This repo is a competition submission for the Zindi Uber Movement SANRAL Cape Town Challenge . This solution, using Non-negative Matrix Factorization took first place in the competition hackathon and remained top of the public and private leaderboards for 4 months despite is simplicity. Please enjoy.

Incident data in Cape Town, South Africa has been provided by SANRAL Freeway Management System and travel times between zones in Cape Town have been provided by Uber Movement. The aim of this challenge is to forecast if an incident will occur for each hour of each day per 500m road segment along the major roadways in Cape Town for 1 January 2019 to 31 March 2019.

Dependencies should be declared in src/requirements.txt for pip installation and src/environment.yml for conda installation.

To install them, run:

kedro install

You can run your Kedro project with:

kedro run

In order to use notebooks in your Kedro project, you need to install Jupyter:

pip install jupyter

For using Jupyter Lab, you need to install it:

pip install jupyterlab

After installing Jupyter, you can start a local notebook server:

kedro jupyter notebook

You can also start Jupyter Lab:

kedro jupyter lab

And if you want to run an IPython session:

kedro ipython

Running Jupyter or IPython this way provides the following variables in scope: proj_dir, proj_name, conf, io, parameters and startup_error.

Once you are happy with a notebook, you may want to move your code over into the Kedro project structure for the next stage in your development. This is done through a mixture of cell tagging and Kedro CLI commands.

By adding the node tag to a cell and running the command below, the cell's source code will be copied over to a Python file within src/<package_name>/nodes/.

kedro jupyter convert <filepath_to_my_notebook>

Note: The name of the Python file matches the name of the original notebook.

Alternatively, you may want to transform all your notebooks in one go. To this end, you can run the following command to convert all notebook files found in the project root directory and under any of its sub-folders.

kedro jupyter convert --all

In order to automatically strip out all output cell contents before committing to git, you can run kedro activate-nbstripout. This will add a hook in .git/config which will run nbstripout before anything is committed to git.

Note: Your output cells will be left intact locally.

In order to package the project's Python code in .egg and / or a .wheel file, you can run:

kedro package

After running that, you can find the two packages in src/dist/.

To build API docs for your code using Sphinx, run:

kedro build-docs

See your documentation by opening docs/build/html/index.html.

To generate or update the dependency requirements for your project, run:

kedro build-reqs

This will copy the contents of src/requirements.txt into a new file src/requirements.in which will be used as the source for pip-compile. You can see the output of the resolution by opening src/requirements.txt.

After this, if you'd like to update your project requirements, please update src/requirements.in and re-run kedro build-reqs.