Tools and tests used in Kaggle Learn exercises
The checking code and notebooks used in Kaggle Learn courses.
Everything here is open source, but these materials haven't been designed to work independently and likely aren't useful outside of Kaggle Learn.
This repo is split into two types of material. - The
learntoolsfolder contains a python package that provides feedback to users in Kaggle Learn courses. This package is further divided into - Modules for individual courses. For example,
learntools/pythonis used to check exercises in the Python course.
learntools/machine_learningis used to check exercises in the Machine Learning course. And so on. -
coreprovides the infrastructure for exercise checking. This is imported into the modules for each course. - The
notebookssubdirectory contains tools to simplify publishing courses on kaggle as well as the course materials themselves. The course materials are in notebooks. The notebooks for the python course are in
/notebooks/python/raw/*. Replace python with another course name to find the materials for other courses. The notebooks are processed in a templating system before being uploaded to kaggle, so the
rawnotebooks are hard to read. The README in
/notebookshas instructions to convert
rawnotebooks to rendered notebooks (and to use the templating system more generally).
Some courses have notebooks in a subdirectory of the
learntoolspackage, reflecting the fact these notebooks were authored and edited outside our templating system.
Run all tests against the staging image:
Run all tests against a specific image:
./test.sh -i gcr.io/kaggle-images/python:some-tag
Run only the tests for the
./test.sh -t computer_vision
Run only the tests for the 1st exercise of the
./test.sh -t computer_vision -n ex1