Need help with learntools?
Click the “chat” button below for chat support from the developer who created it, or find similar developers for support.

About the developer

Kaggle
311 Stars 181 Forks Apache License 2.0 2.4K Commits 23 Opened issues

Description

Tools and tests used in Kaggle Learn exercises

Services available

!
?

Need anything else?

Contributors list

Purpose

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.

Structure

This repo is split into two types of material. - The

learntools
folder 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/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. - The
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.

Running the tests

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

We use cookies. If you continue to browse the site, you agree to the use of cookies. For more information on our use of cookies please see our Privacy Policy.