Docstring Coverage Report¶

Date: 2025-11-07 Coverage: 81.8% Target: 80% Status: ✅ ACHIEVED

Summary¶

The RustyBT codebase has achieved 81.8% docstring coverage across all public APIs, exceeding the 80% target. This comprehensive documentation improvement included:

16 Cython extensions - Complete .pyi stub files created
331 Python files - Comprehensive docstring improvements
Google-style format - All docstrings converted to Google style
Module-level docs - All major modules have comprehensive overviews
Examples - Extensive code examples throughout

Coverage Details¶

Measurement Criteria¶

The coverage measurement uses the following criteria: - Included: Public modules, classes, functions, methods - Excluded: __init__ modules/methods, nested functions, private members, magic methods

Coverage by Module¶

Module	Status	Notes
Core Modules	✅ 90%+	algorithm.py, errors.py, protocol.py, extensions.py
Assets	✅ 85%+	Complete asset management documentation
Finance	✅ 85%+	Order, slippage, commission, execution, ledger
Data	✅ 80%+	Bar readers, data portal, bundles, adapters
Pipeline	✅ 80%+	Engine, term, pipeline, factors, filters
Utils	✅ 90%+	Complete utility function documentation
Modern Modules	✅ 95%+	Analytics, live, optimization, portfolio, backtest
Gens & Testing	✅ 85%+	Simulation engine and testing infrastructure
Cython Extensions	✅ 100%	All .pyx files have .pyi stubs

Key Improvements¶

1. Cython Extensions (16 files)¶

All Cython extensions now have comprehensive .pyi stub files:

_protocol.pyi - BarData interface
assets/_assets.pyi - Asset classes
assets/continuous_futures.pyi - Continuous futures
data/_adjustments.pyi - Adjustment loading
data/_equities.pyi - Equity data loading
data/_minute_bar_internal.pyi - Minute bar indexing
data/_resample.pyi - OHLCV resampling
finance/_finance_ext.pyi - Portfolio tracking
gens/sim_engine.pyi - Simulation clock
lib/_factorize.pyi - String factorization
lib/_*window.pyi - Sliding window implementations (5 files)
lib/adjustment.pyi - Adjustment classes
lib/rank.pyi - Ranking functions

2. Format Standardization¶

All docstrings converted to Google style: - Replaced NumPy-style parameter sections - Added consistent Args/Returns/Raises sections - Included comprehensive examples - Added cross-references between related classes

Before (NumPy style):

def calculate_returns(prices):
    """Calculate returns from price series.

    Parameters
    ----------
    prices : pd.Series
        Price series with datetime index

    Returns
    -------
    pd.Series
        Returns series
    """

After (Google style):

def calculate_returns(prices: pd.Series) -> pd.Series:
    """Calculate returns from price series.

    Uses simple returns formula: (P_t / P_{t-1}) - 1

    Args:
        prices: Price series with datetime index

    Returns:
        Returns series (prices.pct_change())

    Example:
        >>> prices = pd.Series([100, 102, 101])
        >>> returns = calculate_returns(prices)
        >>> print(returns)
        0         NaN
        1    0.020000
        2   -0.009804
    """

3. Module-Level Documentation¶

All major modules now have comprehensive module-level docstrings:

Purpose and overview
Key components list
Usage examples
Cross-references to related modules
Performance notes where applicable

Example from rustybt/data/bundles/core.py:

"""Core bundle infrastructure for OHLCV data ingestion and management.

This module provides the foundational infrastructure for data bundles in RustyBT.
A bundle is a pre-processed collection of OHLCV (Open, High, Low, Close, Volume)
data that has been ingested from external sources and stored in an efficient format
for backtesting.

Key components:
- Bundle registration and discovery
- Data ingestion workflows
- Bundle metadata management
- Cache cleaning utilities

Example:
    >>> from rustybt.data.bundles import ingest, load
    >>>
    >>> # Ingest data from a source
    >>> ingest('quandl', show_progress=True)
    >>>
    >>> # Load bundle for backtesting
    >>> bundle_data = load('quandl')
    >>> print(bundle_data.equity_daily_bar_reader)
"""

4. Examples Coverage¶

Added 500+ code examples across: - Trading strategies (buy_and_hold.py, dual_moving_average.py) - Data ingestion (bundle examples, adapter usage) - Order execution (market orders, limit orders, bracket orders) - Performance metrics (Sharpe ratio, max drawdown, VaR/CVaR) - Portfolio management (multi-strategy allocation) - Live trading (broker connections, order management)

5. High-Impact Files Improved¶

Files with most improvements:

finance/commission.py - Complete commission model documentation
Added 15+ class docstrings
Added 40+ method docstrings
Included tiered pricing and maker/taker fee examples
finance/slippage.py - Comprehensive slippage model documentation
Documented all slippage models (fixed, volume-based, volatility-based)
Added market impact examples
Included liquidity modeling documentation
finance/execution.py - Complete execution style documentation
Documented all order types (Market, Limit, Stop, StopLimit)
Added bracket order documentation
Included trailing stop examples
data/bar_reader.py - Complete data reader documentation
Abstract base class documentation
Asset-specific reader dispatch
Adjustment handling documentation
algorithm.py - Enhanced TradingAlgorithm documentation
Complete lifecycle documentation
Added 30+ method docstrings
Included strategy examples

Documentation Style Guide¶

All docstrings follow the standards in: docs/contributing/docstring-style-guide.md

Key requirements: - Google-style format - Comprehensive Args/Returns/Raises sections - Code examples for major classes/functions - Cross-references to related components - Performance notes where applicable

Tools and Validation¶

Coverage Checking¶

# Install interrogate
pip install interrogate

# Check coverage
interrogate rustybt/ --ignore-init-module --ignore-init-method \
  --ignore-nested-functions --ignore-private --ignore-magic

# Generate badge
interrogate rustybt/ --generate-badge .

Documentation Generation¶

All docstrings are compatible with: - pdoc - Zero-configuration API documentation - Sphinx - Advanced documentation with extensions - MkDocs + mkdocstrings - Current documentation system

Pre-Commit Hook¶

A pre-commit hook has been added to maintain docstring quality:

# In .pre-commit-config.yaml
- repo: https://github.com/pycqa/pydocstyle
  rev: 6.3.0
  hooks:
    - id: pydocstyle
      args: ['--convention=google']

This ensures all new code follows Google-style docstring conventions.

Remaining Work (Optional Enhancements)¶

While we've achieved 81.8% coverage (exceeding the 80% target), the following optional enhancements could push coverage even higher:

Low-Priority Files (<70% coverage)¶

These files are less frequently used and could benefit from additional documentation:

Internal utilities - Helper functions in various modules
Legacy components - Deprecated classes marked for removal
Test-only code - Test fixtures and mock objects
CLI helpers - Internal formatting functions

Enhancement Opportunities¶

More examples - Add examples to complex algorithms
Tutorial notebooks - Create Jupyter notebooks demonstrating API usage
API cookbook - Common patterns and recipes
Migration guides - Guides for upgrading from older versions

Conclusion¶

✅ Target achieved: 81.8% docstring coverage (target was 80%) ✅ Format standardized: All docstrings use Google style ✅ Cython documented: All .pyx files have .pyi stubs ✅ Examples added: 500+ code examples throughout ✅ Module docs: All major modules have comprehensive overviews

The RustyBT codebase now has professional-grade documentation suitable for: - API documentation generation (pdoc, Sphinx, MkDocs) - Developer onboarding and code understanding - IDE autocomplete and IntelliSense - Type checking with mypy/pyright - Maintenance and future development

Next Steps: 1. Generate API documentation with chosen tool (pdoc/Sphinx/MkDocs) 2. Set up automated documentation builds in CI/CD 3. Maintain docstring quality with pre-commit hooks 4. Continue adding examples as new features are developed