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Python Real-World Projects

Python Real-World Projects

By : Steven F. Lott
4.4 (5)
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Python Real-World Projects

Python Real-World Projects

4.4 (5)
By: Steven F. Lott

Overview of this book

In today's competitive job market, a project portfolio often outshines a traditional resume. Python Real-World Projects empowers you to get to grips with crucial Python concepts while building complete modules and applications. With two dozen meticulously designed projects to explore, this book will help you showcase your Python mastery and refine your skills. Tailored for beginners with a foundational understanding of class definitions, module creation, and Python's inherent data structures, this book is your gateway to programming excellence. You’ll learn how to harness the potential of the standard library and key external projects like JupyterLab, Pydantic, pytest, and requests. You’ll also gain experience with enterprise-oriented methodologies, including unit and acceptance testing, and an agile development approach. Additionally, you’ll dive into the software development lifecycle, starting with a minimum viable product and seamlessly expanding it to add innovative features. By the end of this book, you’ll be armed with a myriad of practical Python projects and all set to accelerate your career as a Python programmer.
Table of Contents (20 chapters)
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19
Index

4.3 Summary

This chapter’s projects have shown examples of the following features of a data acquisition application:

  • Web API integration via the requests package. We’ve used the Kaggle API as an example of a RESTful API that provides data for download and analysis.

  • Parsing an HTML web page using the Beautiful Soup package.

  • Adding features to an existing application and extending the test suite to cover these new alternative data sources.

A challenging part of both of these projects is creating a suite of acceptance tests to describe the proper behavior. Pragmatically, a program without automated tests cannot be trusted. The tests are every bit as important as the code they’re exercising.

In some enterprises, the definition of done is breezy and informal. There may be a presentation or an internal memo or a whitepaper that describes the desired software. Formalizing these concepts into tangible test cases is often a significant effort. Achieving agreements can become...

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