1. Clone the repository.
2. Open the website folder.
3. Create a .env file in the website folder.
4. Add the following environment variables to the .env file:

## Azure Blob Storage

AZURE_STORAGE_CONNECTION_STRING = 'connection_string'
AZURE_STORAGE_CONTAINER_SUBMISSION = 'container_name'
AZURE_STORAGE_CONTAINER_VALIDATOR = 'container_name'

## Backend 
SECRET_KEY = "secret_key"
DB_NAME = "benchlab"
DB_HOST = "localhost"
DB_USER = "benchlabuser"
DB_PASSWORD = "password"

DEBUG = "True"

EMAIL_BACKEND = "django.core.mail.backends.smtp.EmailBackend"
EMAIL_HOST = "mail.tptech.nl"
EMAIL_FROM = "[email protected]"
EMAIL_HOST_USER = "[email protected]"
EMAIL_HOST_PASSWORD = "password"
EMAIL_PORT = "587"
EMAIL_USE_TLS = "True"

FRONTEND_URL = "http://localhost:5173"

ALLOWED_HOSTS = "*"
CSRF_TRUSTED_ORIGINS = "http://localhost"
JUDGE_HOST = "localhost"

## Frontend 
VITE_API_URL = "http://localhost:8000/api"

For the value of EMAIL_HOST_PASSWORD, ask someone who set up the repository already.

1. Make sure you have Node.js 20 LTS installed on your machine. If not, please install it. LINUX ONLY: You might need to use Node Version Manager (nvm) to install this specific version of Node.js, as the default install command via apt has an older version.
2. Install/Activate yarn (run corepack enable, this command might require admin priviliges).
3. Open the frontend folder.
4. Run yarn (this will install all dependencies). DO NOT USE NPM TO INSTALL DEPENDENCIES.
5. To start vite you can run yarn vite.

1. Install MySQL.
2. Create a basic server.
3. Open the created database and run CREATE DATABASE benchlab; (using sudo mysql on Linux).
4. The run CREATE USER 'benchlabuser'@'localhost' IDENTIFIED WITH mysql_native_password BY 'password';.
5. Finally run GRANT ALL PRIVILEGES ON benchlab.* TO 'benchlabuser'@'localhost';.
6. Adjust the .env file based on the properties defined above, in case you modified any values (e.g. the password).

1. Make sure you have Python 3.12 installed. On Linux, this can be done with sudo add-apt-repository ppa:deadsnakes/ppa, followed by sudo apt install python3.12 python3.12-venv python3.12-dev (since you also need venv and the Python development headers).
2. On Linux, you also need the following: sudo apt install pkg-config default-libmysqlclient-dev build-essential (used by mysqlclient).
3. Create a virtual environment by running python -m venv .venv in the website(root) directory.
4. Select the virtual environment as your VS Code interpreter.
5. Activate the virtual environment by running (Linux) source .venv/bin/activate or (Windows) .venv\Scripts\activate.bat.
6. Navigate your command line into the backend folder (e.g. using cd backend).
7. Run pip install -r requirements.txt (this will install all dependencies).
8. Install the Ruff VSCode extension.
9. Run migrations: python manage.py makemigrations and python manage.py migrate.
10. Run seeder: python manage.py loaddata XXXX_filename.json where XXXX_filename.json is the file with the highest number in backend/api/fixtures.
11. To start the server, use python manage.py runserver.

After following the steps above, the folder structure should look like this:

website/
├─ .github/
├─ .venv/
├─ backend/
├─ docs/
├─ frontend/
├─ .env
├─ .gitignore
├─ README.md
├─ ruff.toml
├─ SECURITY.md

Use the production branch to deploy the webapp.

To get initial data in the database run python manage.py loaddata XXXX_filename.json. To remove all data from the database run python manage.py flush this will permanently delete all data from the database so be carefull with this. Note: the passwords for the currently seeded accounts are admin, staff and user respectively

A convenient way to make new seeder files is by creating new entries in the tables via the django admin panel (localhost:8000/admin) and then running the following command: python manage.py dumpdata api --indent 4 --output=api/fixtures/XXXX_filename.json. Here count up from previous highest number in the folder and maybe give the new file a somewhat descriptive name.

You can also choose to write your own seeder files from scratch with json but that can be a bit of a hassle because you have to manually do all the foreign keys.

NOTE: this is not yet a very streamlined workflow so if you find out stuff doesn't work or if you find a better way, please edit the file and make a pull request for it. When doing migrations, sometimes it's not necessary to change all the data, in those cases make a new fixture file after migrating so that the changes are reflected in the seeded data. If you do need to change data this can be a workflow:

• run python manage.py makemigrations to generate the migration files.
• run python manage.py migrate to migrate the changes.
• adapt the seeder files to reflect the new changes in the db.
• run python manage.py flush to empty the database.
• run python manage.py loaddata XXXX_filename.json to seed the db with the new data.

If the migrate command gives an error, it might be easier to reset your entire database. This can be done with python manage.py reset_db, rather than the flush command.

Ruff is a tool that checks, based on some rules, the Python code, similar to Java Checkstyle.

To change the settings or add features to ruff check the ruff.toml file. This can be found in the backend folder. This file also contains explanations for each setting/rule.

The following keybinds might be different on your machine:

Pressing Shift + Alt + F will allow you to use Ruff to format and fix the code. Keep in mind that Ruff is not able to fix all issues.

Pressing Shift + Alt + O will use isort to sort the imports.

Navigate to show output as shown below in the Usage section. If show output in the workflow failed and it states Code violations found!!!!! at the bottom then you're code does not adhere to the quality standards. The table in the output above shows which categories have violations (in red). For a better understanding of quality standards you can look at the tables in the Metrics section.

For any questions about this workflow or issues contact Tom.

This worklfow is run whenever a commit is pushed to main or a pr into main is made. It may take between 1 to 3 minutes to complete the analysis. To view the results do the following:

Navigate to the github action and click on the job Code Quality:

The Show output tab shows all the metrics gathered by the tools:

The output starts with some intermediate debug results, which you can ignore. The evaluation of you code is shown in the tables below. Threshold violation percentages is the percentage of files/code that violate the metrics shown in the table below. Ranks shows the combined rank for each maintainability attribute. It shows the grade that our code would get according to the metrics that the TU/e uses.

For each characteristic we compute what percentage of the code is above the threshold. Then a rank is computed for that characteristic. For each Maintainability attribute we compute the average rank (based on its corresponding code characteristics).

The code quality assessment document that TU/e uses can be found here.

TU/e uses simian to analyse code duplication. understand is used to derive all the other metrics.

Note: understand incorrectly computes Module coupling, it only accounts for classes in the same file.

In order to run backend unit tests, navigate to the backend folder, then run the following command: python manage.py test tests

When you want to run frontend unit tests for the first time, navigate to the fontend folder. You might have to run this command first to install the necessary dependencies: yarn To run frontend unit tests, navigate to the fontend folder, then run the following command: yarn run test If you would like to also see code coverage, run the following command instead: yarn run test --coverage