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pyproject.toml
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pyproject.toml
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[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "autograd"
version = "1.7.0"
requires-python = ">=3.9"
description = "Efficiently computes derivatives of NumPy code."
readme = "README.md"
license = {file = "license.txt"}
authors = [
{name = "Dougal Maclaurin", email = "[email protected]"},
{name = "David Duvenaud", email = "[email protected]"},
{name = "Matthew Johnson", email = "[email protected]"},
{name = "Jamie Townsend", email = "[email protected]"},
]
maintainers = [
{name = "Jamie Townsend", email = "[email protected]"},
{name = "Fabian Joswig", email = "[email protected]"},
{name = "Agriya Khetarpal", email = "[email protected]"},
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Information Technology",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: MIT License",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Topic :: Scientific/Engineering",
]
keywords = [
"Automatic differentiation",
"backpropagation",
"gradients",
"machine learning",
"optimization",
"neural networks",
"Python",
"NumPy",
"SciPy",
]
dependencies = [
"numpy",
]
# dynamic = ["version"]
[project.urls]
Source = "https://github.com/HIPS/autograd"
[project.optional-dependencies]
scipy = [
"scipy",
]
test = [
"pytest",
"pytest-cov",
"pytest-xdist",
]
[tool.coverage.run]
source = ["autograd"]
[tool.coverage.report]
show_missing = true
[tool.pytest.ini_options]
required_plugins = ["pytest-cov", "pytest-xdist"]
# TODO: generate HTML report, upload to CodeCov
addopts = "--color=yes -sra -n auto --cov=autograd --cov-report=xml --cov-report=term"
[tool.ruff]
extend-exclude = []
# TODO: not ignore them
lint.extend-ignore = [
"E731",
"F401",
"F403",
"F841",
"F821",
"E721",
"E722",
"E741",
"E402",
"F811"
]
lint.extend-select = ["I", "W"]
line-length = 109