• closes DOC: Document the filters argument in read_parquet #52238 (Replace xxxx with the issue number)
• Tests added and passed if fixing a bug or adding a new feature
• All code checks passed.
• Added type annotations 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.

added filters as a new parameter in pd.read_parquet

Instead since we still support both engines, I think linking to the docs for both fastparquet and pyarrow in **kwargs is sufficient #52238 (comment)

Given that the filters keyword is supported by both engines and works the same, I think it would certainly be useful to explicitly document this keyword, and not hide it in the description of the kwargs. We actually already do the same for the columns keyword.

@mroeschke OK with adding this?

Okay yeah that makes sense to add this then

Could you add a test for filters for both engines?

This pull request is stale because it has been open for thirty days with no activity. Please update and respond to this comment if you're still interested in working on this.

@mrastgoo would you have time to add a test?

We have an existing test for the columns keyword (test_read_columns), so could add an equivalent test_read_filters test case next to it. Something like:

    def test_read_filters(self, engine, tmp_path):
        df = pd.DataFrame({"int": list(range(4)), "part": list("aabb"),})

        expected = pd.DataFrame({"int": [0, 1]})
        check_round_trip(
            df,
            engine,
            path=tmp_path,
            expected=expected,
            write_kwargs={"partition_cols": ["part"]},
            read_kwargs={"filters": [("string", "==", "a")], "columns":["int"]},
            repeat=1,
        )

I used partition cols to actually see the effect of the filter also for fastparquet (to ensure it is correctly passed through). And with that, the repeat=1 is needed to not add additional files to the directory when writing a second time (with partition_cols, it does not just overwrite the single file).

@jorisvandenbossche , yes I would do it asap, sorry for the delay in this issue and thanks for the info I will take that into account.

I just pushed for the test.
I changed the following line for the test

read_kwargs={"filters": [("part", "==", "a")], "columns":["int"]},

the error which was raised was not very clear for missing columns, which is not a pandas issue, but thought to mention it.

pyarrow.lib.ArrowInvalid: No match for FieldRef.Name(string) in int: int64
part: dictionary<values=string, indices=int32, ordered=0>

Could you merge in main once more?

[mroeschke]

Could you put this as the last argument? (before **kwargs)?

[mroeschke]

Could you add a .. versionadded:: 2.1.0 at the end?

Also needs a whatsnew entry in 2.1.0.rst in the IO section

Thanks @mrastgoo