T�tulo: Organizing Python: Modules, Packages, and Project Structure: A Comprehensive Guide for Structuring, Managing, and Distributing Your Python Projects
Editor: Independently published
Fecha de publicaci�n: 2025
Idioma: Ingl�s
ISBN 13: 9798288416705
Encuadernaci�n: Encuadernaci�n de tapa blanda
Estado: As New

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Sinopsis

What You Will Learn in This Book

Master the fundamentals of Python code organization, understanding why a structured approach is crucial for readability, maintainability, reusability, and collaborative development.
Effectively utilize Python modules to break down large programs, reuse code, and manage namespaces, along with best practices for their creation and design.
Implement Python packages to structure larger projects hierarchically, avoiding naming conflicts and streamlining complex application development.
Navigate Python's module search path (sys.path) to ensure your custom modules and packages are correctly discovered and imported.
Apply best practices for writing clean, maintainable modules and packages, including naming conventions, docstrings, minimizing side effects, and avoiding common pitfalls like circular imports.
Leverage key standard library modules to efficiently handle common programming tasks, from file system interactions to data manipulation and more.
Differentiate between absolute and relative imports, understanding when and how to use each for clear and robust package importing.
Optimize the use of __init__.py files for package initialization, API exposure, and internal module aggregation.
Create and manage isolated Python environments using venv or conda to prevent dependency conflicts and ensure project reproducibility.
Manage project dependencies effectively using pip and requirements.txt files, and gain an introduction to modern tools like pyproject.toml.
Design and implement common project structures for various Python applications, including web applications, data science projects, and libraries.
Build installable Python packages using setuptools and pyproject.toml, preparing your code for wider distribution.
Publish your Python packages to PyPI, making your creations easily accessible to others in the Python community.
Identify and avoid common anti-patterns in code organization, leading to more robust and scalable applications.
Integrate code quality tools such as linters, formatters, and import sorters into your development workflow for consistent and high-quality code.

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