pyproject.toml

[tool.ruff]
exclude = [
    "other-methods/",
    "MathFeature/",
    "manuscript/",
    ".venv/",
]
line-length = 120

[tool.ruff.lint]
# Focus on real bugs; ignore patterns common in scientific Python scripts
select = ["E", "F", "W"]
ignore = [
    "E402",  # module-import-not-at-top (common in CLI scripts with sys.path manipulation)
    "F401",  # unused-import (common in ML scripts with conditional usage)
    "F403",  # star-import (used in several modules)
    "F405",  # star-import usage
    "F811",  # redefined-while-unused
    "E501",  # line-too-long (handled by formatter)
    "E741",  # ambiguous variable name (l, O, I — common in math code)
]

[tool.ruff.format]
# Only the App/ source is formatted; scripts in other dirs are excluded above

[project]
name = "BioAutoML-FAST"
version = "1.0.0"
description = "Empowering Breakthroughs in Life Sciences with End-to-End Machine Learning"
readme = "README.md"
requires-python = ">=3.11"
dependencies = [
    "bibtexparser>=1.4.3",
    "biopython>=1.85",
    "catboost>=1.2.7",
    "cryptography>=46.0.3",
    "fastexcel>=0.14.0",
    "hyperopt>=0.2.7",
    "igraph>=0.11.8",
    "imbalanced-learn>=0.13.0",
    "ipykernel>=6.29.5",
    "lightgbm>=4.6.0",
    "networkx>=3.4.2",
    "openpyxl>=3.1.5",
    "optuna>=4.2.1",
    "pandas>=2.2.3",
    "plotly>=6.0.1",
    "polars>=1.27.0",
    "psutil>=7.0.0",
    "pygad>=3.4.0",
    "redis>=7.1.0",
    "reportlab>=4.3.1",
    "requests>=2.32.3",
    "rq>=2.6.1",
    "scikit-learn>=1.6.1",
    "seaborn>=0.13.2",
    "setuptools>=78.1.0",
    "shap>=0.47.1",
    "sklearn-genetic>=0.6.0",
    "sklearn-genetic-opt>=0.11.1",
    "streamlit==1.55.0",
    "streamlit-aggrid>=1.2.1",
    "streamlit-option-menu>=0.4.0",
    "tpot>=0.12.2",
    "tqdm>=4.67.1",
    "umap-learn>=0.5.7",
    "xgboost>=3.0.0",
]