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modular-code

modular-code

github.com/parcadeiDevelopment3.9k567 installsUpdated 39w ago
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About modular-code

modular-code is a skill for organizing maintainable Python code, intended for developers and AI-assisted coding workflows. It offers file-sizing guidance, ways to identify module boundaries, and an incremental refactoring process.

Key features

  1. 01Python file-size guidelines
  2. 02Criteria for splitting modules
  3. 03Patterns for package structure
  4. 04Naming and organization practices
  5. 05Incremental refactoring steps

Use cases

  1. 01Split an oversized Python module
  2. 02Separate unrelated code concerns
  3. 03Refactor files while checking tests

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/parcadei/continuous-claude-v3 --skill modular-code

After installing, type/modular-codein Claude Code to confirm it loaded.

Details

From the project README

Modular Code Organization

Write modular Python code with files sized for maintainability and AI-assisted development.

File Size Guidelines

LinesStatusAction
150-500OptimalSweet spot for AI code editors and human comprehension
500-1000LargeLook for natural split points
1000-2000Too largeRefactor into focused modules
2000+CriticalMust 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

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