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.
learntools
folder contains a python package that provides feedback to users in Kaggle Learn courses. This package is further divided into
learntools/python
is used to check exercises in the Python course. learntools/machine_learning
is used to check exercises in the Machine Learning course. And so on.core
provides the infrastructure for exercise checking. This is imported into the modules for each course.notebooks
subdirectory 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 raw
notebooks are hard to read. The README in /notebooks
has instructions to convert raw
notebooks to rendered notebooks (and to use the templating system more generally).Some courses have notebooks in a subdirectory of the learntools
package, reflecting the fact these notebooks were authored and edited outside our templating system.
Run all tests against the staging image:
./test.sh
Run all tests against a specific image:
./test.sh -i gcr.io/kaggle-images/python:some-tag
Run only the tests for the computer_vision
track:
./test.sh -t computer_vision
Run only the tests for the 1st exercise of the computer_vision
track:
./test.sh -t computer_vision -n ex1