-
I noticed during reviewing #13 , but it's actually independent of it:
Installation of the package is quite a bit slower than expected, making e.g. the CI quite slow. The main reason appears to be s…
-
Could the variable `timeout` in line 6318 of the [scheduler](https://github.com/dask/distributed/blob/main/distributed/scheduler.py) have a more sensible name?
I have no idea how to configure that…
-
**Reproducer**
```python
@gen_cluster(client=True, nthreads=[("", 1)])
async def test_client_waits_indefinitely_on_log_event_recursion_error(c, s, a):
def error(*args):
from distrib…
-
### Description
Dask array fails to be written to FITS, at least when using `dask.distributed`. This doesn't occur for me if I *don't* create a `dask.distributed` `Client`. That is,…
-
We've observed a bunch of severe stability issues with the most recent versions.
It appears that the January version `2022.1.1` is the most recent stable version. Should we [yank](https://pypi.org/…
-
### Description
Hi there, I'm using dask to scale some work I'm doing. A small step includes some astropy unit conversions. This works fine when using `distributed.LocalCluster` for…
-
Since [iris 3.6](https://scitools-iris.readthedocs.io/en/stable/whatsnew/3.6.html), it is possible to use [Dask distributed](https://distributed.dask.org/en/stable/) with iris. This is a great new fea…
-
There is a traceback in the Dask case for the parallel notebook, and somehow this doesn't fail the CI or execution and rendering.
I see no sign of this in the pytest jobs (which uses `nbval`), but …
-
Previous issues have discussed supporting dask enabled parallel regridding (e.g. #3). This seems to be working for the threaded scheduler but not for the distributed scheduler. It seems like this shou…
-
**What happened**:
Using an asynchronous `dask.distributed.Client` both the asynchronous and synchronous context managers are asynchronous. Producing a `coroutine 'PooledRPCCall.__getattr__..sen…