Python | Set 4 (Dictionary, Keywords in Python)
Last Updated :
11 Sep, 2023
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In the previous two articles (Set 2 and Set 3), we discussed the basics of python. In this article, we will learn more about python and feel the power of python.
Dictionary in Python
In python, the dictionary is similar to hash or maps in other languages. It consists of key-value pairs. The value can be accessed by a unique key in the dictionary. (Before python 3.7 dictionary used to be unordered meant key-value pairs are not stored in the order they are inputted into the dictionary but from python 3.7 they are stored in order like the first element will be stored in the first position and the last at the last position.)
# Create a new dictionary
d = dict() # or d = {}
# Add a key - value pairs to dictionary
d['xyz'] = 123
d['abc'] = 345
# print the whole dictionary
print (d)
# print only the keys
print (d.keys())
# print only values
print (d.values())
# iterate over dictionary
for i in d :
print ("%s %d" %(i, d[i]))
# another method of iteration
for index, key in enumerate(d):
print (index, key, d[key])
# check if key exist
print ('xyz' in d)
# delete the key-value pair
del d['xyz']
# check again
print ("xyz" in d)
32
1
# Create a new dictionary 2
d = dict() # or d = {}3
4
# Add a key - value pairs to dictionary5
d['xyz'] = 1236
d['abc'] = 3457
8
# print the whole dictionary9
print (d)10
11
# print only the keys12
print (d.keys())13
14
# print only values15
print (d.values())16
17
# iterate over dictionary 18
for i in d :19
print ("%s %d" %(i, d[i]))20
21
# another method of iteration22
for index, key in enumerate(d):23
print (index, key, d[key])24
25
# check if key exist26
print ('xyz' in d)27
28
# delete the key-value pair29
del d['xyz']30
31
# check again 32
print ("xyz" in d)Output:
{'xyz': 123, 'abc': 345}
['xyz', 'abc']
[123, 345]
xyz 123
abc 345
0 xyz 123
1 abc 345
True
False
Time Complexity: O(1)
Auxiliary Space: O(n)
break, continue, pass in Python
- break: takes you out of the current loop.
- continue: ends the current iteration in the loop and moves to the next iteration.
- pass: The pass statement does nothing. It can be used when a statement is required. syntactically but the program requires no action.
It is commonly used for creating minimal classes.
# Function to illustrate break in loop
def breakTest(arr):
for i in arr:
if i == 5:
break
print (i)
# For new line
print("")
# Function to illustrate continue in loop
def continueTest(arr):
for i in arr:
if i == 5:
continue
print (i)
# For new line
print("")
# Function to illustrate pass
def passTest(arr):
pass
# Driver program to test above functions
# Array to be used for above functions:
arr = [1, 3 , 4, 5, 6 , 7]
# Illustrate break
print ("Break method output")
breakTest(arr)
# Illustrate continue
print ("Continue method output")
continueTest(arr)
# Illustrate pass- Does nothing
passTest(arr)
Output:
Break method output 1 3 4 Continue method output 1 3 4 6 7
Time complexity: O(n), where n is the length of the array arr.
Auxiliary space: O(1), since the space used is constant and does not depend on the size of the input.
map, filter, lambda
- map: The map() function applies a function to every member of iterable and returns the result. If there are multiple arguments, map() returns a list consisting of tuples containing the corresponding items from all iterables.
- filter: It takes a function returning True or False and applies it to a sequence, returning a list of only those members of the sequence for which the function returned True.
- lambda: Python provides the ability to create a simple (no statements allowed internally) anonymous inline function called lambda function. Using lambda and map you can have two for loops in one line.
# python program to test map, filter and lambda
items = [1, 2, 3, 4, 5]
#Using map function to map the lambda operation on items
cubes = list(map(lambda x: x**3, items))
print(cubes)
# first parentheses contains a lambda form, that is
# a squaring function and second parentheses represents
# calling lambda
print( (lambda x: x**2)(5))
# Make function of two arguments that return their product
print ((lambda x, y: x*y)(3, 4))
#Using filter function to filter all
# numbers less than 5 from a list
number_list = range(-10, 10)
less_than_five = list(filter(lambda x: x < 5, number_list))
print(less_than_five)
20
1
# python program to test map, filter and lambda2
items = [1, 2, 3, 4, 5]3
4
#Using map function to map the lambda operation on items5
cubes = list(map(lambda x: x**3, items))6
print(cubes)7
8
# first parentheses contains a lambda form, that is 9
# a squaring function and second parentheses represents10
# calling lambda11
print( (lambda x: x**2)(5))12
13
# Make function of two arguments that return their product14
print ((lambda x, y: x*y)(3, 4))15
16
#Using filter function to filter all 17
# numbers less than 5 from a list18
number_list = range(-10, 10)19
less_than_five = list(filter(lambda x: x < 5, number_list))20
print(less_than_five)Output:
[1, 8, 27, 64, 125] 25 12 [-10, -9, -8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4]
For more clarity about map, filter, and lambda, you can have a look at the below example:
# code without using map, filter and lambda
# Find the number which are odd in the list
# and multiply them by 5 and create a new list
# Declare a new list
x = [2, 3, 4, 5, 6]
# Empty list for answer
y = []
# Perform the operations and print the answer
for v in x:
if v % 2:
y += [v*5]
print(y)
16
1
# code without using map, filter and lambda2
3
# Find the number which are odd in the list4
# and multiply them by 5 and create a new list5
6
# Declare a new list7
x = [2, 3, 4, 5, 6]8
9
# Empty list for answer10
y = []11
12
# Perform the operations and print the answer13
for v in x:14
if v % 2:15
y += [v*5]16
print(y)Output:
[15, 25]
The same operation can be performed in two lines using map, filter, and lambda as :
# above code with map, filter and lambda
# Declare a list
x = [2, 3, 4, 5, 6]
# Perform the same operation as in above post
y = list(map(lambda v: v * 5, filter(lambda u: u % 2, x)))
print(y)
8
1
# above code with map, filter and lambda2
3
# Declare a list4
x = [2, 3, 4, 5, 6]5
6
# Perform the same operation as in above post7
y = list(map(lambda v: v * 5, filter(lambda u: u % 2, x)))8
print(y)Output:
[15, 25]
