Python Packages


Python

Python / Machine Learning

  • pandas: data manipulation and I/O for CSV/JSON/SQL.
  • numpy: numerical arrays and fast computations.
  • scikit-learn: model building, validation, and preprocessing utilities.
  • xgboost: gradient-boosted trees for classification/regression.
  • lightgbm: fast gradient boosting optimized for large datasets.
  • catboost: gradient boosting that handles categorical features.
  • optuna: hyperparameter tuning framework.
  • mlflow: experiment tracking for ML results.
  • shap: model explainability tools.
  • statsmodels: statistical models and tests.
  • scipy: scientific computations and statistics.
  • joblib: model persistence and parallel utilities.
  • tensorflow / torch: optional deep learning frameworks for neural models.
Data

Data & Web

Utilities

Utilities & Testing

  • pytest: tests and assertions.
  • pytest-cov: coverage reporting for pytest suites.
  • pytest-asyncio: asyncio test support for pytest.
  • black: code formatter for consistent style.
  • ruff: linter and format checker.
  • mypy: static typing analysis.
  • plotly: graphing capabilities.
  • flake8: style and linting for Python source.
  • pre-commit: git hooks for code quality checks.
  • pandas-stubs: type stubs for pandas.
Repo specific

Repo-specific Libraries

Specialized libraries used in individual projects (F1, MLB, NBA, etc.).

  • fastf1: Formula 1 telemetry (f1Analysis).
  • mlb-statsapi: MLB data service (baseball-predictions).
  • nba_api: NBA game stats service (nba-predictions).
  • pybaseball: baseball metrics (baseball-predictions).
  • cbbd: college basketball stats (march-madness).
  • cfbd: college football stats (tailgate-edge).
  • betfairlightweight: Betfair market data (horse-racing-predictions).
  • sbrscrape: sportsbook odds scraping helper (multiple repos).