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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

Chapter 4
Data Acquisition Features: Web APIs and Scraping

Data analysis often works with data from numerous sources, including databases, web services, and files prepared by other applications. In this chapter, you will be guided through two projects to add additional data sources to the baseline application from the previous chapter. These new sources include a web service query, and scraping data from a web page.

This chapter’s projects cover the following essential skills:

  • Using the requests package for Web API integration. We’ll look at the Kaggle API, which requires signing up to create an API token.

  • Using the Beautiful Soup package to parse an HTML web page.

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

It’s important to recognize this application has a narrow focus on data acquisition. In later chapters, we’ll validate the data and convert it to a more useful form. This reflects...

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