Installation#
VirtualiZarr is available on PyPI via pip:
pip install virtualizarr
and on conda-forge:
conda install -c conda-forge virtualizarr
Optional dependencies#
VirtualiZarr has many optional dependencies, split into those for reading various file formats, and those for writing virtual references out to different formats.
Optional dependencies can be installed in groups via pip. For example to read HDF files and write virtual references to icechunk you could install all necessary dependencies via:
pip install "virtualizarr[hdf, icechunk]"
The full list of optional dependencies can be seen in the pyproject.toml
file:
[project.optional-dependencies]
# for creating virtual datasets from objects on remote storage
remote = [
"fsspec",
"requests",
"aiohttp",
"s3fs",
]
obstore = [
"obstore>=0.5.1",
]
# non-kerchunk-based readers
hdf = [
"virtualizarr[remote]",
"h5py",
"hdf5plugin",
"imagecodecs",
"imagecodecs-numcodecs==2024.6.1",
"obstore>=0.5.1",
]
# kerchunk-based readers
hdf5 = [
"virtualizarr[remote]",
"kerchunk>=0.2.8",
"h5py",
]
netcdf3 = [
"virtualizarr[remote]",
"kerchunk>=0.2.8",
"scipy",
]
fits = [
"virtualizarr[remote]",
"kerchunk>=0.2.8",
"astropy",
]
all_readers = [
"virtualizarr[hdf]",
"virtualizarr[hdf5]",
"virtualizarr[netcdf3]",
"virtualizarr[fits]",
]
# writers
icechunk = [
"icechunk>=0.2.4",
]
kerchunk = ["fastparquet"]
all_writers = [
"virtualizarr[icechunk]",
"virtualizarr[kerchunk]",
]
The compound groups allow you to install multiple sets of dependencies at once, e.g. install every file reader via
pip install "virtualizarr[all_readers]"
The basic pip install virtualizarr
will only install the minimal required dependencies, and so may not be particularly useful on its own.
Install Test Dependencies#
For local development you will want to install the test dependencies so that you can run all the tests in the test suite:
pip install '-e .[test]'
Install Docs Dependencies#
To build the documentation locally you will need further dependencies:
pip install '-e .[docs]'