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