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20 hours ago •
xCDAT
xCDAT
[Bug]: conda update wants to downgrade xcdat from 0.7.1 to 0.7.0
What happened?
I have a brand new python environment on a Linux server where I installed xcdat and other stuff a few days ago
I thought I would check if there were some updates available today. There are, including a numpy update, but I also get
The following packages will be DOWNGRADED:
xcdat 0.7.1-pyhd8ed1ab_0 --> 0.7.0-pyhd8ed1ab_0
Full output below. I have type "n" to cancel the operation
$ conda update -n bezaud_env --all
Retrieving notices: ...working... done
Channels:
- conda-forge
- defaults
Platform: linux-64
Collecting package metadata (repodata.json): done
Solving environment: done
## Package Plan ##
environment location: /homedata/jypmce/miniconda3_2024-03/envs/bezaud_env
The following packages will be downloaded:
package | build
---------------------------|-----------------
aws-c-auth-0.7.22 | heee8711_7 104 KB conda-forge
aws-c-cal-0.7.0 | h816f305_0 47 KB conda-forge
aws-c-http-0.8.2 | had8cc17_4 190 KB conda-forge
aws-c-io-0.14.9 | h37d6bf3_5 154 KB conda-forge
aws-c-s3-0.6.0 | h1f67ec3_0 108 KB conda-forge
aws-crt-cpp-0.27.1 | h93f15ff_1 337 KB conda-forge
aws-sdk-cpp-1.11.329 | h70d5bd1_7 3.5 MB conda-forge
ipykernel-6.29.5 | pyh3099207_0 116 KB conda-forge
ipython-8.26.0 | pyh707e725_0 585 KB conda-forge
libarrow-16.1.0 | h040edfd_12_cpu 7.9 MB conda-forge
libarrow-acero-16.1.0 | he02047a_12_cpu 585 KB conda-forge
libarrow-dataset-16.1.0 | he02047a_12_cpu 565 KB conda-forge
libarrow-substrait-16.1.0 | hc9a23c6_12_cpu 536 KB conda-forge
libgoogle-cloud-2.26.0 | h26d7fe4_0 1.2 MB conda-forge
libgoogle-cloud-storage-2.26.0| ha262f82_0 746 KB conda-forge
libparquet-16.1.0 | h9e5060d_12_cpu 1.1 MB conda-forge
mpich-4.2.2 | h4a7f18d_100 25.1 MB conda-forge
numpy-2.0.0 | py312h22e1c76_0 8.0 MB conda-forge
pillow-10.4.0 | py312h287a98d_0 40.1 MB conda-forge
s2n-1.4.17 | he19d79f_0 342 KB conda-forge
snappy-1.2.1 | ha2e4443_0 41 KB conda-forge
xcdat-0.7.0 | pyhd8ed1ab_0 70 KB conda-forge
xesmf-0.8.6 | pyhd8ed1ab_0 44 KB conda-forge
------------------------------------------------------------
Total: 91.4 MB
The following packages will be UPDATED:
aws-c-auth 0.7.22-hf36ad8f_6 --> 0.7.22-heee8711_7
aws-c-cal 0.6.15-h816f305_1 --> 0.7.0-h816f305_0
aws-c-http 0.8.2-h75ac8c9_3 --> 0.8.2-had8cc17_4
aws-c-io 0.14.9-hd3d3696_3 --> 0.14.9-h37d6bf3_5
aws-c-s3 0.5.10-h44b787d_4 --> 0.6.0-h1f67ec3_0
aws-crt-cpp 0.26.12-he940a02_1 --> 0.27.1-h93f15ff_1
aws-sdk-cpp 1.11.329-h0f5bab0_6 --> 1.11.329-h70d5bd1_7
ca-certificates 2024.6.2-hbcca054_0 --> 2024.7.4-hbcca054_0
ipykernel 6.29.4-pyh3099207_0 --> 6.29.5-pyh3099207_0
ipython 8.25.0-pyh707e725_0 --> 8.26.0-pyh707e725_0
libarrow 16.1.0-h4a673ee_10_cpu --> 16.1.0-h040edfd_12_cpu
libarrow-acero 16.1.0-hac33072_10_cpu --> 16.1.0-he02047a_12_cpu
libarrow-dataset 16.1.0-hac33072_10_cpu --> 16.1.0-he02047a_12_cpu
libarrow-substrait 16.1.0-h7e0c224_10_cpu --> 16.1.0-hc9a23c6_12_cpu
libcurl 8.8.0-hca28451_0 --> 8.8.0-hca28451_1
libgoogle-cloud 2.25.0-h2736e30_0 --> 2.26.0-h26d7fe4_0
libgoogle-cloud-s~ 2.25.0-h3d9a0c8_0 --> 2.26.0-ha262f82_0
libparquet 16.1.0-h6a7eafb_10_cpu --> 16.1.0-h9e5060d_12_cpu
mpich 4.2.1-h63d650b_101 --> 4.2.2-h4a7f18d_100
numpy 1.26.4-py312heda63a1_0 --> 2.0.0-py312h22e1c76_0
pillow 10.3.0-py312h287a98d_1 --> 10.4.0-py312h287a98d_0
s2n 1.4.16-he19d79f_0 --> 1.4.17-he19d79f_0
snappy 1.2.0-hdb0a2a9_1 --> 1.2.1-ha2e4443_0
xesmf 0.8.5-pyhd8ed1ab_0 --> 0.8.6-pyhd8ed1ab_0
The following packages will be DOWNGRADED:
xcdat 0.7.1-pyhd8ed1ab_0 --> 0.7.0-pyhd8ed1ab_0
Proceed ([y]/n)?
What did you expect to happen? Are there are possible answers you came across?
I did not expect an xcdat downgrade!
Minimal Complete Verifiable Example (MVCE)
No response
Relevant log output
No response
Anything else we need to know?
No response
Environment
$ conda activate bezaud_env
(bezaud_env) jypmce@spiritx1:/homedata/jypmce/miniconda3_2024-03/pkgs/python-3.12.4-h194c7f8_0_cpython/bin$ python
Python 3.12.4 | packaged by conda-forge | (main, Jun 17 2024, 10:23:07) [GCC 12.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import xarray as xr
>>> xr.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 3.12.4 | packaged by conda-forge | (main, Jun 17 2024, 10:23:07) [GCC 12.3.0]
python-bits: 64
OS: Linux
OS-release: 5.4.0-176-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: 1.14.3
libnetcdf: 4.9.2
xarray: 2024.6.0
pandas: 2.2.2
numpy: 1.26.4
scipy: 1.14.0
netCDF4: 1.7.1
pydap: None
h5netcdf: None
h5py: None
zarr: None
cftime: 1.6.4
nc_time_axis: None
iris: None
bottleneck: None
dask: 2024.6.2
distributed: 2024.6.2
matplotlib: 3.8.4
cartopy: 0.23.0
seaborn: None
numbagg: None
fsspec: 2024.6.1
cupy: None
pint: None
sparse: 0.15.4
flox: None
numpy_groupies: None
setuptools: 70.1.1
pip: 24.0
conda: None
pytest: None
mypy: None
IPython: 8.25.0
sphinx: None
>>>
