N-D labeled arrays and datasets in Python
http://github.com/pydata/xarray
xarray (formerly xray) is a python-pandas-like and pandas-compatible
toolkit for analytics on multi-dimensional arrays. It provides
N-dimensional variants of the python-pandas labeled data structures,
rather than the tabular data that pandas uses.
The Common Data Model for self-describing scientific data is used.
The dataset is an in-memory representation of a netCDF file.
- Developed at devel:languages:python:numeric
- Sources inherited from project openSUSE:Factory
-
2
derived packages
- Download package
-
Checkout Package
osc -A https://api.opensuse.org checkout openSUSE:Factory:Rebuild/python-xarray && cd $_
- Create Badge
Refresh
Refresh
Source Files
Filename | Size | Changed |
---|---|---|
_multibuild | 0000000053 53 Bytes | |
local_dataset.patch | 0000000665 665 Bytes | |
python-xarray.changes | 0000235985 230 KB | |
python-xarray.spec | 0000007149 6.98 KB | |
xarray-2024.11.0-gh.tar.gz | 0003236300 3.09 MB |
Latest Revision
Ana Guerrero (anag+factory)
accepted
request 1226114
from
Sebastian Wagner (sebix)
(revision 51)
- skip test test_asi8 on 32bit, results in "OverflowError: Python int too large to convert to C long" - update to version .2024.11.0: - disable the 'parallel' subpackage because dask is unavailable 3.12, which is because numba is unavailable on 3.13 https://build.opensuse.org/request/show/1225144 https://github.com/numba/numba/issues/9760 - disabled tests requiring dask - delete obsolete patches xarray-pr9356-dasktests.patch, xarray-pr9321-dasktests.patch and xarray-pr9403-np2.1-scalar.patch
Comments 8
This comment has been deleted
The cause is: https://build.opensuse.org/package/show/openSUSE:Factory/python-numcodecs fails to build because of a failing test case.
I am on it, but simply updateing numcodecs to 0.14 will break zarr: https://github.com/zarr-developers/numcodecs/issues/653
Thank you for investigating this!
This comment has been deleted
a result of https://build.opensuse.org/request/show/1225144
upstream issue report at numba: https://github.com/numba/numba/issues/9760
You could try re-enabling it, as we ship a python313 patch for numba now: sr#1225801