TorchStream/pyproject.toml at master · CorentinJ/TorchStream · GitHub

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[project]
# PyPi name, import name is "torchstream"
name = "torchstream-lib"
version = "1.0.2"
authors = [
  { name = "Corentin Jemine", email = "corentin.jemine@gmail.com" }
]
maintainers = [
  { name = "Corentin Jemine", email = "corentin.jemine@gmail.com" }
]
description = "A library for making PyTorch models streamable"
keywords = ["torch", "pytorch", "streaming", "deep learning", "machine learning", "neural networks", "numpy", "optimization"]
classifiers = [
    "Programming Language :: Python :: 3",
    "Operating System :: OS Independent",
    "Intended Audience :: Developers",
    "Intended Audience :: Science/Research",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
    "Topic :: Software Development :: Libraries",
    "Framework :: OpenTelemetry :: Instrumentations",
]
readme = "README.md"
license = "MIT"
license-files = ["LICENSE"]
requires-python = ">=3.8"
dependencies = [
    "numpy>=1.23.0",
    "opentelemetry-api>=1.33.1",
    "scipy>=1.10.1",
    "torch>=1.11.0",
    "z3-solver>=4.14.0.0",
]

[project.optional-dependencies]
cpu = [
  "torch>=1.11.0",
]
cuda = [
  "torch>=1.11.0",
]

[project.urls]
Repository = "https://github.com/CorentinJ/TorchStream"

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

# Defining a build system lets us install the project as a dev package
[build-system]
requires = ["setuptools"]
build-backend = "setuptools.build_meta"

[dependency-groups]
demos = [
    "colorama>=0.4.6",
    "huggingface_hub>=0.23.4,<=0.36",
    "kokoro>=0.9.2",
    "librosa>=0.11.0",
    "matplotlib>=3.7.5",
    "opentelemetry-sdk>=1.33.1",
    "pip>=25.0.1",
    "requests>=2.32.4",
    "resampy>=0.4.3",
    "soundfile",
    "streamlit>=1.40.1",
    "torch>=1.11.0",
    "torchaudio>=2.5.1",
]
dev = [
    "opentelemetry-sdk>=1.33.1",
    "pytest>=8.3.4",
    "pytest-profiling>=1.8.1",
]

[tool.uv]
conflicts = [
  [
    { extra = "cpu" },
    { extra = "cuda" },
  ],
]

[tool.uv.sources]
torch = [
  { index = "pytorch-cpu",  extra = "cpu"   },
  { index = "pytorch-cu118", extra = "cuda" },
]

# It's easier to setup torchaudio on CPU, regardless of whether CUDA is used for torch.
# We don't need CUDA-enabled torchaudio for the demos.
torchaudio = [
  { index = "pytorch-cpu", group = "demos" },
]

[[tool.uv.index]]
name = "pytorch-cu118"
url = "https://download.pytorch.org/whl/cu118"
explicit = true

[[tool.uv.index]]
name = "pytorch-cpu"
url = "https://download.pytorch.org/whl/cpu"
explicit = true

[tool.uv.dependency-groups]
demos = { requires-python = ">=3.10" }

[tool.ruff]
line-length = 120