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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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 568705055 | MDU6SXNzdWU1Njg3MDUwNTU= | 3785 | open_dataarray(cache=False) still uses cached version of dataarray | ngreenwald 13770365 | closed | 0 | 2 | 2020-02-21T02:58:22Z | 2020-03-03T18:29:46Z | 2020-03-03T18:29:46Z | NONE | MCVE Code Sample```python Your code hereimport xarray as xr import numpy as np import os create two different xarrays with different sizes and coordstest_xr1 = xr.DataArray(np.zeros((5, 5, 3)), coords=[range(5), range(5), ["x1", "y1", "z1"]], dims=["1", "2", "3"]) test_xr2 = xr.DataArray(np.zeros((10, 2, 3)), coords=[range(10), range(2), ["x2", "y2", "z2"]], dims=["1", "2", "3"]) save first xarray, reload it, and inspect coordstest_xr1.to_netcdf("test_xr.xr") loaded_xr = xr.open_dataarray("test_xr.xr", cache=False) loaded_xr.coords Out[13]: Coordinates: * 1 (1) int64 0 1 2 3 4 * 2 (2) int64 0 1 2 3 4 * 3 (3) object 'x1' 'y1' 'z1' remove first xarray, save second with the same name, and load itos.remove("test_xr.xr") test_xr2.to_netcdf("test_xr.xr") loaded_xr = xr.open_dataarray("test_xr.xr", cache=False) loaded_xr.coords Out[17]: Coordinates: * 1 (1) int64 0 1 2 3 4 * 2 (2) int64 0 1 2 3 4 * 3 (3) object 'x1' 'y1' 'z1' ``` Expected OutputRather than loading the newly created/updated version of the file on disk, the cached version is used Problem DescriptionIf a file ever gets updated on disk and needs to be reloaded, this causes very mysterious bugs. Furthermore, the only workaround I found is to restart the python session. Output of
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completed | xarray 13221727 | issue |
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