Book Image

Python Real-World Projects

By : Steven F. Lott
5 (1)
Book Image

Python Real-World Projects

5 (1)
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)
19
Index

3.1 Description

Analysts and decision-makers need to acquire data for further analysis. In many cases, the data is available in CSV-formatted files. These files may be extracts from databases or downloads from web services.

For testing purposes, it’s helpful to start with something relatively small. Some of the Kaggle data sets are very, very large, and require sophisticated application design. One of the most fun small data sets to work with is Anscombe’s Quartet. This can serve as a test case to understand the issues and concerns in acquiring raw data.

We’re interested in a few key features of an application to acquire data:

  • When gathering data from multiple sources, it’s imperative to convert it to a common format. Data sources vary, and will often change with software upgrades. The acquisition process needs to be flexible with respect to data sources and avoid assumptions about formats.

  • A CLI application permits a variety of automation possibilities....