mllam-data-prep/pyproject.toml at main · mllam/mllam-data-prep · GitHub

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[project]
name = "mllam-data-prep"
version = "0.7.0"
description = "dataset preparation for data-driven weather models"
authors = [
    {name = "Leif Denby", email = "lcd@dmi.dk"},
    {name = "Hauke Schulz", email = "has@dmi.dk"},
    {name = "Emy Alerskans", email = "ea@dmi.dk"},
    {name = "Eleni Briola", email = "elb@dmi.dk"},
    {name = "Joel Oskarsson", email = "joel.oskarsson@liu.se"},
    {name = "Kashif Rasul", email = "kashif.rasul@gmail.com"},
    {name = "Jordan Matelsky", email = "opensource@matelsky.com"},
    {name = "Martin Frølund", email = "maf@dmi.dk"},
    {name = "Simon Kamuk Christiansen", email = "skc@dmi.dk"},
]
dependencies = [
    "xarray>=2024.2.0",
    "zarr>=2.17.0",
    "pyyaml>=6.0.1",
    "loguru>=0.7.2",
    "isodate>=0.6.1",
    "requests>=2.31.0",
    "aiohttp>=3.9.3",
    "dataclass-wizard>=0.29.2,<1.0",
    "semver>=3.0.2",
    "rich>=13.7.1",
    "dask>=2024.2.1",
    "psutil>=5.7.2",
    "packaging>=23.1",
    "deepdiff>=8.2.0",
    "spherical-geometry>=1.3.2",
    "cartopy>=0.23.0",
    "gcsfs>=2024.10.0",
    "jinja2>=3.1.4",
]
requires-python = ">=3.9"
readme = "README.md"
license = {text = "MIT"}

[project.optional-dependencies]
dask-distributed = [
    "dask[distributed]>=2024.7.1",
    "bokeh!=3.0.*,>=2.4.2",
]

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


[tool.isort]
profile = "black"

[tool.pdm]
distribution = true
[tool.pdm.dev-dependencies]
dev = [
    "pytest>=8.0.2",
    "ipdb>=0.13.13",
    "pre-commit>=3.7.1",
    "ipykernel>=6.29.5",
]
[project.scripts]
mllam_data_prep = "mllam_data_prep:cli.call"