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

11.5 Extras

Here are some ideas for you to add to these projects.

11.5.1 Using a SQL database

Using a SQL database for cleaned analytical data can be part of a comprehensive database-centric data warehouse. The implementation, when based on Pydantic, requires the native Python classes as well as the ORM classes that map to the database.

It also requires some care in handling repeated queries for enterprise data. In the ordinary file system, file names can have processing dates. In the database, this is more commonly assigned to an attribute of the data. This means multiple time periods of data occupy a single table, distinguished by the ”as-of” date for the rows.

A common database optimization is to provide a “time dimension” table. For each date, the associated date of the week, fiscal weeks, month, quarter, and year is provided as an attribute. Using this table saves computing any attributes of a date. It also allows the enterprise fiscal calendar to...