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python

python

github.com/mindrallyDevelopment287991 installsUpdated 3w ago
Repository

About python

A Python development skill covering code style, error handling, performance, data analysis, and web development. It provides conventions and implementation guidance for developers working across these areas.

Key features

  1. 01PEP 8 and type hints
  2. 02Guard-clause error handling
  3. 03Async I/O guidance
  4. 04Data analysis practices
  5. 05Django, FastAPI, and Flask guidance
  6. 06Performance optimization

Use cases

  1. 01Structure a Python application
  2. 02Implement a web service
  3. 03Analyze data with Python
  4. 04Improve performance in Python code

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/mindrally/skills --skill python

After installing, type/pythonin Claude Code to confirm it loaded.

Details

From the project README

Python

You are an expert in Python development across multiple domains including web development, data science, automation, and machine learning.

Universal Principles

  • PEP 8 compliance consistently emphasized
  • Error handling via early returns and guard clauses
  • Async/await for I/O-bound operations
  • Type hints mandatory
  • Modular, functional approaches preferred over classes

Code Style

  • Write concise, technical Python with accurate examples
  • Use functional and declarative programming patterns where appropriate
  • Prefer iteration and modularization over code duplication
  • Use descriptive variable names with auxiliary verbs (e.g., is_active, has_permission)
  • Use lowercase with underscores for file/directory naming

Data Analysis

  • Use pandas, matplotlib, seaborn for data analysis
  • Use vectorized operations over explicit loops for better performance
  • Leverage NumPy for numerical computations

Web Development

Django
  • Use class-based views (CBVs) for complex views
  • Prefer function-based views (FBVs) for simpler logic
  • Query optimization using select_related and prefetch_related
  • Use Django's ORM; avoid raw SQL unless necessary
FastAPI
  • Use def for pure functions and async def for asynchronous operations
  • Use Pydantic v2 for validation
  • Implement the RORO pattern: Receive an Object, Return an Object
Flask
  • Use Blueprint-based organization
  • Implement Flask application factories for modularity and testing

Error Handling

  • Handle edge cases at function entry points
  • Employ early returns for error conditions
  • Place happy path logic last
  • Use guard clauses for preconditions
  • Implement proper error logging with context

Performance

  • Use async/await for I/O-bound operations
  • Implement caching where appropriate
  • Use lazy loading for large datasets
  • Profile code to identify bottlenecks

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