What is the primary purpose of the Python Practices skill?

It provides specialized guidance for writing, testing, and documenting Python code following industry standards and OAPS-specific workflows.

How do I load specific Python references with this skill?

You can use the 'oaps skill context python-practices --references ' command to load specific dynamic context into your Claude session.

Can this skill help with Python packaging and distribution?

Yes, it includes references and guidance for modern Python packaging methods and distribution best practices.

Does it support different Python testing frameworks?

Yes, it covers popular Python testing frameworks and provides best practices for unit, integration, and end-to-end testing.

How does the workflow work within this skill?

The skill uses a 5-step workflow: gathering context, identifying references, loading dynamic context, reviewing allowed commands, and following the selected workflow.

Python Development Best Practices

Name: Python Development Best Practices
Author: tbhb

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Security & Testing

Standardizes Python development workflows by providing expert guidance on coding standards, testing, and documentation.

About

The Python Practices skill integrates with the Overengineered Agentic Planning System (OAPS) to provide a structured approach to Python development. It assists developers in maintaining high-quality codebases by offering progressively-disclosed references on coding standards, testing frameworks, documentation tools, and packaging methods. By leveraging dynamic context loading and predefined workflows, it ensures that Python projects are built using industry-standard patterns, robust architectural principles, and consistent style guidelines.

Key Features

Dynamic context loading for domain-specific Python libraries and tools
Standardized Python coding and PEP 8 style guide enforcement
Comprehensive testing framework integration and implementation strategies
0 GitHub stars
Expert guidance on Python packaging, distribution, and API design
Structured workflows for refactoring and maintaining legacy Python code

Use Cases

Establishing robust testing and CI/CD workflows for new Python applications
Generating high-quality documentation and professional API specifications
Refactoring existing Python projects to meet modern architectural and style standards

About

Key Features

Dynamic context loading for domain-specific Python libraries and tools
Standardized Python coding and PEP 8 style guide enforcement
Comprehensive testing framework integration and implementation strategies
0 GitHub stars
Expert guidance on Python packaging, distribution, and API design
Structured workflows for refactoring and maintaining legacy Python code

Use Cases

Establishing robust testing and CI/CD workflows for new Python applications
Generating high-quality documentation and professional API specifications
Refactoring existing Python projects to meet modern architectural and style standards