Testing pandas code [closed]

Question

I have a script of about 50 lines that reads data from a database, loads it into a pandas dataframe and then perform numerous operations on the dataframe.

I was wondering how people generally test this type of code? I'm not talking about tools like assert_frame_equal, but rather principles people follow.

For instance, should I create 50 separate tests to basically test each operation performed or should I try to break up the script in smaller parts?

If anybody knows of quality open source projects that I can use as inspiration, please let me know.

Answer 1

If you want to start to write python unit test, this question is recommended.

Since the 50 lines are relevant, you probably want a functional test.
Read the difference between unit, functional, acceptance, and integration testing.
If you know SOLID principle of object-oriented-design, refactoring to the code is needed.

About how to design a good test, What are the properties of good unit tests

Specific to pandas, use fewer data to improve performance for testing.
Make a dummy copy for testing, rather than use the origin data.
And check mainly on the key feature, you want to check.