equidistant-ml

Contains ml for equidistant, an app to estimate journey times.

Setup

Required: python dependencies, python 3.8.8, poetry, conda

It's recommended to set up with a python installer (Conda or PyEnv will work).

conda create --name py388 python=3.8.8

conda activate py388

conda install poetry

Install python dependencies and editable package

poetry install

Run tests

This project uses pytest and pytest_commander to run tests.

To run the test suite, run:

poetry run pytest_commander

This project uses GitHub actions to run the pytest suite on any push automatically.

Deployment & CI / CD

This project is deployed on Heroku.

Pull requests opened to main will trigger a Review App at: https://dashboard.heroku.com/apps/equidistant-ml

Merged PRs to main will auto-deploy to staging.

TODO

• Create a linear approximator as a baseline model [DONE]
• Some inspiration can be taken from: https://towardsdatascience.com/simple-example-of-2d-density-plots-in-python-83b83b934f67
• Add tests in GitHub actions CI

Credits

This package was created with Cookiecutter and the btjones-me/cookiecutter-pypackage project template.

• Cookiecutter: https://github.com/cookiecutter/cookiecutter
• btjones-me/cookiecutter-pypackage: https://github.com/btjones-me/cookiecutter-pypackage