name defined above. docstring: This is the comment you want to give in your extension. Putting this all together looks like the following: #include <Python.h> static PyObject *module_func(PyObject *self, PyObject *args) { /* Do your stuff here. */ Py_RETURN_NONE; } static PyMethodDef module_methods[] = { { "func", (PyCFunction)module_func, METH_NOARGS, NULL }, { NULL, NULL, 0, NULL } }; PyMODINIT_FUNC initModule() { Py_InitModule3(func, module_methods, "docstring..."); } Example: A simple example that makes use of all the above concepts: #include <Python.h> static PyObject* helloworld(PyObject* self) { return Py_BuildValue("s", "Hello, Python extensions!!"); } static char helloworld_docs[] = "helloworld( ): Any message you want to put here!!n"; 3/22/2011 5:29 PM
- 160. Python - ExtensionProgramming with C 4 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... static PyMethodDef helloworld_funcs[] = { {"helloworld", (PyCFunction)helloworld, METH_NOARGS, helloworld_docs}, {NULL} }; void inithelloworld(void) { Py_InitModule3("helloworld", helloworld_funcs, "Extension module example!"); } Here the Py_BuildValue function is used to build a Python value. Save above code in hello.c file. We would see how to compile and install this module to be called from Python script. Building and Installing Extensions: The distutils package makes it very easy to distribute Python modules, both pure Python and extension modules, in a standard way. Modules are distributed in source form and built and installed via a setup script usually called setup.py as follows. For the above module, you would have to prepare following setup.py script: from distutils.core import setup, Extension setup(name='helloworld', version='1.0', ext_modules=[Extension('helloworld', ['hello.c'])]) Now use the following command, which would perform all needed compilation and linking steps, with the right compiler and linker commands and flags, and copies the resulting dynamic library into an appropriate directory: $ python setup.py install On Unix-based systems, you'll most likely need to run this command as root in order to have permissions to write to the site-packages directory. This usually isn't a problem on Windows Import Extensions: Once you installed your extension, you would be able to import and call that extension in your Python script as follows: #!/usr/bin/python import helloworld print helloworld.helloworld() This would produce following result: Hello, Python extensions!! Passing Function Parameters: Because you'll most likely want to define functions that do accept arguments, you can use one of the other signatures for your C functions. For example, following function, that accepts some number of 3/22/2011 5:29 PM
- 161. Python - ExtensionProgramming with C 5 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... parameters, would be defined like this: static PyObject *module_func(PyObject *self, PyObject *args) { /* Parse args and do something interesting here. */ Py_RETURN_NONE; } The method table containing an entry for the new function would look like this: static PyMethodDef module_methods[] = { { "func", (PyCFunction)module_func, METH_NOARGS, NULL }, { "func", module_func, METH_VARARGS, NULL }, { NULL, NULL, 0, NULL } }; You can use API PyArg_ParseTuple function to extract the arguments from the one PyObject pointer passed into your C function. The first argument to PyArg_ParseTuple is the args argument. This is the object you'll be parsing. The second argument is a format string describing the arguments as you expect them to appear. Each argument is represented by one or more characters in the format string as follows. static PyObject *module_func(PyObject *self, PyObject *args) { int i; double d; char *s; if (!PyArg_ParseTuple(args, "ids", &i, &d, &s)) { return NULL; } } /* Do something interesting here. */ Py_RETURN_NONE; Compiling the new version of your module and importing it will enable you to invoke the new function with any number of arguments of any type: module.func(1, s="three", d=2.0) module.func(i=1, d=2.0, s="three") module.func(s="three", d=2.0, i=1) You can probably come up with even more variations. The PyArg_ParseTuple Function: Here is the standard signature for PyArg_ParseTuple function: int PyArg_ParseTuple(PyObject* tuple,char* format,...) This function returns 0 for errors, and a value not equal to 0 for success. tuple is the PyObject* that was the C function's second argument. Here format is a C string that describes mandatory and optional arguments. Here is a list of format codes for PyArg_ParseTuple function: 3/22/2011 5:29 PM
- 162. Python - ExtensionProgramming with C 6 of 8 Code http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... C type Meaning c char A Python string of length 1 becomes a C char. d double A Python float becomes a C double. f float A Python float becomes a C float. i int A Python int becomes a C int. l long A Python int becomes a C long. L long long A Python int becomes a C long long O PyObject* Gets non-NULL borrowed reference to Python argument. s char* Python string without embedded nulls to C char*. s# char*+int Any Python string to C address and length. t# char*+int Read-only single-segment buffer to C address and length. u Py_UNICODE* Python Unicode without embedded nulls to C. u# Py_UNICODE*+int Any Python Unicode C address and length. w# char*+int Read/write single-segment buffer to C address and length. z char* Like s, also accepts None (sets C char* to NULL). z# char*+int Like s#, also accepts None (sets C char* to NULL). (...) as per ... A Python sequence is treated as one argument per item. | The following arguments are optional. : Format end, followed by function name for error messages. ; Format end, followed by entire error message text. Returning Values: Py_BuildValue takes in a format string much like PyArg_ParseTuple does. Instead of passing in the addresses of the values you're building, you pass in the actual values. Here's an example showing how to implement an add function: static PyObject *foo_add(PyObject *self, PyObject *args) { int a; int b; } if (!PyArg_ParseTuple(args, "ii", &a, &b)) { return NULL; } return Py_BuildValue("i", a + b); This is what it would look like if implemented in Python: def add(a, b): return (a + b) You can return two values from your function as follows, this would be cauptured using a list in Python. 3/22/2011 5:29 PM
- 163. Python - ExtensionProgramming with C 7 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... static PyObject *foo_add_subtract(PyObject *self, PyObject *args) { int a; int b; if (!PyArg_ParseTuple(args, "ii", &a, &b)) { return NULL; } return Py_BuildValue("ii", a + b, a - b); } This is what it would look like if implemented in Python: def add_subtract(a, b): return (a + b, a - b) The Py_BuildValue Function: Here is the standard signature for Py_BuildValue function: PyObject* Py_BuildValue(char* format,...) Here format is a C string that describes the Python object to build. The following arguments of Py_BuildValue are C values from which the result is built. The PyObject* result is a new reference. Following table lists the commonly used code strings, of which zero or more are joined into string format. Code C type Meaning c char A C char becomes a Python string of length 1. d double A C double becomes a Python float. f float A C float becomes a Python float. i int A C int becomes a Python int. l long A C long becomes a Python int. N PyObject* Passes a Python object and steals a reference. O PyObject* Passes a Python object and INCREFs it as normal. O& convert+void* Arbitrary conversion s char* C 0-terminated char* to Python string, or NULL to None. s# char*+int C char* and length to Python string, or NULL to None. u Py_UNICODE* C-wide, null-terminated string to Python Unicode, or NULL to None. u# Py_UNICODE*+int C-wide string and length to Python Unicode, or NULL to None. w# char*+int Read/write single-segment buffer to C address and length. z char* Like s, also accepts None (sets C char* to NULL). z# char*+int Like s#, also accepts None (sets C char* to NULL). (...) as per ... Builds Python tuple from C values. [...] as per ... Builds Python list from C values. {...} as per ... Builds Python dictionary from C values, alternating keys and values. 3/22/2011 5:29 PM
- 164. Python - ExtensionProgramming with C 8 of 8 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Code {...} builds dictionaries from an even number of C values, alternately keys and values. For example, Py_BuildValue("{issi}",23,"zig","zag",42) returns a dictionary like Python's {23:'zig','zag':42}. Copyright © tutorialspoint.com 3/22/2011 5:29 PM
- 165. Python - QuickGuide 1 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Quick Guide Python Overview: Python is a high-level, interpreted, interactive and object oriented-scripting language. Python is Interpreted Python is Interactive Python is Object-Oriented Python is Beginner's Language Python was developed by Guido van Rossum in the late eighties and early nineties at the National Research Institute for Mathematics and Computer Science in the Netherlands. Python's feature highlights include: Easy-to-learn Easy-to-read Easy-to-maintain A broad standard library Interactive Mode Portable Extendable Databases GUI Programming Scalable Getting Python: The most up-to-date and current source code, binaries, documentation, news, etc. is available at the official website of Python: Python Official Website : http://www.python.org/ You can download the Python documentation from the following site. The documentation is available in HTML, PDF, and PostScript formats. Python Documentation Website : www.python.org/doc/ First Python Program: Interactive Mode Programming: Invoking the interpreter without passing a script file as a parameter brings up the following prompt: 3/22/2011 5:29 PM
- 166. Python - QuickGuide 2 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... root# python Python 2.5 (r25:51908, Nov 6 2007, 16:54:01) [GCC 4.1.2 20070925 (Red Hat 4.1.2-27)] on linux2 Type "help", "copyright", "credits" or "license" for more info. >>> Type the following text to the right of the Python prompt and press the Enter key: >>> print "Hello, Python!"; This will produce following result: Hello, Python! Python Identifiers: A Python identifier is a name used to identify a variable, function, class, module, or other object. An identifier starts with a letter A to Z or a to z or an underscore (_) followed by zero or more letters, underscores, and digits (0 to 9). Python does not allow punctuation characters such as @, $, and % within identifiers. Python is a case sensitive programming language. Thus Manpower and manpower are two different identifiers in Python. Here are following identifier naming convention for Python: Class names start with an uppercase letter and all other identifiers with a lowercase letter. Starting an identifier with a single leading underscore indicates by convention that the identifier is meant to be private. Starting an identifier with two leading underscores indicates a strongly private identifier. If the identifier also ends with two trailing underscores, the identifier is a language-defined special name. Reserved Words: The following list shows the reserved words in Python. These reserved words may not be used as constant or variable or any other identifier names. Keywords contain lowercase letters only. and exec not assert finally or break for pass class from print continue global raise def if return del import try elif in while else is with 3/22/2011 5:29 PM
- 167. Python - QuickGuide 3 of 28 except http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... lambda yield Lines and Indentation: One of the first caveats programmers encounter when learning Python is the fact that there are no braces to indicate blocks of code for class and function definitions or flow control. Blocks of code are denoted by line indentation, which is rigidly enforced. The number of spaces in the indentation is variable, but all statements within the block must be indented the same amount. Both blocks in this example are fine: if True: print "True" else: print "False" However, the second block in this example will generate an error: if True: print "Answer" print "True" else: print "Answer" print "False" Multi-Line Statements: Statements in Python typically end with a new line. Python does, however, allow the use of the line continuation character () to denote that the line should continue. For example: total = item_one + item_two + item_three Statements contained within the [], {}, or () brackets do not need to use the line continuation character. For example: days = ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday'] Quotation in Python: Python accepts single ('), double (") and triple (''' or """) quotes to denote string literals, as long as the same type of quote starts and ends the string. The triple quotes can be used to span the string across multiple lines. For example, all the following are legal: word = 'word' sentence = "This is a sentence." paragraph = """This is a paragraph. It is made up of multiple lines and sentences.""" 3/22/2011 5:29 PM
- 168. Python - QuickGuide 4 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Comments in Python: A hash sign (#) that is not inside a string literal begins a comment. All characters after the # and up to the physical line end are part of the comment, and the Python interpreter ignores them. #!/usr/bin/python # First comment print "Hello, Python!"; # second comment This will produce following result: Hello, Python! A comment may be on the same line after a statement or expression: name = "Madisetti" # This is again comment You can comment multiple lines as follows: # # # # This is a comment. This is a comment, too. This is a comment, too. I said that already. Using Blank Lines: A line containing only whitespace, possibly with a comment, is known as a blank line, and Python totally ignores it. In an interactive interpreter session, you must enter an empty physical line to terminate a multiline statement. Multiple Statements on a Single Line: The semicolon ( ; ) allows multiple statements on the single line given that neither statement starts a new code block. Here is a sample snip using the semicolon: import sys; x = 'foo'; sys.stdout.write(x + 'n') Multiple Statement Groups as Suites: Groups of individual statements making up a single code block are called suites in Python. Compound or complex statements, such as if, while, def, and class, are those which require a header line and a suite. Header lines begin the statement (with the keyword) and terminate with a colon ( : ) and are followed by one or more lines which make up the suite. Example: 3/22/2011 5:29 PM
- 169. Python - QuickGuide 5 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... if expression : suite elif expression : suite else : suite Python - Variable Types: Variables are nothing but reserved memory locations to store values. This means that when you create a variable you reserve some space in memory. Based on the data type of a variable, the interpreter allocates memory and decides what can be stored in the reserved memory. Therefore, by assigning different data types to variables, you can store integers, decimals, or characters in these variables. Assigning Values to Variables: The operand to the left of the = operator is the name of the variable, and the operand to the right of the = operator is the value stored in the variable. For example: counter = 100 miles = 1000.0 name = "John" # An integer assignment # A floating point # A string print counter print miles print name Standard Data Types: Python has five standard data types: Numbers String List Tuple Dictionary Python Numbers: Number objects are created when you assign a value to them. For example: var1 = 1 var2 = 10 Python supports four different numerical types: int (signed integers) long (long integers [can also be represented in octal and hexadecimal]) float (floating point real values) 3/22/2011 5:29 PM
- 170. Python - QuickGuide 6 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... complex (complex numbers) Here are some examples of numbers: int long float complex 10 51924361L 0.0 3.14j 100 -0x19323L 15.20 45.j -786 0122L -21.9 9.322e-36j 080 0xDEFABCECBDAECBFBAEl 32.3+e18 .876j -0490 535633629843L -90. -.6545+0J -0x260 -052318172735L -32.54e100 3e+26J 0x69 -4721885298529L 70.2-E12 4.53e-7j Python Strings: Strings in Python are identified as a contiguous set of characters in between quotation marks. Example: str = 'Hello World!' print print print print print print str str[0] str[2:5] str[2:] str * 2 str + "TEST" # # # # # # Prints Prints Prints Prints Prints Prints complete string first character of the string characters starting from 3rd to 6th string starting from 3rd character string two times concatenated string Python Lists: Lists are the most versatile of Python's compound data types. A list contains items separated by commas and enclosed within square brackets ([]). #!/usr/bin/python list = [ 'abcd', 786 , 2.23, 'john', 70.2 ] tinylist = [123, 'john'] print print print print print print list # list[0] # list[1:3] # list[2:] # tinylist * 2 # list + tinylist Prints complete list Prints first element of the list Prints elements starting from 2nd to 4th Prints elements starting from 3rd element Prints list two times # Prints concatenated lists Python Tuples: A tuple is another sequence data type that is similar to the list. A tuple consists of a number of values separated by commas. Unlike lists, however, tuples are enclosed within parentheses. Tuples can be thought of as read-only lists. 3/22/2011 5:29 PM
- 171. Python - QuickGuide 7 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... tuple = ( 'abcd', 786 , 2.23, 'john', 70.2 tinytuple = (123, 'john') print print print print print print tuple # tuple[0] # tuple[1:3] # tuple[2:] # tinytuple * 2 # tuple + tinytuple ) Prints complete list Prints first element of the list Prints elements starting from 2nd to 4th Prints elements starting from 3rd element Prints list two times # Prints concatenated lists Python Dictionary: Python 's dictionaries are hash table type. They work like associative arrays or hashes found in Perl and consist of key-value pairs. tinydict = {'name': 'john','code':6734, 'dept': 'sales'} print dict['one'] # Prints value for 'one' key print dict[2] # Prints value for 2 key print tinydict # Prints complete dictionary print tinydict.keys() # Prints all the keys print tinydict.values() # Prints all the values Python - Basic Operators: Operator Description Example + Addition - Adds values on either side of the operator a + b will give 30 - Subtraction - Subtracts right hand operand from left hand operand a - b will give -10 * Multiplication - Multiplies values on either side of the operator a * b will give 200 / Division - Divides left hand operand by right hand operand b / a will give 2 % Modulus - Divides left hand operand by right hand operand and returns remainder b % a will give 0 ** Exponent - Performs exponential (power) calculation on operators a**b will give 10 to the power 20 // Floor Division - The division of operands where the result is the quotient in which the digits after the decimal point are removed. 9//2 is equal to 4 and 9.0//2.0 is equal to 4.0 == Checks if the value of two operands are equal or not, if yes then condition becomes true. (a == b) is not true. != Checks if the value of two operands are equal or not, if values are not equal then condition becomes true. (a != b) is true. <> Checks if the value of two operands are equal or not, if values are not equal then condition becomes true. (a <> b) is true. This is similar to != operator. 3/22/2011 5:29 PM
- 172. Python - QuickGuide 8 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... > Checks if the value of left operand is greater than the value of right operand, if yes then condition becomes true. (a > b) is not true. < Checks if the value of left operand is less than the value of right operand, if yes then condition becomes true. (a < b) is true. >= Checks if the value of left operand is greater than or equal to the value of right operand, if yes then condition becomes true. (a >= b) is not true. <= Checks if the value of left operand is less than or equal to the value of right operand, if yes then condition becomes true. (a <= b) is true. = Simple assignment operator, Assigns values from right side operands to left side operand c = a + b will assigne value of a + b into c += Add AND assignment operator, It adds right operand to the left operand and assign the result to left operand c += a is equivalent to c = c + a -= Subtract AND assignment operator, It subtracts right operand from the left operand and assign the result to left operand c -= a is equivalent to c = c - a *= Multiply AND assignment operator, It multiplies right operand with the left operand and assign the result to left operand c *= a is equivalent to c = c * a /= Divide AND assignment operator, It divides left operand with the right operand and assign the result to left operand c /= a is equivalent to c = c / a %= Modulus AND assignment operator, It takes modulus using two operands and assign the result to left operand c %= a is equivalent to c = c % a **= Exponent AND assignment operator, Performs exponential (power) calculation on operators and assign value to the left operand c **= a is equivalent to c = c ** a //= Floor Dividion and assigns a value, Performs floor division on operators and assign value to the left operand c //= a is equivalent to c = c // a & Binary AND Operator copies a bit to the result (a & b) will give 12 which is 0000 1100 if it exists in both operands. | Binary OR Operator copies a bit if it exists in eather operand. (a | b) will give 61 which is 0011 1101 ^ Binary XOR Operator copies the bit if it is set in one operand but not both. (a ^ b) will give 49 which is 0011 0001 ~ Binary Ones Complement Operator is unary and has the efect of 'flipping' bits. (~a ) will give -60 which is 1100 0011 << Binary Left Shift Operator. The left operands value is moved left by the number of bits specified by the right operand. a << 2 will give 240 which is 1111 0000 >> Binary Right Shift Operator. The left operands value is moved right by the number of bits a >> 2 will give 15 which is 0000 1111 specified by the right operand. 3/22/2011 5:29 PM
- 173. Python - QuickGuide 9 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... and Called Logical AND operator. If both the operands are true then then condition becomes true. (a and b) is true. or Called Logical OR Operator. If any of the two operands are non zero then then condition becomes true. (a or b) is true. not Called Logical NOT Operator. Use to reverses the logical state of its operand. If a condition is true then Logical NOT operator will make false. not(a && b) is false. in Evaluates to true if it finds a variable in the specified sequence and false otherwise. x in y, here in results in a 1 if x is a member of sequence y. not in Evaluates to true if it finds a variable in the specified sequence and false otherwise. x not in y, here not in results in a 1 if x is a member of sequence y. is Evaluates to true if the variables on either side of the operator point to the same object and false otherwise. x is y, here is results in 1 if id(x) equals id(y). is not Evaluates to false if the variables on either side of the operator point to the same object and true otherwise. x is not y, here is not results in 1 if id(x) is not equal to id(y). Python Operators Precedence The following table lists all operators from highest precedence to lowest. Operator Description ** Exponentiation (raise to the power) ~+- Ccomplement, unary plus and minus (method names for the last two are +@ and -@) * / % // Multiply, divide, modulo and floor division +- Addition and subtraction >> << Right and left bitwise shift & Bitwise 'AND' ^| Bitwise exclusive `OR' and regular `OR' <= < > >= Comparison operators <> == != Equality operators = %= /= //= -= += |= &= >>= <<= *= **= Assignment operators is is not Identity operators in not in Membership operators note or and Logical operators The if statement: The syntax of the if statement is: 3/22/2011 5:29 PM
- 174. Python - QuickGuide 10 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... if expression: statement(s) The else Statement: The syntax of the if...else statement is: if expression: statement(s) else: statement(s) The elif Statement The syntax of the if...elif statement is: if expression1: statement(s) elif expression2: statement(s) elif expression3: statement(s) else: statement(s) This will produce following result: 3 - Got a true expression value 100 Good bye! The Nested if...elif...else Construct The syntax of the nested if...elif...else construct may be: if expression1: statement(s) if expression2: statement(s) elif expression3: statement(s) else statement(s) elif expression4: statement(s) else: statement(s) The while Loop: The syntax of the while look is: 3/22/2011 5:29 PM
- 175. Python - QuickGuide 11 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... while expression: statement(s) The Infinite Loops: You must use caution when using while loops because of the possibility that this condition never resolves to a false value. This results in a loop that never ends. Such a loop is called an infinite loop. An infinite loop might be useful in client/server programming where the server needs to run continuously so that client programs can communicate with it as and when required. Single Statement Suites: Similar to the if statement syntax, if your while clause consists only of a single statement, it may be placed on the same line as the while header. Here is an example of a one-line while clause: while expression : statement The for Loop: The syntax of the loop look is: for iterating_var in sequence: statements(s) Iterating by Sequence Index: An alternative way of iterating through each item is by index offset into the sequence itself: fruits = ['banana', 'apple', 'mango'] for index in range(len(fruits)): print 'Current fruit :', fruits[index] print "Good bye!" The break Statement: The break statement in Python terminates the current loop and resumes execution at the next statement, just like the traditional break found in C. The most common use for break is when some external condition is triggered requiring a hasty exit from a loop. The break statement can be used in both while and for loops. for letter in 'Python': # First Example if letter == 'h': break print 'Current Letter :', letter var = 10 # Second Example while var > 0: print 'Current variable value :', var 3/22/2011 5:29 PM
- 176. Python - QuickGuide 12 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... var = var -1 if var == 5: break print "Good bye!" The continue Statement: The continue statement in Python returns the control to the beginning of the while loop. The continue statement rejects all the remaining statements in the current iteration of the loop and moves the control back to the top of the loop. The continue statement can be used in both while and for loops. for letter in 'Python': # First Example if letter == 'h': continue print 'Current Letter :', letter var = 10 # Second Example while var > 0: print 'Current variable value :', var var = var -1 if var == 5: continue print "Good bye!" The else Statement Used with Loops Python supports to have an else statement associated with a loop statements. If the else statement is used with a for loop, the else statement is executed when the loop has exhausted iterating the list. If the else statement is used with a while loop, the else statement is executed when the condition becomes false. The pass Statement: The pass statement in Python is used when a statement is required syntactically but you do not want any command or code to execute. The pass statement is a null operation; nothing happens when it executes. The pass is also useful in places where your code will eventually go, but has not been written yet (e.g., in stubs for example): #!/usr/bin/python for letter in 'Python': if letter == 'h': pass print 'This is pass block' print 'Current Letter :', letter print "Good bye!" Defining a Function 3/22/2011 5:29 PM
- 177. Python - QuickGuide 13 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... You can define functions to provide the required functionality. Here are simple rules to define a function in Python: Function blocks begin with the keyword def followed by the function name and parentheses ( ( ) ). Any input parameters or arguments should be placed within these parentheses. You can also define parameters inside these parentheses. The first statement of a function can be an optional statement - the documentation string of the function or docstring. The code block within every function starts with a colon (:) and is indented. The statement return [expression] exits a function, optionally passing back an expression to the caller. A return statement with no arguments is the same as return None. Syntax: def functionname( parameters ): "function_docstring" function_suite return [expression] By default, parameters have a positional behavior, and you need to inform them in the same order that they were defined. Example: Here is the simplest form of a Python function. This function takes a string as input parameter and prints it on standard screen. def printme( str ): "This prints a passed string into this function" print str return Calling a Function Defining a function only gives it a name, specifies the parameters that are to be included in the function, and structures the blocks of code. Once the basic structure of a function is finalized, you can execute it by calling it from another function or directly from the Python prompt. Following is the example to call printme() function: #!/usr/bin/python # Function definition is here def printme( str ): "This prints a passed string into this function" print str; return; # Now you can call printme function printme("I'm first call to user defined function!"); printme("Again second call to the same function"); This would produce following result: 3/22/2011 5:29 PM
- 178. Python - QuickGuide 14 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... I'm first call to user defined function! Again second call to the same function Python - Modules: A module allows you to logically organize your Python code. Grouping related code into a module makes the code easier to understand and use. A module is a Python object with arbitrarily named attributes that you can bind and reference. Simply, a module is a file consisting of Python code. A module can define functions, classes, and variables. A module can also include runnable code. Example: The Python code for a module named aname normally resides in a file named aname.py. Here's an example of a simple module, hello.py def print_func( par ): print "Hello : ", par return The import Statement: You can use any Python source file as a module by executing an import statement in some other Python source file. import has the following syntax: import module1[, module2[,... moduleN] When the interpreter encounters an import statement, it imports the module if the module is present in the search path. Asearch path is a list of directories that the interpreter searches before importing a module. Example: To import the module hello.py, you need to put the following command at the top of the script: #!/usr/bin/python # Import module hello import hello # Now you can call defined function that module as follows hellp.print_func("Zara") This would produce following result: Hello : Zara A module is loaded only once, regardless of the number of times it is imported. This prevents the module execution from happening over and over again if multiple imports occur. Opening and Closing Files: 3/22/2011 5:29 PM
- 179. Python - QuickGuide 15 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... The open Function: Before you can read or write a file, you have to open it using Python's built-in open() function. This function creates a file object which would be utilized to call other support methods associated with it. Syntax: file object = open(file_name [, access_mode][, buffering]) Here is paramters detail: file_name: The file_name argument is a string value that contains the name of the file that you want to access. access_mode: The access_mode determines the mode in which the file has to be opened ie. read, write append etc. A complete list of possible values is given below in the table. This is optional parameter and the default file access mode is read (r) buffering: If the buffering value is set to 0, no buffering will take place. If the buffering value is 1, line buffering will be performed while accessing a file. If you specify the buffering value as an integer greater than 1, then buffering action will be performed with the indicated buffer size. This is optional paramter. Here is a list of the different modes of opening a file: Modes Description r Opens a file for reading only. The file pointer is placed at the beginning of the file. This is the default mode. rb Opens a file for reading only in binary format. The file pointer is placed at the beginning of the file. This is the default mode. r+ Opens a file for both reading and writing. The file pointer will be at the beginning of the file. rb+ Opens a file for both reading and writing in binary format. The file pointer will be at the beginning of the file. w Opens a file for writing only. Overwrites the file if the file exists. If the file does not exist, creates a new file for writing. wb Opens a file for writing only in binary format. Overwrites the file if the file exists. If the file does not exist, creates a new file for writing. w+ Opens a file for both writing and reading. Overwrites the existing file if the file exists. If the file does not exist, creates a new file for reading and writing. wb+ Opens a file for both writing and reading in binary format. Overwrites the existing file if the file exists. If the file does not exist, creates a new file for reading and writing. a Opens a file for appending. The file pointer is at the end of the file if the file exists. That is, the file is in the append mode. If the file does not exist, it creates a new file for writing. ab Opens a file for appending in binary format. The file pointer is at the end of the file if the file exists. That is, the file is in the append mode. If the file does not exist, it creates a new file for writing. a+ Opens a file for both appending and reading. The file pointer is at the end of the file if the file exists. The file opens in the append mode. If the file does not exist, it creates a new file for reading and writing. ab+ Opens a file for both appending and reading in binary format. The file pointer is at the end of the file if the file exists. The file opens in the append mode. If the file does not exist, it creates a new file for reading and writing. 3/22/2011 5:29 PM
- 180. Python - QuickGuide 16 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... The file object atrributes: Once a file is opened and you have one file object, you can get various information related to that file. Here is a list of all attributes related to file object: Attribute Description file.closed Returns true if file is closed, false otherwise. file.mode Returns access mode with which file was opened. file.name Returns name of the file. file.softspace Returns false if space explicitly required with print, true otherwise. The close() Method: The close() method of a file object flushes any unwritten information and closes the file object, after which no more writing can be done. fileObject.close(); Reading and Writing Files: The write() Method: Syntax: fileObject.write(string); The read() Method: Syntax: fileObject.read([count]); File Positions: The tell() method tells you the current position within the file in other words, the next read or write will occur at that many bytes from the beginning of the file: The seek(offset[, from]) method changes the current file position. The offset argument indicates the number of bytes to be moved. The from argument specifies the reference position from where the bytes are to be moved. If from is set to 0, it means use the beginning of the file as the reference position and 1 means use the current position as the reference position and if it is set to 2 then the end of the file would be taken as the reference position. Renaming and Deleting Files: Syntax: os.rename(current_file_name, new_file_name) The remove() Method: 3/22/2011 5:29 PM
- 181. Python - QuickGuide 17 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Syntax: os.delete(file_name) Directories in Python: The mkdir() Method: You can use the mkdir() method of the os module to create directories in the current directory. You need to supply an argument to this method, which contains the name of the directory to be created. Syntax: os.mkdir("newdir") The chdir() Method: You can use the chdir() method to change the current directory. The chdir() method takes an argument, which is the name of the directory that you want to make the current directory. Syntax: os.chdir("newdir") The getcwd() Method: The getcwd() method displays the current working directory. Syntax: os.getcwd() The rmdir() Method: The rmdir() method deletes the directory, which is passed as an argument in the method. Before removing a directory, all the contents in it should be removed. Syntax: os.rmdir('dirname') Handling an exception: If you have some suspicious code that may raise an exception, you can defend your program by placing the suspicious code in a try: block. After the try: block, include an except: statement, followed by a block of code which handles the problem as elegantly as possible. Syntax: Here is simple syntax of try....except...else blocks: try: Do you operations here; 3/22/2011 5:29 PM
- 182. Python - QuickGuide 18 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... ...................... except ExceptionI: If there is ExceptionI, then execute this block. except ExceptionII: If there is ExceptionII, then execute this block. ...................... else: If there is no exception then execute this block. Here are few important points above the above mentioned syntax: A single try statement can have multiple except statements. This is useful when the try block contains statements that may throw different types of exceptions. You can also provide a generic except clause, which handles any exception. After the except clause(s), you can include an else-clause. The code in the else-block executes if the code in the try: block does not raise an exception. The else-block is a good place for code that does not need the try: block's protection. The except clause with no exceptions: You can also use the except statement with no exceptions defined as follows: try: Do you operations here; ...................... except: If there is any exception, then execute this block. ...................... else: If there is no exception then execute this block. The except clause with multiple exceptions: You can also use the same except statement to handle multiple exceptions as follows: try: Do you operations here; ...................... except(Exception1[, Exception2[,...ExceptionN]]]): If there is any exception from the given exception list, then execute this block. ...................... else: If there is no exception then execute this block. Standard Exceptions: Here is a list standard Exceptions available in Python: Standard Exceptions The try-finally clause: You can use a finally: block along with a try: block. The finally block is a place to put any code that must execute, whether the try-block raised an exception or not. The syntax of the try-finally statement is this: 3/22/2011 5:29 PM
- 183. Python - QuickGuide 19 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... try: Do you operations here; ...................... Due to any exception, this may be skipped. finally: This would always be executed. ...................... Argument of an Exception: An exception can have an argument, which is a value that gives additional information about the problem. The contents of the argument vary by exception. You capture an exception's argument by supplying a variable in the except clause as follows: try: Do you operations here; ...................... except ExceptionType, Argument: You can print value of Argument here... Raising an exceptions: You can raise exceptions in several ways by using the raise statement. The general syntax for the raise statement. Syntax: raise [Exception [, args [, traceback]]] User-Defined Exceptions: Python also allows you to create your own exceptions by deriving classes from the standard built-in exceptions. Here is an example related to RuntimeError. Here a class is created that is subclassed from RuntimeError. This is useful when you need to display more specific information when an exception is caught. In the try block, the user-defined exception is raised and caught in the except block. The variable e is used to create an instance of the class Networkerror. class Networkerror(RuntimeError): def __init__(self, arg): self.args = arg So once you defined above class, you can raise your exception as follows: try: raise Networkerror("Bad hostname") except Networkerror,e: print e.args Creating Classes: 3/22/2011 5:29 PM
- 184. Python - QuickGuide 20 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... The class statement creates a new class definition. The name of the class immediately follows the keyword class followed by a colon as follows: class ClassName: 'Optional class documentation string' class_suite The class has a documentation string which can be access via ClassName.__doc__. The class_suite consists of all the component statements, defining class members, data attributes, and functions. Creating instance objects: To create instances of a class, you call the class using class name and pass in whatever arguments its __init__ method accepts. "This would create first object of Employee class" emp1 = Employee("Zara", 2000) "This would create second object of Employee class" emp2 = Employee("Manni", 5000) Accessing attributes: You access the object's attributes using the dot operator with object. Class variable would be accessed using class name as follows: emp1.displayEmployee() emp2.displayEmployee() print "Total Employee %d" % Employee.empCount Built-In Class Attributes: Every Python class keeps following built-in attributes and they can be accessed using dot operator like any other attribute: __dict__ : Dictionary containing the class's namespace. __doc__ : Class documentation string, or None if undefined. __name__: Class name. __module__: Module name in which the class is defined. This attribute is "__main__" in interactive mode. __bases__ : A possibly empty tuple containing the base classes, in the order of their occurrence in the base class list. Destroying Objects (Garbage Collection): Python deletes unneeded objects (built-in types or class instances) automatically to free memory space. The process by which Python periodically reclaims blocks of memory that no longer are in use is termed garbage collection. Python's garbage collector runs during program execution and is triggered when an object's reference count reaches zero. An object's reference count changes as the number of aliases that point to it changes: 3/22/2011 5:29 PM
- 185. Python - QuickGuide 21 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... An object's reference count increases when it's assigned a new name or placed in a container (list, tuple, or dictionary). The object's reference count decreases when it's deleted with del, its reference is reassigned, or its reference goes out of scope. When an object's reference count reaches zero, Python collects it automatically. Class Inheritance: Instead of starting from scratch, you can create a class by deriving it from a preexisting class by listing the parent class in parentheses after the new class name: The child class inherits the attributes of its parent class, and you can use those attributes as if they were defined in the child class. A child class can also override data members and methods from the parent. Syntax: Derived classes are declared much like their parent class; however, a list of base classes to inherit from are given after the class name: class SubClassName (ParentClass1[, ParentClass2, ...]): 'Optional class documentation string' class_suite Overriding Methods: You can always override your parent class methods. One reason for overriding parent's methods is because you may want special or different functionality in your subclass. class Parent: # define parent class def myMethod(self): print 'Calling parent method' class Child(Parent): # define child class def myMethod(self): print 'Calling child method' c = Child() c.myMethod() # instance of child # child calls overridden method Base Overloading Methods: Following table lists some generic functionality that you can override in your own classes: SN Method, Description & Sample Call 1 __init__ ( self [,args...] ) Constructor (with any optional arguments) Sample Call : obj = className(args) 2 __del__( self ) Destructor, deletes an object Sample Call : dell obj 3 __repr__( self ) Evaluatable string representation Sample Call : repr(obj) 4 __str__( self ) Printable string representation Sample Call : str(obj) 3/22/2011 5:29 PM
- 186. Python - QuickGuide 22 of 28 5 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... __cmp__ ( self, x ) Object comparison Sample Call : cmp(obj, x) Overloading Operators: Suppose you've created a Vector class to represent two-dimensional vectors. What happens when you use the plus operator to add them? Most likely Python will yell at you. You could, however, define the __add__ method in your class to perform vector addition, and then the plus operator would behave as per expectation: #!/usr/bin/python class Vector: def __init__(self, a, b): self.a = a self.b = b def __str__(self): return 'Vector (%d, %d)' % (self.a, self.b) def __add__(self,other): return Vector(self.a + other.a, self.b + other.b) v1 = Vector(2,10) v2 = Vector(5,-2) print v1 + v2 Data Hiding: An object's attributes may or may not be visible outside the class definition. For these cases, you can name attributes with a double underscore prefix, and those attributes will not be directly visible to outsiders: #!/usr/bin/python class JustCounter: __secretCount = 0 def count(self): self.__secretCount += 1 print self.__secretCount counter = JustCounter() counter.count() counter.count() print counter.__secretCount A regular expression is a special sequence of characters that helps you match or find other strings or sets of strings, using a specialized syntax held in a pattern. Regular expressions are widely used in UNIX world. The module re provides full support for Perl-like regular expressions in Python. The re module raises the exception re.error if an error occurs while compiling or using a regular expression. We would cover two important functions which would be used to handle regular expressions. But a small thing first: There are various characters which would have special meaning when they are used in regular 3/22/2011 5:29 PM
- 187. Python - QuickGuide 23 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... expression. To avoid any confusion while dealing with regular expressions we would use Raw Strings as r'expression'. The match Function This function attempts to match RE pattern to string with optional flags. Here is the syntax for this function: re.match(pattern, string, flags=0) Here is the description of the parameters: Parameter Description pattern This is the regular expression to be matched. string This is the string which would be searched to match the pattern flags You can specifiy different flags using exclusive OR (|). These are modifiers which are listed in the table below. The re.match function returns a match object on success, None on failure. We would use group(num) or groups() function of match object to get matched expression. Match Object Methods Description group(num=0) This methods returns entire match (or specific subgroup num) groups() This method return all matching subgroups in a tuple (empty if there weren't any) The search Function This function search for first occurrence of RE pattern within string with optional flags. Here is the syntax for this function: re.string(pattern, string, flags=0) Here is the description of the parameters: Parameter Description pattern This is the regular expression to be matched. string This is the string which would be searched to match the pattern flags You can specifiy different flags using exclusive OR (|). These are modifiers which are listed in the table below. The re.search function returns a match object on success, None on failure. We would use group(num) or groups() function of match object to get matched expression. Match Object Methods Description group(num=0) This methods returns entire match (or specific subgroup num) groups() This method return all matching subgroups in a tuple (empty if there weren't any) 3/22/2011 5:29 PM
- 188. Python - QuickGuide 24 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Matching vs Searching: Python offers two different primitive operations based on regular expressions: match checks for a match only at the beginning of the string, while search checks for a match anywhere in the string (this is what Perl does by default). Search and Replace: Some of the most important re methods that use regular expressions is sub. Syntax: sub(pattern, repl, string, max=0) This method replace all occurrences of the RE pattern in string with repl, substituting all occurrences unless max provided. This method would return modified string. Regular-expression Modifiers - Option Flags Regular expression literals may include an optional modifier to control various aspects of matching. The modifier are specified as an optional flag. You can provide multiple modified using exclusive OR (|), as shown previously and may be represented by one of these: Modifier Description re.I Performs case-insensitive matching. re.L Interprets words according to the current locale.This interpretation affects the alphabetic group (w and W), as well as word boundary behavior (b and B). re.M Makes $ match the end of a line (not just the end of the string) and makes ^ match the start of any line (not just the start of the string). re.S Makes a period (dot) match any character, including a newline. re.U Interprets letters according to the Unicode character set. This flag affects the behavior of w, W, b, B. re.X Permits "cuter" regular expression syntax. It ignores whitespace (except inside a set [] or when escaped by a backslash), and treats unescaped # as a comment marker. Regular-expression patterns: Except for control characters, (+ ? . * ^ $ ( ) [ ] { } | ), all characters match themselves. You can escape a control character by preceding it with a backslash. Following table lists the regular expression syntax that is available in Python. Pattern Description ^ Matches beginning of line. $ Matches end of line. . Matches any single character except newline. Using m option allows it to match newline as well. [...] Matches any single character in brackets. 3/22/2011 5:29 PM
- 189. Python - QuickGuide 25 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... [^...] Matches any single character not in brackets re* Matches 0 or more occurrences of preceding expression. re+ Matches 0 or 1 occurrence of preceding expression. re{ n} Matches exactly n number of occurrences of preceding expression. re{ n,} Matches n or more occurrences of preceding expression. re{ n, m} Matches at least n and at most m occurrences of preceding expression. a| b Matches either a or b. (re) Groups regular expressions and remembers matched text. (?imx) Temporarily toggles on i, m, or x options within a regular expression. If in parentheses, only that area is affected. (?-imx) Temporarily toggles off i, m, or x options within a regular expression. If in parentheses, only that area is affected. (?: re) Groups regular expressions without remembering matched text. (?imx: re) Temporarily toggles on i, m, or x options within parentheses. (?-imx: re) Temporarily toggles off i, m, or x options within parentheses. (?#...) Comment. (?= re) Specifies position using a pattern. Doesn't have a range. (?! re) Specifies position using pattern negation. Doesn't have a range. (?> re) Matches independent pattern without backtracking. w Matches word characters. W Matches nonword characters. s Matches whitespace. Equivalent to [tnrf]. S Matches nonwhitespace. d Matches digits. Equivalent to [0-9]. D Matches nondigits. A Matches beginning of string. Z Matches end of string. If a newline exists, it matches just before newline. z Matches end of string. G Matches point where last match finished. b Matches word boundaries when outside brackets. Matches backspace (0x08) when inside brackets. B Matches nonword boundaries. n, t, etc. Matches newlines, carriage returns, tabs, etc. 1...9 Matches nth grouped subexpression. 10 Matches nth grouped subexpression if it matched already. Otherwise refers to the octal representation of a character code. Regular-expression Examples: 3/22/2011 5:29 PM
- 190. Python - QuickGuide 26 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Literal characters: Example python Description Match "python". Character classes: Example Description [Pp]ython Match "Python" or "python" rub[ye] Match "ruby" or "rube" [aeiou] Match any one lowercase vowel [0-9] Match any digit; same as [0123456789] [a-z] Match any lowercase ASCII letter [A-Z] Match any uppercase ASCII letter [a-zA-Z0-9] Match any of the above [^aeiou] Match anything other than a lowercase vowel [^0-9] Match anything other than a digit Special Character Classes: Example Description . Match any character except newline d Match a digit: [0-9] D Match a nondigit: [^0-9] s Match a whitespace character: [ trnf] S Match nonwhitespace: [^ trnf] w Match a single word character: [A-Za-z0-9_] W Match a nonword character: [^A-Za-z0-9_] Repetition Cases: Example Description ruby? Match "rub" or "ruby": the y is optional ruby* Match "rub" plus 0 or more ys ruby+ Match "rub" plus 1 or more ys d{3} Match exactly 3 digits d{3,} Match 3 or more digits d{3,5} Match 3, 4, or 5 digits Nongreedy repetition: This matches the smallest number of repetitions: Example Description 3/22/2011 5:29 PM
- 191. Python - QuickGuide 27 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... <.*> Greedy repetition: matches "<python>perl>" <.*?> Nongreedy: matches "<python>" in "<python>perl>" Grouping with parentheses: Example Description Dd+ No group: + repeats d (Dd)+ Grouped: + repeats Dd pair ([Pp]ython(, )?)+ Match "Python", "Python, python, python", etc. Backreferences: This matches a previously matched group again: Example Description ([Pp])ython&1ails Match python&rails or Python&Rails (['"])[^1]*1 Single or double-quoted string. 1 matches whatever the 1st group matched . 2 matches whatever the 2nd group matched, etc. Alternatives: Example Description python|perl Match "python" or "perl" rub(y|le)) Match "ruby" or "ruble" Python(!+|?) "Python" followed by one or more ! or one ? Anchors: This need to specify match position Example Description ^Python Match "Python" at the start of a string or internal line Python$ Match "Python" at the end of a string or line APython Match "Python" at the start of a string PythonZ Match "Python" at the end of a string bPythonb Match "Python" at a word boundary brubB B is nonword boundary: match "rub" in "rube" and "ruby" but not alone Python(?=!) Match "Python", if followed by an exclamation point Python(?!!) Match "Python", if not followed by an exclamation point Special syntax with parentheses: Example Description R(?#comment) Matches "R". All the rest is a comment R(?i)uby Case-insensitive while matching "uby" 3/22/2011 5:29 PM
- 192. Python - QuickGuide 28 of 28 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... R(?i:uby) Same as above rub(?:y|le)) Group only without creating 1 backreference Copyright © tutorialspoint.com 3/22/2011 5:29 PM
- 193. Python - Toolsand Utilities 1 of 3 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Tools/Utilities The standard library comes with a number of modules that can be used both as modules and as command-line utilities. The dis Module: The dis module is the Python disassembler. It converts byte codes to a format that is slightly more appropriate for human consumption. You can run the disassembler from the command line. It compiles the given script and prints the disassembled byte codes to the STDOUT. You can also use dis as a module. The dis function takes a class, method, function, or code object as its single argument. Example: #!/usr/bin/python import dis def sum(): vara = 10 varb = 20 sum = vara + varb print "vara + varb = %d" % sum # Call dis function for the function. dis.dis(sum) This would produce following result: 6 0 LOAD_CONST 3 STORE_FAST 1 (10) 0 (vara) 7 6 LOAD_CONST 9 STORE_FAST 2 (20) 1 (varb) 9 10 12 15 18 19 LOAD_FAST LOAD_FAST BINARY_ADD STORE_FAST 0 (vara) 1 (varb) 22 25 28 29 30 31 34 LOAD_CONST LOAD_FAST BINARY_MODULO PRINT_ITEM PRINT_NEWLINE LOAD_CONST RETURN_VALUE 3 ('vara + varb = %d') 2 (sum) 2 (sum) 0 (None) 3/22/2011 5:30 PM
- 194. Python - Toolsand Utilities 2 of 3 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... The pdb Module The pdb module is the standard Python debugger. It is based on the bdb debugger framework. You can run the debugger from the command line (type n [or next] to go to the next line and help to get a list of available commands): Example: Before you try to run pdb.py, set your path properly to Python lib directory. So let us try with above example sum.py: $pdb.py sum.py > /test/sum.py(3)<module>() -> import dis (Pdb) n > /test/sum.py(5)<module>() -> def sum(): (Pdb) n >/test/sum.py(14)<module>() -> dis.dis(sum) (Pdb) n 6 0 LOAD_CONST 3 STORE_FAST 7 9 10 6 LOAD_CONST 9 STORE_FAST 1 (10) 0 (vara) 2 (20) 1 (varb) 12 15 18 19 LOAD_FAST LOAD_FAST BINARY_ADD STORE_FAST 0 (vara) 1 (varb) 22 25 28 29 30 31 34 LOAD_CONST LOAD_FAST BINARY_MODULO PRINT_ITEM PRINT_NEWLINE LOAD_CONST RETURN_VALUE 3 ('vara + varb = %d') 2 (sum) 2 (sum) 0 (None) --Return-> /test/sum.py(14)<module>()->None -v dis.dis(sum) (Pdb) n --Return-> <string>(1)<module>()->None (Pdb) The profile Module: The profile module is the standard Python profiler. You can run the profiler from the command line: Example: Let us try to profile following program: #!/usr/bin/python 3/22/2011 5:30 PM
- 195. Python - Toolsand Utilities 3 of 3 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... vara = 10 varb = 20 sum = vara + varb print "vara + varb = %d" % sum Now try running cProfile.py over this file sum.py as follows: $cProfile.py sum.py vara + varb = 30 4 function calls in 0.000 CPU seconds Ordered by: standard name ncalls 1 1 1 1 tottime 0.000 0.000 0.000 0.000 percall 0.000 0.000 0.000 0.000 cumtime 0.000 0.000 0.000 0.000 percall filename:lineno 0.000 <string>:1(<module>) 0.000 sum.py:3(<module>) 0.000 {execfile} 0.000 {method ......} The tabnanny Module The tabnanny module checks Python source files for ambigous indentation. If a file mixes tabs and spaces in a way that throws off indentation, no matter what tab size you're using, the nanny complains: Example: Let us try to profile following program: #!/usr/bin/python vara = 10 varb = 20 sum = vara + varb print "vara + varb = %d" % sum If you would try a correct file with tabnanny.py then it won't complain as follows: $tabnanny.py -v sum.py 'sum.py': Clean bill of health. Copyright © tutorialspoint.com 3/22/2011 5:30 PM
- 196. Python - UsefulResources 1 of 1 http://www.tutorialspoint.com/cgi-bin/printversion.cgi?tutorial=python&f... Copyright © tutorialspoint.com Python - Useful Resources If you want to list down your website, book or any other resource on this page then please contact at [email protected] Python.org - Official Python site. Find a complete list of all documentation, installation, tutorials, news etc. Web Programming in Python - This topic guide attempts to cover every aspect of programming Web applications (both clients and servers) using Python. Starship - ... a Home for Pythonistas This is not the official Python Language Website! The Jython Project - Jython is an implementation of the high-level, dynamic, object-oriented language Python written in 100% Pure Java, and seamlessly integrated with the Java platform. PythonWare - PythonWare site provides useful software to the Python community under the PythonWare and effbot.org brands. Wing IDE - Wing IDE is a powerful integrated development environment (IDE) for the Python programming language. python.vim - Enhanced version of the python syntax highlighting script. Python XML Tools - The Python XML Tools collection is built on top of PyXML and features two GTK widgets:XmlTree and XmlEditor. Python and XML - This Topic Guide links to documentation and code for handling XML in Python. Think Python - Free book on python. How to think like a computer scientist, by Allen Downey? Copyright © tutorialspoint.com 3/22/2011 5:30 PM