IFT6758-Projet

This repository will be a shared work space for our project on NLH data analysis.

Using the project

Be sure to run pip install -e . in the project's root directory immediately after cloning.

1. Downloading the data

To download the NHL raw data for a specific season: In the project's root directory, run .\src\data/scrape.py *year* *optional: output path*
e.g. ./src/data/scrape.py 2017 download data for the 2017/2018 season. This will create a *year*.json file in the /data/datasets/json_files containing the raw data. You can also specify the output path as a second arguement

2. Cleaning the data

To clean the data and obtain the features required for visualizations, run /src/features/clean.py *path_to_json* *optional: output path
e.g. /src/data/scrape.py /data/datasets/csv_files/2017.csv
If the output_path is left emtpy, the data will be written to /data/datasets/csv_files/*year*.json

3. Visualizing the data

For data visualizations, use the notebooks found in /notebooks
Interactif_debug_tool.ipynb: Debugging tool to view every offensive play in every season.
simple_visualization.ipynb: Simple visualizations: shot efficiency by type, shot efficiency by distance, etc...
advanced_visualization.ipynb: Advanced visualization: shot map for every team by season.

Environment setup

For uniformity, I suggest using virtualenv with pip and requirements.txt to keep the tools used up to date.
With pip and virtualenv installed on your system, follow these steps:

1. Clone the repository with git clone https://github.com/MkYacine/IFT6758-Projet.git
2. In your project repo, create the virtual environment with vitualenv venv
3. Activate your virtual environment with venv\Scripts\activate
4. Run pip install -r requirements.txt to install all required packages.
   The requirements.txt file should be maintained manually; before committing your changes, run pip freeze > requirements.txt to update.

General workflow

If you're inexperienced with Git, here is a general workflow that I have used for previous team projects:

1. Create a New Branch:

Within your IDE, create a new branch from the main branch.
Name the branch in a descriptive manner, such as feature/feature-name, bugfix/bug-name.
git checkout -b feature/feature-name main

2. Implement Your Feature:

Checkout to your newly created branch.
Start implementing your feature, regularly committing changes with meaningful commit messages.
git add <file1> <file2> <file3>
git commit -m "Implemented a new feature: feature-name"

3. Fetch and Merge Main:

Before pushing your changes, fetch the latest changes from the main branch and merge them into your feature branch to resolve any conflicts and ensure smooth integration.
git checkout main
git pull
git checkout feature/feature-name
git merge main

4. Push Your Branch:

Once you've resolved any conflicts and are satisfied with your changes, push your feature branch to the remote GitHub repository on your remote branch.
git push -u origin feature/feature-name

5. Create a Pull Request:

Go to the GitHub repository online and navigate to the “Pull requests” tab.
Click on “New pull request”.
Set the base branch to main and the compare branch to your feature branch.

6. Request Reviews:

Request reviews from at least two other team members. Respond to any comments or requested changes.

7. Get Approval and Merge:

Click on “Merge pull request” to merge your changes into the main branch.

8. Clean Up:

Delete the remote feature branch from GitHub.
Switch to the main branch in your local environment, pull the latest changes, and delete the local feature branch.
git branch -d feature/feature-name
git push origin --delete feature/feature-name