fix: add List, Dict, Tuple and NamedTuple to the GenericDType bound

[sam-goodwin]

Closes https://github.com/unionai-oss/pandera/issues/1555

[codecov[bot]]

Codecov Report

All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 83.07%. Comparing base (4df61da) to head (8ab65a5). Report is 75 commits behind head on main.

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Additional details and impacted files

@@             Coverage Diff             @@
##             main    #1556       +/-   ##
===========================================
- Coverage   94.29%   83.07%   -11.22%     
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  Files          91      111       +20     
  Lines        7024     8191     +1167     
===========================================
+ Hits         6623     6805      +182     
- Misses        401     1386      +985     

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[cosmicBboy]

Thanks @sam-goodwin, see https://pandera.readthedocs.io/en/latest/CONTRIBUTING.html#set-up-pre-commit for steps to make sure linters and unit tests are passing. You'll also need to sign your commits: https://pandera.readthedocs.io/en/latest/CONTRIBUTING.html#dco-signing-commits

[cosmicBboy]

Mypy errors:

tests/core/test_typing.py:498: error: "list" is not subscriptable, use "typing.List" instead  [misc]
tests/core/test_typing.py:499: error: "dict" is not subscriptable, use "typing.Dict" instead  [misc]
tests/core/test_typing.py:500: error: "tuple" is not subscriptable, use "typing.Tuple" instead  [misc]

Note that pandera needs to support python 3.8 as well, so we need to use the generic types in the typing module.

Failing unit test:

FAILED tests/core/test_typing.py::test_complex_python_collection_types - pandera.errors.SchemaError: expected series 'list' to have type list[pandera.dtypes.Int32]:
failure cases:
   index failure_case
0      0       [1, 2]
1      1    [3, 4, 5]

Looks like you need to use the built-in int type? pandera.dtypes.Int32 translates to the numpy dtype for pandas columns.

[sam-goodwin]

Looks like you need to use the built-in int type? pandera.dtypes.Int32 translates to the numpy dtype for pandas columns.

Do you mean we can't specify ints with specific precision in a List or Dict in pandera?

[cosmicBboy]

Do you mean we can't specify ints with specific precision in a List or Dict in pandera?

This just follows the way pandas deals with data. Columns containing list or dict objects are just python objects, meaning they're not numpy arrays. This might be different for pyarrow data representations, but that'll be something to tackle when adding pyarrow support https://github.com/unionai-oss/pandera/issues/1262.

In summary, pandera.dtypes.Int32 maps onto a numpy.int32, and a list[numpy.int32] isn't meaningful in the context of pandas. list[int] does tho, and will contain just lists of python ints.

[cosmicBboy]

@sam-goodwin friendly ping: one of the unit tests is still failing: https://github.com/unionai-oss/pandera/actions/runs/8861081819/job/24332580434?pr=1556