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cover of the book Python Real-World Projects: Craft your Python portfolio with deployable applications

Ebook: Python Real-World Projects: Craft your Python portfolio with deployable applications

Author: Steven F. Lott

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02.03.2024
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Develop Python applications using an enterprise-based approach with unit and acceptance tests by following agile methods to create a minimum viable product (MVP) and iteratively add features
Key Features

Master Python and related technologies by working on 12 hands-on projects

Accelerate your career by building a personal project portfolio

Explore data acquisition, preparation, and analysis applications

Book Description

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.

What you will learn

Explore core deliverables for an application including documentation and test cases

Discover approaches to data acquisition such as file processing, RESTful APIs, and SQL queries

Create a data inspection notebook to establish properties of source data

Write applications to validate, clean, convert, and normalize source data

Use foundational graphical analysis techniques to visualize data

Build basic
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