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| id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at ▲ | closed_at | author_association | active_lock_reason | draft | pull_request | body | reactions | performed_via_github_app | state_reason | repo | type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 829426650 | MDU6SXNzdWU4Mjk0MjY2NTA= | 5023 | Unable to load multiple WRF NetCDF files into Dask array on pangeo | porterdf 7237617 | closed | 0 | 5 | 2021-03-11T18:44:55Z | 2021-04-28T19:16:44Z | 2021-04-28T19:16:44Z | NONE | (Sorry if this is not correct place for this, obviously Pangeo repo is another option) Working with @jkingslake, our immediate goal is to load many WRF history files (3 hourly in this case), currently stored in our public GCS, and write out to Zarr for public/open use. We can get all of this working on local machine, but on us-central1-b As this gist shows, opening a single WRF file works as expected. Is this a limitation of open_mfdatasets? Alternatively, looping through each file and using ``` xr.show_versions() INSTALLED VERSIONScommit: None python: 3.8.6 | packaged by conda-forge | (default, Jan 25 2021, 23:21:18) [GCC 9.3.0] python-bits: 64 OS: Linux OS-release: 4.19.112+ machine: x86_64 processor: x86_64 byteorder: little LC_ALL: C.UTF-8 LANG: C.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.6 libnetcdf: 4.7.4 xarray: 0.16.2 pandas: 1.2.1 numpy: 1.20.0 scipy: 1.6.0 netCDF4: 1.5.5.1 pydap: installed h5netcdf: 0.8.1 h5py: 3.1.0 Nio: None zarr: 2.6.1 cftime: 1.4.1 nc_time_axis: 1.2.0 PseudoNetCDF: None rasterio: 1.2.0 cfgrib: 0.9.8.5 iris: None bottleneck: 1.3.2 dask: 2021.01.1 distributed: 2021.01.1 matplotlib: 3.3.4 cartopy: 0.18.0 seaborn: None numbagg: None pint: 0.16.1 setuptools: 49.6.0.post20210108 pip: 20.3.4 conda: None pytest: None IPython: 7.20.0 sphinx: 3.4.3 ``` |
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