pyproject.toml

[project]
name = "dftio"
dynamic = ["version"]
description = "dftio is to assist machine learning communities to transcript DFT output into a format that is easy to read or used by machine learning models."
authors = [
    {name = "Z. Zhouyin", email = "zhouyinzhanghao@gmail.com"}
]
readme = "README.md"
license = {text = "MIT"}
requires-python = ">=3.9,<3.13"
dependencies = [
    "numpy",
    "scipy>=1.11,<1.12",
    "matplotlib",
    "torch>=2.0.0,<2.5.1",
    "ase",
    "pyyaml",
    "future",
    "dargs==0.4.4",
    "e3nn>=0.5.1",
    "h5py>=3.7.0,<3.11.0,!=3.10.0",
    "lmdb==1.4.1",
    "sisl>=0.14.3",
    "dpdata>=0.2.20",
    "torch-scatter==2.1.2",
    "tqdm",
]

[dependency-groups]
dev = [
    "pytest>=7.2.0",
    "pytest-order==1.2.0",
    "pytest-cov",
    "jupyter-book>=0.15,<1.0",  # Use 0.x for Sphinx-based builds
    "sphinx-autodoc-typehints",
]

[project.scripts]
dftio = "dftio.__main__:main"

[project.urls]
Repository = "https://github.com/deepmodeling/dftio"

[build-system]
requires = ["setuptools>=64", "setuptools-scm>=8"]
build-backend = "setuptools.build_meta"

[tool.setuptools_scm]
version_file = "dftio/_version.py"
local_scheme = "no-local-version"

# UV 特定配置
# PyTorch Geometric 为 torch_scatter 提供预编译的 wheel
# 默认: CPU 版本。如需 GPU 版本，使用:
#   uv sync --find-links https://data.pyg.org/whl/torch-2.5.0+cu121.html
[tool.uv]
find-links = ["https://data.pyg.org/whl/torch-2.5.0+cpu.html"]

# Pytest 配置
# - testpaths: 指定测试文件所在目录
# - python_files/classes/functions: 定义测试文件、类、函数的命名规则
# - addopts: 默认命令行参数 (-v 详细输出, --tb=short 简短的错误追踪)
# - markers: 自定义标记，integration 用于标记集成测试，CI 中会跳过这些测试
[tool.pytest.ini_options]
testpaths = ["test"]
python_files = ["test_*.py"]
python_classes = ["Test*"]
python_functions = ["test_*"]
addopts = "-v --tb=short"
markers = [
    "integration: marks tests as integration tests (deselect with '-m \"not integration\"')",
]