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NASA-DEVELOP / dnppy

DEVELOP National Program Python package for use with NASA data and GIS!
https://nasa-develop.github.io/dnppy/
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Develop unit tests for automated testing #56

Open Syntaf opened 9 years ago

Syntaf commented 9 years ago

Now that dnppy has integrated travis-ci documentation building, the environment for automated testing is already in place. All that's missing is testing for the functions.

If tests are developed for dnppy that don't use local files for testing it would be super easy to integrate said testing remotely so you would know when pushes break code.

Jwely commented 9 years ago

Do you think this would be practical with so many of our functions built to operate on large-ish raster data sets?

Syntaf commented 9 years ago

Is there a way to create minimal examples of functions that are built to operate on large data sets? Say call the function with a really small dataset that you can check by hand in the comparison? The data doesn't have to be real of course, e.g. for testing one of my libraries right now all I do is hand check stuff I know is right. How plausible is it to generate small pseudo datasets you can check?

Jwely commented 9 years ago

I suppose it's possible to create some tiny data subsets for some of the raster functions, like little 10x10 pixel images. Some of our functions are built to download and convert data formats from a variety of NASA DAAC's. It is important to test these as well, but I don't see anyway to create tiny test datasets for those functions.

see #25