- Asynchronously fetch data (videos) using YouTube API after every 5 minutes and store the data in the database. The search query used to fetch data is
tutorial). - GET API (
/videos/) to retrieve paginated response (videos) from the local database. - SEARCH API (
/videos/search/?search=<search_query>) to retrieve paginated response (videos) based on the search query on video title and description. The Search API also supports fuzzy matching/pratial matching on video title and description. - Support for multiple API keys.
- Download and install Python 3.8
- Download and install Git.
- Clone the repository to your local machine
$ git clone https://github.com/garg3133/personal-yt-api.git - Change directory to JagratiWebApp
$ cd personal-yt-api - Install virtualenv
$ pip install virtualenv - Create a virtual environment
$ virtualenv env -p python3.8 - Activate the env:
$ source env/bin/activate(for linux)> ./env/Scripts/activate(for Windows PowerShell) - Install the requirements:
$ pip install -r requirements.txt - Create a new file in the root directory of the repository with name
.envand add the following content in it:YOUTUBE_DATA_API_KEY = 'your-youtube-api-key' - Make migrations
$ python manage.py makemigrations - Migrate the changes to the database
$ python manage.py migrate - Create admin
$ python manage.py createsuperuser - Run the server
$ python manage.py runserver
- Clone the repository to your local machine
$ git clone https://github.com/garg3133/personal-yt-api.git - Change directory to JagratiWebApp
$ cd personal-yt-api - Create a new file in the root directory of the repository with name
.envand add the following content in it:YOUTUBE_DATA_API_KEY = 'yt-api-key1,yt-api-key2,...' - Run migrations
docker-compose run web python manage.py migrate - Build the docker image
docker-compose build - Run the docker image
docker-compose up - The server will start at default port (8000), head over to your web browser to test at
http://localhost:8000.