CI: Add pyarrow 11 to ci
- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.
- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.

Status Quo

Currently, we test on pyarrow versions 8, 9, and 10 (IIRC because some version of pyarrow in between our min/latest version broke, but the min/latest version passed). This currently adds a lot of burden on our CI (builds are queueing for 2 hours again even though Github bumped up our concurrent runners), since the builds are created from the cross product of matrix parameters, and also hasn't really caught that many issues (which is expected, since failures would mean that pyarrow had a regression).

IMO, we should share some of that testing burden between the two projects, both to reduce load on the pandas CI, and to ensure that pyarrow has enough testing coverage to catch its own bugs in Pandas/Pyarrow integration.

Proposed changes

- [ ] Pyarrow test pandas nightlies in addition to testing min/latest pandas
    - pyarrow seems to run their tests on pandas nightly.
    - [ ] They should add a job to run pandas tests that test Arrow Extension Arrays/CSV IO/Parquet IO etc.
            - Pyarrow uses pandas internals, so it is easy for them to break something, because of changes to internal structures on our side
            - We should provide a mark to only run Arrow tests so that they don't have to run the full test suite.

- [ ] We drop testing of intermediate versions of pyarrow and move to testing only min/max again
        - This aligns with what we're doing with numpy
        - There is a risk of breakage due to pyarrow's usage of our internals, so we should kinda figure out what pyarrow needs in our internals and mark those functions in the code.
              -  Maybe we can have a "pseudo-public" API for those functions.

- [ ] (optionally) We test pyarrow nightlies
        - If CI capacity frees up enough, we should also test pyarrow nightlies (I couldn't find the nightly builds for the Python bindings though).

Alternatives

Add the "arrow" mark on our side and only run those tests on the parametrized arrow build.

I will open an issue on their side in a couple days if no objections.

cc @mroeschke @jorisvandenbossche  Generally I would support only testing pyarrow min + max again right away. 

pyarrow has seemed fairly stable within the past few versions and appears to be primarily additive in functionality. Especially since pyarrow functionality has been primarily opt-in-without-fallback, I don't see too much utility testing intermediate versions of pyarrow anymore. I am a bit hesitant about only testing min and max as long as we have the flags that control behavior dependent on the pyarrow version. Wdyt about testing 8 on python 3.8, 9 on python 3.9 and so on? FWIW I think since we bumped up the pyarrow version recently we only have version dependent fallback behavior in 2 spots, argsort and fillna in special cases. (They appear to also be or versions < 7 which we recently made our min version)

argsort
```
        null_placement = {"last": "at_end", "first": "at_start"}.get(na_position, None)
        if null_placement is None or pa_version_under7p0:
            # Although pc.array_sort_indices exists in version 6
            # there's a bug that affects the pa.ChunkedArray backing
            # https://issues.apache.org/jira/browse/ARROW-12042
            fallback_performancewarning("7")
            return super().argsort(
                ascending=ascending, kind=kind, na_position=na_position
            )
```

fillna
```
        if method is not None and pa_version_under7p0:
            # fill_null_{forward|backward} added in pyarrow 7.0
            fallback_performancewarning(version="7")
            return super().fillna(value=value, method=method, limit=limit)
``` I don't fully understand why we at some point moved towards parametrizing the build matrix on all supported versions of pyarrow. Personally, I would keep testing all versions of pyarrow (at least if we currently only support the latest 4 versions that seem doable), but that doesn't mean that we have to build every possible combination of python version and single-cpu / non-single-cpu with every version of pyarrow?

We could also generally run one version of pyarrow per version of Python? (roughly speaking) That gives 8 builds (4\*2) instead of 32 (4\*4\*2) > Pyarrow test pandas nightlies in addition to testing min/latest pandas
>   * pyarrow seems to run their tests on pandas nightly.

Indeed, we already have a build with pandas nightly (which regularly catches some changes/regressions)

> * They should add a job to run pandas tests that test Arrow Extension Arrays/CSV IO/Parquet IO etc.

Yes, this is indeed something we could do. I am not actually sure why we don't do that for pandas, as we do exactly that for dask (run a subset of dask's tests using the nightly arrow)

I think starting with specifically running a few files/directories (parquet and csv tests, the arrow extension arrays) might be a good enough start (not necessarily needing a mark, although if we start with marking a few whole files, that's also easy to add)

> (optionally) We test pyarrow nightlies

I would emphasize this a bit more, and it should actually be easy to add (we already have a build with upstream dev versions, and we can add pyarrow nightly to the same build?) > but that doesn't mean that we have to build every possible combination of python version and single-cpu / non-single-cpu with every version of pyarrow

The pyaarrow CSV engine tests are marked as `single_cpu` while the other tests are not. In the past, I noticed the arrow CSV engine would stall if run with xdist.

 > 
> > * They should add a job to run pandas tests that test Arrow Extension Arrays/CSV IO/Parquet IO etc.
> 
> Yes, this is indeed something we could do. I am not actually sure why we don't do that for pandas, as we do exactly that for dask (run a subset of dask's tests using the nightly arrow)
> 
> I think starting with specifically running a few files/directories (parquet and csv tests, the arrow extension arrays) might be a good enough start (not necessarily needing a mark, although if we start with marking a few whole files, that's also easy to add)

Cool. I'll open up an issue on the Arrow side then.

> > (optionally) We test pyarrow nightlies
> 
> I would emphasize this a bit more, and it should actually be easy to add (we already have a build with upstream dev versions, and we can add pyarrow nightly to the same build?)

I can add this if you give me a link. Googling only gives me the R nightlies. > > but that doesn't mean that we have to build every possible combination of python version and single-cpu / non-single-cpu with every version of pyarrow
> 
> The pyaarrow CSV engine tests are marked as `single_cpu` while the other tests are not. In the past, I noticed the arrow CSV engine would stall if run with xdist.

Yes, but what I mentioned was running each combo of python version and single/non-single CPU just with 1 version of pyarrow instead of 4. That still runs the csv tests with pyarrow for single-cpu. > I can add this if you give me a link. Googling only gives me the R nightlies.

@lithomas1 see https://arrow.apache.org/docs/dev/developers/python.html#installing-nightly-packages (it's indeed a bit hidden in the development section instead of having it on the install page).  > Yes, but what I mentioned was running each combo of python version and single/non-single CPU just with 1 version of pyarrow instead of 4. That still runs the csv tests with pyarrow for single-cpu.

Right that's fair. I think I would still prefer to test the min & max version of pyarrow. Anecdotally, pyarrow development has notably affected the minimum pyarrow version build or all builds affecting all Pyarrow versions.  This pull request is stale because it has been open for thirty days with no activity. Please [update](https://pandas.pydata.org/pandas-docs/stable/development/contributing.html#updating-your-pull-request) and respond to this comment if you're still interested in working on this. Sorry, this slipped off my radar for a bit.

Right now, I'm currently working on getting rid of all hanging tests for read_csv with pyarrow. Then, we should be able to get rid of the single_cpu pyarrow builds.

I'm holding off on adding pyarrow nightlies, until we can first reduce the CI matrix first. I stumbled upon this on the desk side today, what are your thoughts on adding the arrow nightly to the numpy nightly build? > I stumbled upon this on the desk side today, what are your thoughts on adding the arrow nightly to the numpy nightly build?

I don't think they test with Cython 3 ATM, so it wouldn't be practical (They currently do support the latest beta as of a couple of days ago, but it is untested in their CI).
It also could cause some noise in our CI when numpydev breaks arrow. IMO I think we could already:

1) Start only testing pyarrow min version & unpinned (latest)
2) Add a new job in the `ubuntu.yml` workflow for testing just arrow nightly

That would be a net of -3 jobs in the workflow while testing pyarrow nightly which is probably more valuable than testing intermediate versions of pyarrow I think we can close this as we cleaned up some of the Arrow testing in the CI as apart of https://github.com/pandas-dev/pandas/pull/52211