modular-code

# Modular Code Organization Write modular Python code with files sized for maintainability and AI-assisted development. ## File Size Guidelines | Lines | Status | Action | |-------|--------|--------| | 150-500 | Optimal | Sweet spot for AI code editors and human comprehension | | 500-1000 | Large | Look for natural split points | | 1000-2000 | Too large | Refactor into focused modules | | 2000+ | Critical | Must split - causes tooling issues and cognitive overload | ## When to Split Split when ANY of these apply: - File exceeds 500 lines - Multiple unrelated concerns in same file - Scroll fatigue finding functions - Tests for the file are hard to organize - AI tools truncate or miss context ## How to Split ### Natural Split Points 1. **By domain concept**: `auth.py` → `auth/login.py`, `auth/tokens.py`, `auth/permissions.py` 2. **By abstraction layer**: Separate interface from implementation 3. **By data type**: Group operations on related data structures 4. **By I/O boundary**: Isolate database, API, file operations ### Package Structure ``` feature/ ├── __init__.py # Keep minimal, just exports ├── core.py # Main logic (under 500 lines) ├── models.py # Data structures ├── handlers.py # I/O and side effects └── utils.py # Pure helper functions ``` ## DO - Use meaningful module names (`data_storage.py` not `utils2.py`) - Keep `__init__.py` files minimal or empty - Group related functions together - Isolate pure functions from side effects - Use snake_case for module names ## DON'T - Split files arbitrarily by line count alone - Create single-function modules - Over-modularize into "package hell" - Use dots or special characters in module names - Hide dependencies with "magic" imports ## Refactoring Large Files When splitting an existing large file: 1. **Identify clusters**: Find groups of related functions 2. **Extract incrementally**: Move one cluster at a time 3. **Update imports**: Fix all import statements 4. **Run tests**: Verify nothing broke after each move 5. **Document**: Update any references to old locations ## Current Codebase Candidates Files over 2000 lines that need attention: - Math compute modules (scipy, mpmath, numpy) - domain-specific, may be acceptable - patterns.py - consider splitting by pattern type - memory_backfill.py - consider splitting by operation type ## Sources - [The Hitchhiker's Guide to Python](https://docs.python-guide.org/writing/structure/) - [Python Project Best Practices - Dagster](https://dagster.io/blog/python-project-best-practices) - [Right-Sizing Python Files for AI Editors](https://medium.com/@eamonn.faherty_58176/right-sizing-your-python-files-the-150-500-line-sweet-spot-for-ai-code-editors-340d550dcea4) - [PEP 8 Style Guide](https://peps.python.org/pep-0008/)