Test all visualizers against API promises systematically

Potential testing idea - not sure how much of this is worth the time. These can be built into each visualizers unit tests, but would be good to have a basic set of checks that can be run for all visualizers.

To make sure that each new visualizer fulfills the few important API promises discussed yesterday, we should write unit tests that check that every visualizer meets them.

• Either make a list of all visualizers or (preferred) automatically find all childeren of the Visualizer class and run test on each one.

Checks:

• fit returns self
• transform returns X
• check that it can accept both numpy array and pandas dataframe
• check that there is a docstring under the class name, and not one under init
• use Inspect module to find all param names, and check that docstring at least contains all of these words somewhere in the docstring (to avoid undocumented params).
• See if there is any other quick and easy formatting check we can do on the docstring. Not sure if there’s anything else worth adding.
• Use inspect module to search for anything that looks like a hard-coded hex value in the draw method.
• Ensure finalize calls self.set_title and not self.ax.set_title.

[ndanielsen]

Just found this interesting package, we might be able to modify for our doc string conventions:

https://github.com/PyCQA/pydocstyle

[bbengfort]

@rebeccabilbro I think you’re right that we can close this since we haven’t moved forward on it in 2 years. One last piece of cleanup might be tests/checks.py – which was a partial prototype of this automatic checking functionality.