pyproject.toml

[build-system]
requires = ["setuptools>=68.0", "wheel"]
build-backend = "setuptools.backends._legacy:_Backend"

[project]
name = "bdna-jepa"
version = "4.0.0"
description = "Bacterial Joint-Embedding Predictive Architecture for genomic foundation modeling"
readme = "README.md"
license = {text = "MIT"}
requires-python = ">=3.10"
authors = [{name = "Valentin Uzan", email = "uzanval@gmail.com"}]
keywords = ["genomics", "self-supervised-learning", "jepa", "bacteria", "foundation-model"]
classifiers = [
    "Development Status :: 3 - Alpha",
    "Intended Audience :: Science/Research",
    "Topic :: Scientific/Engineering :: Bio-Informatics",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
]
dependencies = [
    "torch>=2.1",
    "numpy>=1.24",
    "pandas>=2.0",
    "scikit-learn>=1.3",
    "scipy>=1.11",
    "pyyaml>=6.0",
    "tqdm>=4.65",
    "wandb>=0.15",
    "tokenizers>=0.15",
    "huggingface-hub>=0.20",
]

[project.optional-dependencies]
dev = ["pytest>=7.4", "pytest-cov>=4.1", "ruff>=0.3", "mypy>=1.8", "pre-commit>=3.5"]
eval = ["umap-learn>=0.5", "matplotlib>=3.8", "seaborn>=0.13"]
all = ["bdna-jepa[dev,eval]"]

[project.urls]
Repository = "https://github.com/VUzan-bio/bdna-jepa"
HuggingFace = "https://huggingface.co/orgava/dna-bacteria-jepa"

[tool.setuptools.packages.find]
include = ["bdna_jepa*"]

[tool.ruff]
line-length = 100
target-version = "py310"

[tool.ruff.lint]
select = ["E", "F", "I", "N", "W", "UP"]

[tool.pytest.ini_options]
testpaths = ["tests"]
addopts = "-v --tb=short"