Media Recommendation Engine, an API that recommends content such as movies, tv shows, anime, songs etc. Built with FastAPI.
- Features
- API Reference
- Screenshots
- Demo
- Run on Local Machine
- Deployment
- Contributing
- Technologies Used
- FAQ
- License
- Light/dark mode toggle
- Live previews
- Fullscreen mode
- Cross platform
GET /api/home
Parameter | Type | Description |
---|---|---|
api_key |
string |
Required. Your API key |
GET /api/items/${id}
Parameter | Type | Description |
---|---|---|
id |
string |
Required. Id of item to fetch |
Takes two numbers and returns the sum.
- Clone the repository to your local machine:
git clone https://github.com/Nneji123/Media-Recommendation-Engine.git
- Install the requirements:
cd Media-Recommendation-Engine
pip install -r requirements.txt
- Open a bash/cmd in the directory and run:
uvicorn app:app --reload --port 8000
- After the above steps have been carried out you can now view the documentation of the API.
To visit the FastAPI documentation go to http://localhost:8000/ with a web browser.
- Make sure the API is running already from the above steps.
- Install locust:
pip install locust
- Run locust tests
cd tests
locust -f locust_test_load.py
- Set the number of IP's and address and then run the load tests
- Install the requirements
pip install -r requirements.txt
- Change the directory
cd tests
- Run the tests with pytest
pytest test_api.py --html=pytest_report.html --self-contained-html
Assuming you have git and heroku cli installed just carry out the following steps:
- Clone the repository
git clone https://github.com/Nneji123/Media-Recommendation-Engine.git
- Change the working directory
cd Media-Recommendation-Engine
- Create the heroku app
heroku create your-app-name
Replace your-app-name with the name of your choosing.
- Set the heroku cli git remote to that app
heroku git:remote your-app-name
- Set the heroku stack setting to container
heroku stack:set container
- Push to heroku
git push heroku main
You can also deploy the API to AWS using a free tier EC2 instance by watching the video below:
Contributions are always welcome!
See CONTRIBUTING.MD
for ways to get started.
Please adhere to this project's code of conduct
.
This API can be used to suggest recommendations for an end user such as movies, games, songs etc.
Yes