clostera/pyproject.toml at main · BaseModelAI/clostera · GitHub

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[build-system]
requires = ["maturin>=1.7,<2.0"]
build-backend = "maturin"

[project]
name = "clostera"
version = "1.0.5"
description = "Rust-native high-performance clustering for large vector datasets with NumPy and parquet workflows"
readme = "README.md"
requires-python = ">=3.10"
license = { file = "LICENSE" }
authors = [{ name = "Jacek Dąbrowski", email = "ponythewhite@gmail.com" }]
maintainers = [{ name = "BaseModelAI" }]
keywords = ["clustering", "product-quantization", "vector-search", "rust", "parquet"]
classifiers = [
  "Development Status :: 5 - Production/Stable",
  "Intended Audience :: Science/Research",
  "Intended Audience :: Developers",
  "License :: OSI Approved :: MIT License",
  "Operating System :: MacOS",
  "Operating System :: POSIX :: Linux",
  "Programming Language :: Python :: 3",
  "Programming Language :: Python :: 3.10",
  "Programming Language :: Python :: 3.11",
  "Programming Language :: Python :: 3.12",
  "Programming Language :: Python :: 3.13",
  "Programming Language :: Rust",
  "Topic :: Scientific/Engineering :: Artificial Intelligence",
  "Topic :: Software Development :: Libraries :: Python Modules",
]
dependencies = [
  "numpy>=2.0",
  "pyarrow>=15.0",
]

[project.urls]
Homepage = "https://github.com/BaseModelAI/clostera"
Repository = "https://github.com/BaseModelAI/clostera"
Issues = "https://github.com/BaseModelAI/clostera/issues"
Releases = "https://github.com/BaseModelAI/clostera/releases"

[project.optional-dependencies]
dev = [
  "pytest>=8.0",
  "scikit-learn>=1.5",
  "matplotlib>=3.9",
]
benchmarks = [
  "datasets>=2.20",
  "faiss-cpu>=1.8",
  "h5py>=3.11",
  "matplotlib>=3.9",
  "open_clip_torch>=2.24",
  "pandas>=2.2",
  "pqkmeans",
  "psutil>=5.9",
  "pyarrow>=15",
  "scikit-learn>=1.4",
  "sentence-transformers>=3.0",
  "torch>=2.4",
  "torchvision>=0.19",
  "transformers>=4.45",
]
[tool.maturin]
python-source = "python"
module-name = "clostera._clostera"
features = ["python"]

[tool.pytest.ini_options]
markers = [
  "performance: performance smoke and benchmark-oriented tests",
]