test_package

Doc, install and writing code

Create a new github repository, check all marks ! gitignore, license and readme.
Clone the repository on your computer
Write a doc for the function
Organize code as a package : folder/code/functions.py, and add an __init__.py file, in which only the version is present.
At the root, write a setup.py function that will allow to install the package, and then do pip install -e.. This should not return any error.
In the code folder, create a tests folder, a test_linear_regression.py file in it and write several test functions, with names starting with test_. Then, run pytest at the root file. All tests should pass
Check that the code is compatible with pep 8 using the command flake8
Upload everything on github by first adding all new files using git add ..., then commiting by using git commit -am (write a message here) and then git push. Check on github that the new code is here.

At the root, create an examples folder. In this folder, create a function plot_simple_example in which you write a small example of what the linear regression code can do.
Add some plots using matplotlib.

Add a .github/workflows folder at the root, and write a unittests.yml file in it that runs continuous integration on github. This should run the flake8 and unit tests command, everytime there is a push on the main github branch, or that somebody does a pull request

By pair, fork the github repository of one of the other student, create a new branch using git checkout -b branch-name, then implement regularized linear regression in the linear_regression/linear_regression.py file. Then, commit your changes, push the branch on github, and do a pull request on the other students' repo.
Check that the continuous integration tests are run, and that everything it ok. Then, merge the pull request.