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

7.5 Extras

Here are some ideas for you to add to the projects in this chapter.

7.5.1 Markdown cells with dates and data source information

A minor feature of an inspection notebook is some identification of the date, time, and source of the data. It’s sometimes clear from the context what the data source is; there may, for example, be an obvious path to the data.

However, in many cases, it’s not perfectly clear what file is being inspected or how it was acquired. As a general solution, any processing application should produce a log. In some cases, a metadata file can include the details of the processing steps.

This additional metadata on the source and processing steps can be helpful when reviewing a data inspection notebook or sharing a preliminary inspection of data with others. In many cases, this extra data is pasted into ordinary markdown cells. In other cases, this data may be the result of scanning a log file for key INFO lines that summarize processing.

...