Ian Rose

Currently we are only showing the repository default branch. It would be nice to be able to switch branches.

Authentication for dashboards

19

### The problem Broadly speaking, this extension works by passing around URLs: 1. When a user has a cluster and clicks on the magnifying glass icon, it checks `client.dashboard_link` to...

Better cluster management and discovery

3

## AKA Let's delete dask-labextension's `ClusterManager` ### Goal For a few years now this extension has had a built-in [cluster manager](https://github.com/dask/dask-labextension/blob/main/dask_labextension/manager.py), which is what powers the user interface on the...

Cluster Model update

2

There is currently some churn going on in the interfaces for a generic distributed cluster info dict (cf. #78, #77 #73). At the same time, this extension takes that information,...

initial pass at a to_ibis function.

4

A first pass at implementing #347. This PR is mostly about establishing an interface for drivers to implement -- it doesn't really do anything useful here. The idea is that...

Set the base html element for the data so that relative links work.

11

Next step for #7. This sets the `` element for the iframe html, which allows it to correctly resolve external css, etc to the server.

Groupby sort upstream compatibility

3

Fixes #9428, sort of. The [pandas GroupBy](https://pandas.pydata.org/docs/dev/reference/api/pandas.DataFrame.groupby.html) defaults to `sort=True`, and `None` is not a valid input. Dask's implementation has `sort=None` as a default, so when we started to pass...

This includes the new `shuffle` kwarg in more of the groupby aggregations, and enables shuffle-based aggregation in those places. So now `df.groupby("a").sum()` and `df.groupby("a").agg("sum")` both have access to the same...

The following fails for both `cov` and `corr` when `split_out>1`: ```python import pandas as pd import dask.dataframe as dd pdf = pd.DataFrame( { "a": [1, 2, 6, 4, 4, 6,...

In #9406 @rjzamora did some nice work in implementing a shuffle-based groupby/agg operation for dask dataframe. However, it is currently only implemented for `groupby(...).agg({...})`, and some of the simpler aggregation...