Anderson Banihirwe
Anderson Banihirwe
When verifying the existing of `jupyter` in user's environment, we rely on this command: https://github.com/ncar-xdev/jupyter-forward/blob/64a2c56405f781c0f40f2221aecb2708d80d7efb/jupyter_forward/core.py#L218 However, this command isn't robust enough because having `jupyter` install doesn't necessary mean that `jupyterlab`...
Currently, when parsing the log file for Jupyter server information we use a `while` loop with a naive condition https://github.com/ncar-xdev/jupyter-forward/blob/917c142b6b5df6b78608b1538562ec3fd5b2a907/jupyter_forward/core.py#L209-L215 This loop can easily turn into an infinite loop when...
Currently, if neither of `$TMPDIR` and `$HOME` environment variables are defined on the remote machine, we terminate the connection and exit. We should allow users to override this behavior via...
Currently, if a user uses the `--launch-command` option --to launch the job on a compute node-- and something goes wrong (e.g. they specified a non-existing queue or something is off...
@manzt and i have been experimenting with anywidget + [`@carbonplan/maps`](https://docs.carbonplan.org/maps) in https://github.com/manzt/carbonplan. The notebook works perfectly fine when connected to a live kernel. however, i am facing an issue with...
The notebooks residing in this repo could use some love. Most if not all notebooks have very little prose. This makes it very hard for someone to follow/understand what's going...
While working on #156 and per discussion with @dcherian, I learned that esmlab's codebase is predominantly full of hacks. > I don't know the code that well at all (!)...
Per discussion with @matt-long, it would be useful to add a least squares polynomial fit to esmlab: ```python import xarray as xr import dask.array as da def _order_and_stack(darr, dim): dims_stacked...
Per [a recent CircleCI report](https://circleci.com/gh/NCAR/esmlab/1657?utm_campaign=vcs-integration-link&utm_medium=referral&utm_source=github-build-link), the following tests have issues that require further investigation - tests/test_core.py::test_mon_climatology[cesm_cice_daily-False-variables4-time] - tests/test_core.py::test_mon_climatology_drop_time_bounds[tiny-False-variables1-time-bounds] - tests/test_core.py::test_mon_climatology_drop_time_bounds[cmip5_pr_amon_csiro-False-variables2-time-bounds] tests/test_core.py::test_mon_climatology_drop_time_bounds[cesm_cice_daily-False-variables4-time-bounds]
In the past @matt-long and I noticed degraded performance when performing computations that rely on `groupby()` operations in `esmlab`. TIL of https://github.com/pydata/xarray/issues/2852, and I think that it's worth looking into...