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

6.2 Approach

We’ll take some guidance from the C4 model ( https://c4model.com) when looking at our approach.

  • Context: For this project, the context diagram has two use cases: acquire and inspect

  • Containers: There’s one container for the various applications: the user’s personal computer

  • Components: There are two significantly different collections of software components: the acquisition program and inspection notebooks

  • Code: We’ll touch on this to provide some suggested directions

A context diagram for this application is shown in Figure 6.1.

Figure 6.1: Context Diagram
Figure 6.1: Context Diagram

The data analyst will use the CLI to run the data acquisition program. Then, the analyst will use the CLI to start a Jupyter Lab server. Using a browser, the analyst can then use Jupyter Lab to inspect the data.

The components fall into two overall categories. The component diagram is shown in Figure 6.2.

Figure 6.2: Component diagram
Figure 6.2: Component diagram

The diagram shows the interfaces...