physioex/pyproject.toml at main · guidogagl/physioex · GitHub

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[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[project]
name = "physioex"
dynamic = ["version"]
description = "A python package for explainable sleep staging via deep learning"
readme = {"file" = "README.md", "content-type" = "text/markdown"}
requires-python = ">=3.11"
authors = [
    { name = "Guido Gagliardi", email = "guido.gagliardi@phd.unipi.it" }
]
license = {text = "MIT"}
dependencies = [
    "torch>=2.7.0",
    "numpy>=1.26.0",
    "pandas>=2.0.0",
    "pyyaml>=6.0",

    "matplotlib>=3.10.0",
    "scikit_learn>=1.7.0",
    "scipy>=1.16.0",

    "huggingface_hub>=0.34.0",
    "captum>=0.6.0",
    "loguru>=0.7.0",
    "pyedflib>=0.1.42",
    "braindecode>=1.0.0",
    "ml_dtypes>=0.5.0",
    "einops>=0.7.0",
    "tqdm>=4.65.0",

    "rich>=13.0.0",
    "psutil>=5.9.0",
    "torchinfo>=1.8.0",
]

[project.optional-dependencies]
gpu-monitor = ["nvitop>=1.0.0"]
tracking = ["tensorboard>=2.14", "wandb>=0.16"]
# Heavyweight, feature-specific deps imported lazily; install only if needed.
foundation = ["transformers>=4.40.0"]  # REVE encoder (physioex.models.reve)
datasets = ["mne>=1.6.0"]              # HOMEPAP EDF fallback reader (data.datasets.hpap)
dev = ["ruff", "pytest", "pytest-cov", "black~=22.0"]
legacy = ["pytorch_lightning>=2.5.0", "lightning>=2.5.0", "torchmetrics>=1.8.0"]
explain = [
    "zennit>=0.5.1",   # LRP composites/canonizers (Zennit path) + BatchNorm merging; attention/RNN rules are built in
]
docs = [
    "sphinx==8.1.3",
    "pydata-sphinx-theme==0.16.1",
    "myst-nb==1.2.0",              # pulls in myst-parser
    "sphinx-design==0.6.1",
    "sphinx-copybutton==0.5.2",
    "sphinxcontrib-mermaid==1.0.0",
    # autodoc/autosummary/napoleon/intersphinx/viewcode ship with sphinx.
    # sphinx-autoapi is the static-parsing fallback (not enabled by default).
]

[tool.hatch.version]
path = "physioex/__init__.py"

[tool.hatch.build.targets.wheel]
packages = ["physioex"]

# Runtime data files that must ship in the wheel (loaded via __file__ at import time).
[tool.hatch.build.targets.wheel.force-include]
"physioex/train/models/check_table.csv" = "physioex/train/models/check_table.csv"
"physioex/data/datasets/_splits/shhs.json" = "physioex/data/datasets/_splits/shhs.json"


[project.scripts]
train = "physioex.train.bin.train:train_script"
finetune = "physioex.train.bin.finetune:finetune_script"
test_model = "physioex.train.bin.test:test_script"

[project.urls]
Homepage = "https://github.com/guidogagl/physioex"
Documentation = "https://guidogagl.github.io/physioex"
Repository = "https://github.com/guidogagl/physioex"
Issues = "https://github.com/guidogagl/physioex/issues"

[tool.pytest.ini_options]
testpaths = ["tests"]
addopts = "-ra --strict-markers --import-mode=importlib"
markers = [
    "unit: fast, isolated unit test (default)",
    "integration: exercises several components together",
    "real_data: needs datasets on disk (skipped unless PHYSIOEX_TEST_REAL_DATA=1)",
    "gpu: needs a CUDA GPU (skipped if unavailable)",
    "hf: needs HuggingFace network/checkpoints (skipped unless PHYSIOEX_TEST_HF=1)",
    "slow: long-running test",
]
filterwarnings = [
    "ignore::DeprecationWarning:physioex.data.dataset",
    "ignore::DeprecationWarning:physioex.data.datareader",
]

[tool.coverage.run]
source = ["physioex"]
branch = true
omit = [
    "physioex/data/dataset.py",       # legacy, deprecated
    "physioex/data/datareader.py",    # legacy, deprecated
    "*/tests/*",
    # ── Not exercisable in CPU-only CI (covered by gated/manual runs) ──
    "physioex/train/multidevicetrainer.py",   # DDP, needs multi-GPU
    "physioex/train/bin/*",                    # CLI entry points (gated cli_workflows)
    # Foundation-encoder internals need HuggingFace weights (@hf, run on bio-gpu).
    # Their contract (class attrs, PIPELINE_PRESET, wrapper) is covered CPU-side.
    "physioex/models/bendr.py",
    "physioex/models/biot.py",
    "physioex/models/cbramod.py",
    "physioex/models/labram.py",
    "physioex/models/neurolm.py",
    "physioex/models/reve.py",
    "physioex/models/sjepa.py",
    "physioex/models/sleepfm.py",
    "physioex/models/tfc.py",
    "physioex/models/coresleep.py",            # multimodal, no CPU forward path tested
    "physioex/models/protosleepnet.py",        # composite encoder, gated
    "physioex/models/embed.py",                # extract/probe pipelines need HF + disk
    "physioex/models/pretrained.py",           # checkpoint loading (gated)
    "physioex/models/foundation_checkpoints.py",  # downloads checkpoints
    "physioex/models/foundation_datasets.py",     # dataset registry, needs real roots
    "physioex/models/foundation_channel_mapping.py",  # exercised via @hf encoder builds
]

[tool.coverage.report]
show_missing = true
skip_covered = false
exclude_lines = [
    "pragma: no cover",
    "raise NotImplementedError",
    "if __name__ == .__main__.:",
    "if TYPE_CHECKING:",
    "@(abc\\.)?abstractmethod",
]