What does zedr/clean-code-python do?

Dieses Projekt ist ein Leitfaden für sauberen Python-Code und eine Ressource für Refactoring. Es bietet eine Sammlung von Prinzipien der Software-Handwerkskunst und Beispiele, die darauf ausgelegt sind, die Lesbarkeit und Wartbarkeit von Python-Quellcode zu verbessern.

What are the main features of zedr/clean-code-python?

The main features of zedr/clean-code-python are: Clean Code Guides, Clean Coding Standards, Interface-Driven Abstraction, Design Patterns, Python Patterns, Pattern-Based Organization, Code Duplication Reduction, Code Refactoring Guidelines.

What are some open-source alternatives to zedr/clean-code-python?

Open-source alternatives to zedr/clean-code-python include: piotrplenik/clean-code-php — This project is a PHP clean code guide and software architecture reference. It provides a set of standards, naming… juancrg90/clean-code-notes — Clean-Code-Notes is a clean code study guide and a collection of detailed notes based on professional software… felipe-augusto/clean-code-javascript — This project is a comprehensive guide and set of engineering standards for writing readable, maintainable, and… ryanmcdermott/clean-code-javascript — This project is a collection of engineering guidelines and best practices for writing readable and maintainable… labs42io/clean-code-typescript — This project is a set of software engineering standards and architectural patterns for writing maintainable and… alexeymezenin/laravel-best-practices — This project is a comprehensive guide to architectural standards and coding patterns for developing maintainable…

Clean Code Python - Lesbaren und wartbaren Py…

Clean Code Python - Lesbaren und wartbaren Py… | Awesome Repos

Features

Clean Code Guides - Offers a comprehensive guide to software craftsmanship and clean code principles specifically for Python developers.
Clean Coding Standards - Provides a comprehensive collection of craftsmanship principles and examples for writing clean, maintainable Python code.
Interface-Driven Abstraction - Guides the definition of stable boundaries between high-level modules and low-level implementations to decouple dependencies.
Design Patterns - Uses industry-standard design patterns to solve recurring software design problems and improve maintainability.
Python Patterns - Guides the structuring of Python applications using Pythonic architectural patterns to reduce technical debt.
Pattern-Based Organization - Demonstrates how to organize source code using industry-standard design patterns to ensure maintainability.
Code Duplication Reduction - Provides techniques for eliminating redundant logic through the creation of shared abstractions.
Code Refactoring Guidelines - Provides engineering guidelines for restructuring Python code to optimize naming, reduce duplication, and improve function modularity.
Modular Function Design - Demonstrates how to break complex functions into smaller, independent, and reusable units.
Naming Schemas - Provides specific rules for variable and function naming to eliminate mental mapping and increase clarity.
Python Coding Standards - Provides technical references and guidelines for refactoring Python code using clean code standards.
SOLID Principles - Implements the five core SOLID design principles to create extensible and maintainable software.
Single Responsibility Principles - Provides guidance on decomposing logic into single-purpose units based on the single responsibility principle.
Naming Conventions - Offers guidelines for choosing intention-revealing names for variables and functions to improve readability.
Variable Naming Conventions - Choose pronounceable and searchable names for variables to increase clarity and remove the need for mental mapping.
Abstraction Level Management - Explains how to group function calls by complexity levels to keep logic flow linear and readable.
Side Effect Management - Teaches how to centralize operations that modify global state to prevent unpredictable system behavior.
Clean Code and Principles - Collection of clean code principles applied to Python.
Python Programming Resources - Clean code concepts adapted for Python.

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