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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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1697705761 | I_kwDOAMm_X85lMO8h | 7818 | Warning on distributed lock on dask cluster | jules-ch 43635101 | closed | 0 | 2 | 2023-05-05T14:19:22Z | 2024-02-26T06:08:14Z | 2024-02-26T06:08:14Z | NONE | What is your issue?I'm using xarray to store datasets that are computed on a distributed dask cluster. I'm making use of the to_netcdf to chunk the storage. I get some warnings about coroutine not awaited with distributed. Just wanted to know if that is something to worry about, like locks not released ?
Here is a minimal example : ```python import logging import xarray as xr import numpy as np import dask.distributed as dd import dask.array as da import pandas as pd async def main(): cluster = dd.LocalCluster(scheduler_port=8786, processes=False, asynchronous=True) import asyncio import os if name == "main": logging.basicConfig() os.environ["HDF5_USE_FILE_LOCKING"] = "False" asyncio.run(main()) ``` ```python import xarray as xr xr.show_versions() INSTALLED VERSIONScommit: None python: 3.9.16 (main, Dec 7 2022, 01:12:08) [GCC 11.3.0] python-bits: 64 OS: Linux OS-release: 5.19.0-41-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: ('en_US', 'UTF-8') libhdf5: 1.12.2 libnetcdf: 4.9.1 xarray: 2022.12.0 pandas: 1.5.3 numpy: 1.24.3 scipy: 1.10.1 netCDF4: 1.6.3 pydap: None h5netcdf: 1.1.0 h5py: 3.8.0 Nio: None zarr: None cftime: 1.6.2 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: 2023.4.0 distributed: 2023.4.0 matplotlib: 3.7.1 cartopy: None seaborn: 0.11.2 numbagg: None fsspec: 2023.4.0 cupy: None pint: 0.20.1 sparse: None flox: None numpy_groupies: None setuptools: 67.7.2 pip: 23.1.2 conda: None pytest: 6.2.5 mypy: 0.931 IPython: 8.12.1 sphinx: None ``` Documentation on this feature : https://docs.xarray.dev/en/stable/user-guide/dask.html#reading-and-writing-data feel free to close this issue, if that's unrelated with xarray. |
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not_planned | xarray 13221727 | issue | ||||||
| 1180565228 | I_kwDOAMm_X85GXf7s | 6412 | numpy datetime conversion with DataArray is not working | jules-ch 43635101 | open | 0 | 3 | 2022-03-25T09:46:12Z | 2022-03-29T14:22:11Z | NONE | What happened?I have a simple DataArray with Using the What did you expect to happen?I excpected the DataArray to be converted in the correct dtype Minimal Complete Verifiable Example```Python
Relevant log outputNo response Anything else we need to know?No response EnvironmentINSTALLED VERSIONScommit: None python: 3.8.10 (default, Nov 26 2021, 20:14:08) [GCC 9.3.0] python-bits: 64 OS: Linux OS-release: 5.13.0-37-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: ('en_US', 'UTF-8') libhdf5: 1.12.1 libnetcdf: None xarray: 0.20.2 pandas: 1.4.1 numpy: 1.22.3 scipy: 1.8.0 netCDF4: None pydap: None h5netcdf: None h5py: 3.6.0 Nio: None zarr: None cftime: None nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: 2022.03.0 distributed: 2022.3.0 matplotlib: 3.5.1 cartopy: None seaborn: None numbagg: None fsspec: 2022.02.0 cupy: None pint: 0.18 sparse: None setuptools: 60.6.0 pip: 22.0.3 conda: None pytest: 6.2.5 IPython: 8.1.1 sphinx: None |
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xarray 13221727 | issue |
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