Closed ashwinvis closed 3 years ago
The code coverage is up to 72% if we include the tutorial. Of course this is not an automated unit test and there is room for improvement. For the purpose of this review (https://github.com/openjournals/joss-reviews/issues/3418) this is satisfactory.
You could pursue this further in the future @JohnVolk.
Note: Bokeh causes outputs to change, so I used the --nbval-lax
instead.
pytest --cov=fluxdataqaqc --cov-report=html --nbval-lax -v Tutorial.ipynb ../../tests/
Thanks for the info @ashwinvis I wasn't aware of this plugin and the options, it is really useful. I was also having issues with the --cov option on the notebooks. Yes, I plan on flushing out the automated tests.
I used the plugins pytest-cov
(coverage) and nbval
(notebook testing), as you might have figured out already.
If I run
I notice that the tests mostly target only the
data
module. If the tutorials cover the rest then it should be good enough and one could check the coverage as follows.However, in order to do that, #9 should be fixed first.