DOC: set module on remaining top-level functions #2

lishaxia · 2025-10-29T22:41:46Z

Follow-up on pandas-dev#62727, resolving this for the remaining functions in the top-level namespace (and for some of the submodules, where it were only a few ones to address, i.e. pandas.testing and pandas.api.extensions)

xref pandas-dev#55178

Co-authored-by: Richard Shadrach <rhshadrach@gmail.com>

q-dev-gamma-pdx-interstellar · 2025-10-29T22:41:51Z

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q-dev-gamma-pdx-interstellar · 2025-10-29T22:43:14Z

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lishaxia · 2025-10-29T23:28:05Z

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q-dev-gamma-pdx-interstellar · 2025-10-29T23:28:40Z

Thank you for the opportunity to review this pull request. I've examined the changes, and here are my observations:

The PR correctly sets the __module__ attribute for various functions and classes across multiple files in the pandas library.
The changes are consistent with the PR's title and description, addressing the remaining top-level functions and some submodules.
The modifications appear to be straightforward and don't introduce any functional changes to the code.
This update will improve the consistency of module information for pandas objects, which is beneficial for documentation and introspection.
The changes seem to be comprehensive, covering a wide range of pandas components.

Overall, the changes look good and achieve the stated goal. Do you have any specific areas you'd like me to focus on or any concerns you'd like addressed?

lishaxia · 2025-10-30T00:15:17Z

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lishaxia · 2025-10-30T00:17:52Z

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lishaxia · 2025-10-30T00:31:27Z

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q-dev-gamma-pdx-interstellar · 2025-10-30T00:32:09Z

Thank you for your work on setting the __module__ attribute for remaining top-level functions. This change improves the consistency and clarity of the pandas API. Here are some observations and suggestions:

Consistency: The @set_module decorator is being applied consistently across multiple files, which is good for maintaining a uniform API structure.
Modules: The decorator is setting modules like "pandas", "pandas.api.types", "pandas.api.extensions", "pandas.api.indexers", and "pandas.plotting". This helps in organizing the API and making it more intuitive for users.
Test updates: The test_set_module() function in pandas/tests/api/test_api.py has been removed. Instead, a more comprehensive test test_attributes_module() has been added, which checks for correct __module__ attributes and importability.
Performance: While this change improves API clarity, it's worth noting that using decorators can have a small performance impact. However, in this case, the benefit of clear API structure likely outweighs any minimal performance considerations.
Documentation: Consider updating the relevant documentation to reflect these changes, especially if there are any impacts on how users should import or use these functions and classes.

Overall, this change appears to be a positive step towards a more organized and consistent pandas API. Great job on improving the project's structure!

Do you have any questions or need clarification on any part of this review?

vibhhu-amazon · 2025-10-30T00:45:18Z

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q-dev-gamma-pdx-interstellar · 2025-10-30T00:45:23Z

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q-dev-gamma-pdx-interstellar

Overall, this pull request makes good progress in improving the module attribution for functions in the pandas/_libs/lib.pyx file. The consistent application of the @set_module("pandas.api.types") decorator to functions like is_scalar, is_iterator, is_float, and others is a positive change. It ensures these functions are correctly associated with the pandas.api.types module, which is important for maintaining a clear and organized public API.

Suggestions for improvement:

Review the entire file to ensure all functions that should be part of the public API are decorated with @set_module.
For functions intentionally left without the decorator, consider adding comments explaining why they are not part of the public API.
Ensure consistency in applying this pattern across other relevant files in the pandas library.

These changes contribute to better organization and clarity in the pandas codebase. Good job on improving the module attribution!

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q-dev-gamma-pdx-interstellar · 2025-10-30T00:47:18Z

pandas/_config/config.py

+# import set_module here would cause circular import
+get_option.__module__ = "pandas"
+set_option.__module__ = "pandas"
+describe_option.__module__ = "pandas"
+reset_option.__module__ = "pandas"
+option_context.__module__ = "pandas"


The changes made here are setting the __module__ attribute for several functions to "pandas". This is a good practice for ensuring that these functions are correctly associated with the pandas package. However, we should consider using the @set_module decorator for consistency and maintainability.

Suggested change

# import set_module here would cause circular import

get_option.__module__ = "pandas"

set_option.__module__ = "pandas"

describe_option.__module__ = "pandas"

reset_option.__module__ = "pandas"

option_context.__module__ = "pandas"

from pandas.util._decorators import set_module

@set_module("pandas")

def get_option(pat: str) -> Any:

...

@set_module("pandas")

def set_option(*args) -> None:

...

@set_module("pandas")

def describe_option(pat: str = "", _print_desc: bool = True) -> str | None:

...

@set_module("pandas")

def reset_option(pat: str) -> None:

...

@set_module("pandas")

def option_context(*args) -> Generator[None]:

...

q-dev-gamma-pdx-interstellar · 2025-10-30T00:47:19Z

pandas/_libs/lib.pyx

 from pandas._config import using_string_dtype

 from pandas._libs.missing import check_na_tuples_nonequal
+from pandas.util._decorators import set_module


Good addition of the set_module import. This will help in setting the correct module for the decorated functions. However, we should consider applying this decorator consistently to all relevant functions in this file.

q-dev-gamma-pdx-interstellar · 2025-10-30T00:47:19Z

pandas/_libs/lib.pyx

+@set_module("pandas.api.types")
 def is_scalar(val: object) -> bool:


The @set_module("pandas.api.types") decorator is correctly applied to the is_scalar function. This ensures that the function is properly associated with the pandas.api.types module. Consider applying this decorator consistently to all relevant functions in this file that should be part of the public API.

q-dev-gamma-pdx-interstellar · 2025-10-30T00:47:19Z

pandas/_libs/lib.pyx

+@set_module("pandas.api.types")
 def is_iterator(obj: object) -> bool:


The @set_module("pandas.api.types") decorator is correctly applied to the is_iterator function. This is consistent with the previous application to is_scalar. Ensure that all functions intended to be part of the public API are decorated similarly.

q-dev-gamma-pdx-interstellar · 2025-10-30T00:47:19Z

pandas/_libs/lib.pyx

+@set_module("pandas.api.types")
 def is_float(obj: object) -> bool:


The @set_module("pandas.api.types") decorator is consistently applied to the is_float function here, and to other functions like is_integer, is_bool, is_complex, is_list_like, and infer_dtype in the subsequent changes. This is good practice and ensures these functions are correctly associated with the pandas.api.types module.

Consider reviewing the entire file to ensure all relevant functions that should be part of the public API are decorated appropriately. If there are functions intentionally left without the decorator, it might be helpful to add a comment explaining why they are not part of the public API.

lishaxia · 2025-10-30T01:48:16Z

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lishaxia · 2025-10-30T01:53:28Z

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DOC: set __module__ on remaining top-level functions (pandas-dev#62758)

d7e0620

Co-authored-by: Richard Shadrach <rhshadrach@gmail.com>

q-dev-gamma-pdx-interstellar bot reviewed Oct 30, 2025

View reviewed changes

-# import set_module here would cause circular import
-get_option.__module__ = "pandas"
-set_option.__module__ = "pandas"
-describe_option.__module__ = "pandas"
-reset_option.__module__ = "pandas"
-option_context.__module__ = "pandas"
+from pandas.util._decorators import set_module
+@set_module("pandas")
+def get_option(pat: str) -> Any:
+    ...
+@set_module("pandas")
+def set_option(*args) -> None:
+    ...
+@set_module("pandas")
+def describe_option(pat: str = "", _print_desc: bool = True) -> str | None:
+    ...
+@set_module("pandas")
+def reset_option(pat: str) -> None:
+    ...
+@set_module("pandas")
+def option_context(*args) -> Generator[None]:
+    ...

		@set_module("pandas.api.types")
		def is_scalar(val: object) -> bool:

		@set_module("pandas.api.types")
		def is_iterator(obj: object) -> bool:

		@set_module("pandas.api.types")
		def is_float(obj: object) -> bool:

DOC: set __module__ on remaining top-level functions #2

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DOC: set module on remaining top-level functions #2

DOC: set module on remaining top-level functions #2