A scalable video hosting platform written in Django.
Initially, Videofront was developed to host videos of MOOCs taught on Open edX platforms, but it can easily be used in just any web platform that requires video embedding.
- Video storage, transcoding and streaming
- A RESTful API, with a browsable GUI powered by Swagger
- A flexible and extensible set of backends to store and process videos from different providers. Out of the box, Amazon Web Services (S3 + ElasticTranscoder + Cloudfront) support is provided.
- A basic user permission system for interacting with the API
- Command line and browser-based video upload (with CORS)
- Subtitle upload, conversion to VTT format, storage and download
- Thumbnail generation and customisation
Videofront is still in early beta, although it is already used in production at FUN-MOOC. Here is the list of upcoming features, by decreasing priority:
- Development of a backend for local storage, transcoding and streaming
- Creation of an
/embedendpoint for easy video integration inside iframes - Viewer statistics
- More evolved permission system, with public & private videos
- ... We are open to feature requests!
Clone the repository:
git clone https://github.com/openfun/videofront.git
cd videofront/
Install non-python requirements:
sudo apt-get install rabbitmq-server libxml2-dev libxslt1-dev libtiff5-dev libjpeg8-dev zlib1g-dev
Install python requirements in a virtual environment:
virtualenv --python=python3 venv # note that python3 is required
source venv/bin/activate
pip install -r requirements/base.txt
If you wish to interact with Amazon Web Services, additional dependencies need to be installed:
pip install -r requirements/aws.txt
Note that you will also need to install and configure an SQL database.
Create database tables:
./manage.py migrate
./manage.py createcachetable
You will first need to create a user in Videofront to obtain a token and start interacting with the API:
$ ./manage.py createuser chucknorris fantasticpassword
Created user 'chucknorris' with token: 6f6801edef3f4b74378f2ac270be464b351efefe
Start a local server:
$ ./manage.py runserver
Start a celery worker for periodic and non-periodic tasks:
celery -A videofront worker -B # don't do this in production
Obtain a video upload url:
$ curl -X POST -H "Authorization: Token 6f6801edef3f4b74378f2ac270be464b351efefe" http://127.0.0.1:8000/api/v1/videouploadurls/
{"id":"0sqmLiEuLpGJ","expires_at":1474362128,"origin":null,"playlist":null}(env3)
Upload a video to this url:
$ curl -X POST -H "Authorization: Token 6f6801edef3f4b74378f2ac270be464b351efefe" -F [email protected] http://127.0.0.1:8000/api/v1/videos/0sqmLiEuLpGJ/upload/
Alternatively, you may use the videofront-client package instead of curl for easier interaction with the API.
Install test and contrib requirements:
pip install -r requirements/tests.txt
Run unit tests:
./manage.py test
Check test coverage:
coverage run ./manage.py test
coverage report
Pick a backend and customize the settings file accordingly:
cp videofront/settings_prod_sample_aws.py videofront/settings_prod.py
# edit videofront/settings_prod.py
The recommended approach is to start gunicorn and celery workers with supervisorctl:
$ cat /etc/supervisor/conf.d/videofront.conf
[group:videofront]
programs=gunicorn,celery,celery-beat
[program:gunicorn]
command=/home/user/videofront/venv/bin/gunicorn --name videofront --workers 12 --bind=127.0.0.1:8000 --log-level=INFO videofront.wsgi:application
directory=/home/user/videofront/src/videofront/
environment=DJANGO_SETTINGS_MODULE="videofront.settings_prod"
autostart=true
autorestart=true
user=videofront
priority=997
[program:celery]
directory=/home/user/videofront/src/videofront/
command=/home/user/videofront/venv/bin/celery worker -A videofront --loglevel=INFO --pidfile=/home/user/videofront/celery/w1.pid --hostname 'w1.%%h'
environment=DJANGO_SETTINGS_MODULE="videofront.settings_prod"
autostart=true
autorestart=true
user=videofront
priority=998
[program:celery-beat]
directory=/home/user/videofront/src/videofront/
command=/home/user/videofront/venv/bin/celery beat -A videofront --loglevel=INFO --pidfile=/home/user/videofront/celery/beat.pid --schedule /opt/videofront/celery/celerybeat-schedule
environment=DJANGO_SETTINGS_MODULE="videofront.settings_prod"
autostart=true
autorestart=true
user=videofront
priority=999
Recommended nginx configuration:
$ cat /etc/nginx/sites-enabled/videofront.vhost
upstream django {
server 127.0.0.1:8000;
}
server {
listen 80;
server_name example.com;
client_max_body_size 20M;
location /static/ {
# This depends on the STATIC_ROOT setting
alias /home/user/videofront/static/;
}
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header Host $http_host;
proxy_redirect off;
location ~ ^/api/v1/videos/(.*)/upload/ {
# Max video upload size
client_max_body_size 1G;
proxy_pass http://django;
}
location / {
proxy_pass http://django;
}
}
# Create a user and print out the corresponding access token
./manage.py createuser --admin username password
# Launch a new video transcoding job; useful if the transcoding job is stuck in pending state
./manage.py transcode-video myvideoid
AWS-specific commands:
# Create S3 buckets according to your settings
./manage.py bootstrap-s3
# Delete folders from the production S3 bucket
./manage.py delete-s3-folders videos/xxx folder1/ folder2/somefile.mp4
The code in this repository is licensed under version 3 of the AGPL unless otherwise noted. Your rights and duties are summarised here. Please see the LICENSE file for details.