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I am looking for a way to efficiently map test functions to the specific functions or modules they test. This would help in understanding the coverage and relationships between the test suite and the codebase. Specifically, I'd like to:
Identify which test functions are associated with which functions or modules in the pandas library.
Determine if there's a built-in tool, strategy, or script to extract this mapping.
If there is no such tool or methodology currently available, could you guide us on how this might be achieved?
This would greatly help in improving test coverage analysis.
I have been trying to use git blame and commit history analysis to trace which test functions were added or modified alongside new or updated functions in the codebase. The goal is to map these test functions to the specific functions or modules they test.
Thank you
The text was updated successfully, but these errors were encountered:
I do not think I understand your request. Is this related to pandas development itself, or the development of your codebase / test suite which uses pandas?
I am looking for a way to efficiently map test functions to the specific functions or modules they test.
Can you give an example of such a test function. Are these test functions in the pandas test suite, or one that you have written?
When you say "to the specific functions or modules they test", is this pandas functions / modules?
I am working on understanding the relationship between the test suite and the core pandas codebase. Specifically, I want to efficiently map test functions to the specific pandas functions or modules they test.
For example, consider the test function:
def test_get_slice(self, mgr):
located in pandas/pandas/tests/internals/test_internals.py. I would like to determine exactly which functions or parts of the pandas codebase this test is designed to cover. My goal is to create a clear mapping between test cases and the pandas implementation they validate.
It sounds like you are looking for code coverage of a particular test or collection of tests. There are a variety of packages that provide this, e.g. https://coverage.readthedocs.io/en/7.6.8/.
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Research
I have searched the [pandas] tag on StackOverflow for similar questions.
I have asked my usage related question on StackOverflow.
Link to question on StackOverflow
https://stackoverflow.com/questions/79239968/request-for-a-method-to-map-test-functions-to-the-functions-they-test
Question about pandas
I am looking for a way to efficiently map test functions to the specific functions or modules they test. This would help in understanding the coverage and relationships between the test suite and the codebase. Specifically, I'd like to:
Identify which test functions are associated with which functions or modules in the pandas library.
Determine if there's a built-in tool, strategy, or script to extract this mapping.
If there is no such tool or methodology currently available, could you guide us on how this might be achieved?
This would greatly help in improving test coverage analysis.
I have been trying to use git blame and commit history analysis to trace which test functions were added or modified alongside new or updated functions in the codebase. The goal is to map these test functions to the specific functions or modules they test.
Thank you
The text was updated successfully, but these errors were encountered: