pyproject.toml

[project]
name = "chunkmirage"
version = "0.1.0a1"
description = "Spoof chunked array formats (zarr, n5, neuroglancer precomputed) over HTTP with on-the-fly processing, caching, and pluggable ops."
readme = "README.md"
license = { file = "LICENSE" }
authors = [
    { name = "David Ackerman (@davidackerman)" },
    { name = "Yurii Zubov (@yuriyzubov)" },
]
requires-python = ">=3.11"
keywords = ["zarr", "n5", "neuroglancer", "tensorstore", "virtual", "chunked", "imaging"]
classifiers = [
    "Development Status :: 3 - Alpha",
    "Intended Audience :: Science/Research",
    "License :: OSI Approved :: BSD License",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
    "Programming Language :: Python :: 3.13",
    "Topic :: Scientific/Engineering",
    "Topic :: Scientific/Engineering :: Image Processing",
    "Typing :: Typed",
]
dependencies = [
    "numpy>=1.26",
    "numcodecs>=0.12",
    "tensorstore>=0.1.60",
    "starlette>=0.37",
    "uvicorn[standard]>=0.29",
    "hypercorn[h2]>=0.17",
    "pydantic>=2.6",
    "typer>=0.12",
]

[project.optional-dependencies]
hdf5 = ["h5py>=3.10"]
# GeoTIFF / cloud-optimized GeoTIFF sources (tensorstore's tiff driver reads only uint8)
tiff = ["tifffile>=2024.1", "imagecodecs>=2024.1"]
ops = ["scipy>=1.12"]
# meshes computed on demand (marching cubes)
mesh = ["scikit-image>=0.22", "DracoPy>=1.4"]
mcp = ["mcp>=1.0"]
viewer = ["neuroglancer>=2.40"]
https = ["cryptography>=42"]
# register:// solves on a GPU when there is one (CPU otherwise). gpu is PyTorch's CUDA build,
# ~3 GB of wheels, so not in `all`; cpu is its CPU-only build (CI, laptops). Pick one.
gpu = ["torch>=2.6", "scipy>=1.12"]
cpu = ["torch>=2.6", "scipy>=1.12"]
all = ["chunkmirage[hdf5,tiff,ops,mesh,mcp,viewer,https]"]

[project.urls]
Homepage = "https://janeliascicomp.github.io/chunkmirage/"
Documentation = "https://janeliascicomp.github.io/chunkmirage/"
Source = "https://github.com/JaneliaSciComp/chunkmirage"
Issues = "https://github.com/JaneliaSciComp/chunkmirage/issues"
Changelog = "https://github.com/JaneliaSciComp/chunkmirage/blob/main/CHANGELOG.md"

[project.scripts]
chunkmirage = "chunkmirage.cli:app"

[project.entry-points."chunkmirage.ops"]
threshold = "chunkmirage.ops.pointwise:Threshold"
cast = "chunkmirage.ops.pointwise:Cast"
scale = "chunkmirage.ops.pointwise:Scale"

[dependency-groups]
docs = [
    "mkdocs>=1.6,<2",
    "mkdocs-material>=9.5",
    "mkdocstrings[python]>=0.25",
]
dev = [
    "pytest>=8",
    "pytest-asyncio>=0.23",
    "httpx>=0.27",
    "ruff>=0.5",
    "neuroglancer>=2.40",
]

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

# torch per extra. gpu: CUDA 12.8, which covers Turing (sm_75) through Blackwell and runs on
# any driver >= 525, unlike PyPI's default build, which may need a newer driver than a
# workstation has. cpu: the CPU-only build, a tenth of the size.
[tool.uv.sources]
torch = [
  { index = "pytorch-cpu", extra = "cpu" },
  { index = "pytorch-cu128", extra = "gpu" },
]

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

[[tool.uv.index]]
name = "pytorch-cu128"
url = "https://download.pytorch.org/whl/cu128"
explicit = true

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[tool.hatch.build.targets.wheel]
packages = ["src/chunkmirage"]

[tool.ruff]
line-length = 100
target-version = "py311"

[tool.ruff.lint]
select = ["E", "F", "I", "UP", "B"]
ignore = ["B008", "B905", "E501"]

[tool.pytest.ini_options]
asyncio_mode = "auto"
testpaths = ["tests"]