kdaquila-structure-lint 7.0.0

Opinionated Python project structure and code quality linter

kdaquila-structure-lint

Opinionated Python project structure and code quality linter.

Overview

kdaquila-structure-lint is a Python linter that enforces code quality and project structure conventions. It provides three validators that can be enabled independently:

• Line Limits Validator (enabled by default) - Enforces maximum line count per file
• One-Per-File Validator (enabled by default) - Ensures single function/class per file
• Structure Validator (opt-in) - Enforces opinionated folder structure rules

Installation

Install from PyPI using pip:

pip install kdaquila-structure-lint

For development installations:

git clone https://github.com/kdaquila/kdaquila-structure-lint.git
cd kdaquila-structure-lint
pip install -e ".[dev]"

Quick Start

Run the linter in your project directory:

structure-lint

The tool will:

1. Auto-detect your project root by searching for pyproject.toml
2. Load configuration from [tool.structure-lint] section (or use defaults)
3. Run all enabled validators
4. Report any violations with clear error messages

Basic Example

Add configuration to your pyproject.toml:

[tool.structure-lint]
enabled = true

[tool.structure-lint.validators]
line_limits = true
one_per_file = true
structure = false  # Opt-in only

Run the linter:

structure-lint

Features

Line Limits Validator

Enforces a maximum number of lines per Python file to encourage modular, maintainable code.

Default: 150 lines per file

Configuration:

[tool.structure-lint]
search_paths = ["src"]  # Applies to all validators

[tool.structure-lint.line_limits]
max_lines = 150

Example Output:

============================================================
Running line limit validation...
============================================================
✗ src/features/data_processing/processor.py: 187 lines (exceeds 150 line limit)
✗ src/analysis/report_generator.py: 203 lines (exceeds 150 line limit)

2 files exceed the line limit

One-Per-File Validator

Ensures each Python file contains at most one top-level function or class definition, promoting better organization and discoverability.

Configuration:

[tool.structure-lint]
search_paths = ["src"]  # Applies to all validators

Example Output:

============================================================
Running one-per-file validation...
============================================================
✗ src/functions/helpers.py: 3 definitions (expected 1)
  - format_date (function)
  - parse_date (function)
  - DateFormatter (class)

1 file violates one-per-file rule

Structure Validator (Opt-in)

Enforces an opinionated folder structure based on feature-driven development principles. This validator is disabled by default as it's highly prescriptive.

Enable with:

[tool.structure-lint.validators]
structure = true

See docs/validators.md for detailed structure rules.

Configuration

Minimal Configuration

Create a minimal configuration in your pyproject.toml:

[tool.structure-lint]
enabled = true

This uses all default settings with line_limits and one_per_file enabled.

Full Configuration

See all available options:

[tool.structure-lint]
enabled = true
search_paths = ["src"]  # Applies to all validators

[tool.structure-lint.validators]
structure = false        # Opt-in (default: disabled)
line_limits = true       # Default: enabled
one_per_file = true      # Default: enabled

[tool.structure-lint.line_limits]
max_lines = 150

[tool.structure-lint.structure]
folder_depth = 2
standard_folders = ["_types", "_functions", "_constants", "_tests", "_errors", "_classes"]
files_allowed_anywhere = ["__init__.py"]
ignored_folders = ["__pycache__", ".mypy_cache", ".pytest_cache", ".ruff_cache", ".hypothesis", ".tox", ".coverage", "*.egg-info"]

For detailed configuration options, see docs/configuration.md.

Example Configurations

Example configurations are available in the docs/examples/ directory:

• minimal_config.toml - Bare minimum configuration
• full_config.toml - All options with defaults
• custom_structure.toml - Custom structure validation setup

Command-Line Interface

Basic Usage

structure-lint                    # Run in current directory
structure-lint --verbose          # Show detailed output
structure-lint --version          # Show version
structure-lint --help             # Show help message

Advanced Options

# Specify project root explicitly
structure-lint --project-root /path/to/project

# Use a specific pyproject.toml file
structure-lint --config /path/to/pyproject.toml

# Verbose output (shows project root and detailed progress)
structure-lint --verbose

Exit Codes

The CLI returns different exit codes for automation and CI/CD integration:

• 0 - All validations passed
• 1 - One or more validations failed
• 2 - Configuration error or unexpected error

Usage in CI/CD

GitHub Actions

Add to your .github/workflows/ci.yml:

name: CI

on: [push, pull_request]

jobs:
  lint:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - uses: actions/setup-python@v4
        with:
          python-version: "3.11"
      - name: Install dependencies
        run: |
          pip install kdaquila-structure-lint
      - name: Run structure linter
        run: structure-lint

Pre-commit Hook

Add to your .pre-commit-config.yaml:

repos:
  - repo: local
    hooks:
      - id: structure-lint
        name: structure-lint
        entry: structure-lint
        language: system
        pass_filenames: false

GitLab CI

Add to your .gitlab-ci.yml:

structure-lint:
  image: python:3.11
  script:
    - pip install kdaquila-structure-lint
    - structure-lint

Development

Running Tests

pip install -e ".[dev]"
pytest

Type Checking

mypy src/features

Linting

ruff check src/features tests

Documentation

• Configuration Reference - Complete schema and options
• Validator Details - In-depth validator documentation
• Examples - Sample configurations

Philosophy

This linter enforces opinions about code organization based on these principles:

1. Modularity - Files should be small and focused
2. Discoverability - One definition per file makes code easier to find
3. Consistency - Predictable structure reduces cognitive load
4. Flexibility - All rules are configurable and can be disabled

The structure validator is opt-in because it's highly opinionated. The other validators (line limits and one-per-file) represent more universally accepted best practices.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Author

Created by kdaquila

Links

• GitHub Repository
• Issue Tracker
• PyPI Package