# django-peertube-runner-connector: A django application to connect to a peertube runner and transcode videos
[](https://www.python.org/)
[](https://www.djangoproject.com/)
[](https://circleci.com/gh/openfun/django-peertube-runner-connector/tree/main)
## Overview
django-peertube-runner-connector is designed to use [Peertube](https://github.com/Chocobozzz/PeerTube/) transcoding runners outside of Peertube App. It implements a set of endpoints with [Django Rest Framework](https://www.django-rest-framework.org/) and a [SocketIO](https://python-socketio.readthedocs.io/en/latest/) server that allow runners to request jobs, updated job status, download media files and upload the transcoded media files. It provides a function that can be used by your app that will launch the transcoding process.
To make use of the SocketIO server, this app only work in ASGI.
## Architecture
### Runner API
This part will interact with Peertube runners. It is not designed to be used by a user as it reproduces what the Peertube App is doing in order to manage runners / jobs.
#### Runner Behavior
Jobs are stored in a Database, and runners hit the `/request` endpoint to get the available jobs to transcode.
### The transcode video function
The function receives a video file and a name, and then creates transcoding jobs for it.
We use function `probe` of [python-ffmpeg](https://github.com/kkroening/ffmpeg-python) library, to get a thumbnail and all the necessary metadata to create transcoding jobs. Once the jobs are created, the WebSocket server emits an event to inform runners of a new pending jobs.
#### Job implementation
Currently we didn't implement all the transcoding jobs the runner can do. We are planning to implement more jobs in the future. For now, the API only implements the following jobs:
- [x] HLS transcoding
- [ ] VOD web video transcoding
- [ ] Live transcoding
- [ ] VOD audio merge transcoding
- [ ] Video Studio transcoding
Theses jobs are created and handled through their respective classes in `api.transcoding.utils.job_handlers` directory. Some of them are already almost implemented but are not used, so they are commented.
### SocketIO server
The SocketIO server is used to communicate with runners. It is only used to inform runners of new jobs, thus, make this part very simple. It implements only one function that emits the event `available-jobs` to runners when a new job is created. Once a runner receives this event, it will hit the `/request` endpoint in the Runner API to get the new job.
## Installation
Once you have installed the library, you will need to setup your project to use it (see [configuration](#configuration) part). You can find a demo application in the `tests` directory.
### PyPi
To install the library with pip, enter the following command:
```shell
pip install django-peertube-runner-connector
```
### Local
To install the library locally, enter the following commands at the root of the project:
build the library:
```shell
python setup.py sdist bdist_wheel
```
This should create a ``dist`` directory with the library files.
Then you can go in your application, source your virtual environment and install the library with pip:
```shell
pip install /path/to/django-peertube-runner-connector/dist/django_peertube_runner_connector-1.tar
```
## Setup
### Configuration
```python
# settings.py
INSTALLED_APPS = [
# ...
"rest_framework",
"django_peertube_runner_connector.apps.DjangoPeertubeRunnerConnectorConfig",
"storages", # optional django-storages library
]
# Transcoding resolution settings
TRANSCODING_ALWAYS_TRANSCODE_ORIGINAL_RESOLUTION = False
TRANSCODING_RESOLUTIONS_144P = False
TRANSCODING_RESOLUTIONS_240P = False
TRANSCODING_RESOLUTIONS_360P = True
TRANSCODING_RESOLUTIONS_480P = True
TRANSCODING_RESOLUTIONS_720P = True
TRANSCODING_RESOLUTIONS_1080P = False
TRANSCODING_RESOLUTIONS_1440P = False
TRANSCODING_RESOLUTIONS_2160P = False
# Transcoding fps settings
TRANSCODING_FPS_MIN = 1
TRANSCODING_FPS_STANDARD = [24, 25, 30]
TRANSCODING_FPS_HD_STANDARD = [50, 60]
TRANSCODING_FPS_AUDIO_MERGE = 25
TRANSCODING_FPS_AVERAGE = 30
TRANSCODING_FPS_MAX = 60
TRANSCODING_FPS_KEEP_ORIGIN_FPS_RESOLUTION_MIN = 720
# Max number of times a job can fail before being marked as failed
TRANSCODING_RUNNER_MAX_FAILURE = 5
# The callback path to a function that will be called when a video transcoding ended
TRANSCODING_ENDED_CALLBACK_PATH = ""
# The django-peertube-runner-connector app uses the django storage system to store the transcoded videos.
# It uses the "videos" storage where you can configure the storage backend you want to use.
STORAGES = {
"default": {
"BACKEND": "django.core.files.storage.FileSystemStorage",
},
"videos": { # This is the storage used to store the transcoded videos
"BACKEND": "app.storage.MyCustomFileSystemVideoStorage", # You can use the storage backend you want
},
"staticfiles": {
"BACKEND": "django.contrib.staticfiles.storage.StaticFilesStorage",
},
}
```
#### Storage
Django-peertube-runner-connector uses the django storage system to store the transcoded videos. It uses the "videos" storage where you can configure the storage backend you want to use. To use an S3 like storage, you can use the [django-storages](https://django-storages.readthedocs.io/en/latest/) library. Here is an example of a custom storage backend that uses the S3 storage:
```python
# app/storage.py
from storages.backends.s3boto3 import S3Boto3Storage
class MyS3VideoStorage(S3Boto3Storage):
"""Custom S3 storage class."""
bucket_name = "my-bucket"
```
then you can use it in your settings:
```python
# settings.py
# ... S3 settings
STORAGES = {
"default": {
"BACKEND": "django.core.files.storage.FileSystemStorage",
},
"videos": {
"BACKEND": "app.storage.MyS3VideoStorage", # Your custom storage backend
},
"staticfiles": {
"BACKEND": "django.contrib.staticfiles.storage.StaticFilesStorage",
},
}
```
#### Server
To make use of the SocketIO server, you need to have ASGi server like [uvicorn](https://www.uvicorn.org/).
Here is an example on how to configure your asgi server to use the SocketIO server:
```python
from configurations.asgi import get_asgi_application
django_asgi_app = get_asgi_application()
# its important to make all other imports below this comment
import socketio
from django_peertube_runner_connector.socket import sio
application = socketio.ASGIApp(sio, django_asgi_app)
```
Add the runners api views to your urls:
```python
# urls.py
from django_peertube_runner_connector.urls import (
urlpatterns as django_peertube_runner_connector_urls,
)
urlpatterns += django_peertube_runner_connector_urls
```
If your application is distributed on multiple servers, you will probably need
to use a message queue. We manage redis and redis sentinel manager. For this,
you have to define this settings
#### Redis sentinel
- `DJANGO_PEERTUBE_RUNNER_CONNECTOR_SENTINELS`: A list of sentinel nodes.
Each node is represented by a pair (hostname, port). Example: [('localhost', 26379)]
- `DJANGO_PEERTUBE_RUNNER_CONNECTOR_SENTINELS_MASTER`: The master sentinel name. Example: mymaster
#### Redis
- `DJANGO_PEERTUBE_RUNNER_CONNECTOR_REDIS`: The redis url. Example: `redis://localhost:6379`
Voilà! Your server should be ready!
### Demo application
For testing purpose, you can find a basic django app using the django-peertube-runner-connector library in the `tests` directory. You use run it with the following commands:
Create your virtual environment:
```shell
python -m venv env
source env/bin/activate
```
Install the dependencies:
```shell
pip install -e ."[dev]"
```
Go to the tests directory:
```shell
cd tests
```
Create the database and run the migrations:
```shell
python manage.py migrate
```
Collect the static files:
```shell
python manage.py collectstatic
```
Create a super user:
```shell
python manage.py createsuperuser
```
Launch the server with an asgi server like uvicorn:
```shell
python -m uvicorn app.asgi:application --reload
```
Once the server is running, you can register your server to a peertube runner.
#### Registering a Peertube runner
First you will to generate a registration token. To do so, use the following command and keep the registrationToken for late:
```shell
python tests/manage.py create_runner_registration_token
```
First you will need a Peertube runner. To launch one, follow the instructions (theses instructions are made by me and for development purpose only)
Clone and go to the [peertube repository](https://github.com/Chocobozzz/PeerTube)
```shell
git clone https://github.com/Chocobozzz/PeerTube
```
```shell
cd PeerTube
```
Install the dependencies
```shell
cd apps/peertube-runner
npm install
cd ../../
```
Build the runner
```shell
npm run build:peertube-runner
```
Launch the runner
```shell
./apps/peertube-runner/dist/peertube-runner.js server
```
Open a new terminal in the same directory and register your runner to your django app
```shell
./apps/peertube-runner/dist/peertube-runner.js register --url http://localhost:8000 --registration-token $MY_TOKEN --runner-name transcode-api
```
#### Created a transcoding jobs and receive the transcoded video
You can now launch a transcoding job with using the ``http://127.0.0.1:8000/videos/upload`` end point of the django app by sending a multipart/form-data request with your file as the value of the ``videoFile`` key. This video view is given by the test app not by the django-peertube-runner-connector app. This should population a directory named ``video-[uuid]`` in the root of the project with the result of the transcoding job.
### Launch test
To launch the tests, enter the following commands at the root of the project:
Create your virtual environment:
```shell
python -m venv env
source env/bin/activate
```
Install the dependencies:
```shell
pip install -e ."[dev]"
```
Launch the tests:
```shell
make test
```
## License
This work is released under the MIT License (see [LICENSE](./LICENSE)).
MIT License
Copyright (c) 2023 France Université Numérique
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Raw data
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"description": "# django-peertube-runner-connector: A django application to connect to a peertube runner and transcode videos \n\n[](https://www.python.org/)\n[](https://www.djangoproject.com/)\n[](https://circleci.com/gh/openfun/django-peertube-runner-connector/tree/main)\n\n## Overview \ndjango-peertube-runner-connector is designed to use [Peertube](https://github.com/Chocobozzz/PeerTube/) transcoding runners outside of Peertube App. It implements a set of endpoints with [Django Rest Framework](https://www.django-rest-framework.org/) and a [SocketIO](https://python-socketio.readthedocs.io/en/latest/) server that allow runners to request jobs, updated job status, download media files and upload the transcoded media files. It provides a function that can be used by your app that will launch the transcoding process.\n\nTo make use of the SocketIO server, this app only work in ASGI.\n\n\n## Architecture\n\n### Runner API\n\nThis part will interact with Peertube runners. It is not designed to be used by a user as it reproduces what the Peertube App is doing in order to manage runners / jobs.\n\n\n#### Runner Behavior\n\nJobs are stored in a Database, and runners hit the `/request` endpoint to get the available jobs to transcode.\n\n\n### The transcode video function\n\nThe function receives a video file and a name, and then creates transcoding jobs for it.\n\nWe use function `probe` of [python-ffmpeg](https://github.com/kkroening/ffmpeg-python) library, to get a thumbnail and all the necessary metadata to create transcoding jobs. Once the jobs are created, the WebSocket server emits an event to inform runners of a new pending jobs.\n\n\n#### Job implementation\n\nCurrently we didn't implement all the transcoding jobs the runner can do. We are planning to implement more jobs in the future. For now, the API only implements the following jobs:\n\n- [x] HLS transcoding\n- [ ] VOD web video transcoding\n- [ ] Live transcoding\n- [ ] VOD audio merge transcoding\n- [ ] Video Studio transcoding\n\nTheses jobs are created and handled through their respective classes in `api.transcoding.utils.job_handlers` directory. Some of them are already almost implemented but are not used, so they are commented.\n\n### SocketIO server\n\nThe SocketIO server is used to communicate with runners. It is only used to inform runners of new jobs, thus, make this part very simple. It implements only one function that emits the event `available-jobs` to runners when a new job is created. Once a runner receives this event, it will hit the `/request` endpoint in the Runner API to get the new job.\n\n## Installation\n\nOnce you have installed the library, you will need to setup your project to use it (see [configuration](#configuration) part). You can find a demo application in the `tests` directory.\n\n### PyPi\n\nTo install the library with pip, enter the following command:\n\n```shell\npip install django-peertube-runner-connector\n```\n\n### Local\nTo install the library locally, enter the following commands at the root of the project:\n\nbuild the library:\n```shell\npython setup.py sdist bdist_wheel\n```\n\nThis should create a ``dist`` directory with the library files.\n\nThen you can go in your application, source your virtual environment and install the library with pip:\n```shell\npip install /path/to/django-peertube-runner-connector/dist/django_peertube_runner_connector-1.tar\n```\n\n## Setup\n\n### Configuration\n\n\n```python\n# settings.py\nINSTALLED_APPS = [\n # ...\n \"rest_framework\",\n \"django_peertube_runner_connector.apps.DjangoPeertubeRunnerConnectorConfig\",\n \"storages\", # optional django-storages library\n]\n\n# Transcoding resolution settings\nTRANSCODING_ALWAYS_TRANSCODE_ORIGINAL_RESOLUTION = False\nTRANSCODING_RESOLUTIONS_144P = False\nTRANSCODING_RESOLUTIONS_240P = False\nTRANSCODING_RESOLUTIONS_360P = True\nTRANSCODING_RESOLUTIONS_480P = True\nTRANSCODING_RESOLUTIONS_720P = True\nTRANSCODING_RESOLUTIONS_1080P = False\nTRANSCODING_RESOLUTIONS_1440P = False\nTRANSCODING_RESOLUTIONS_2160P = False\n\n# Transcoding fps settings\nTRANSCODING_FPS_MIN = 1\nTRANSCODING_FPS_STANDARD = [24, 25, 30]\nTRANSCODING_FPS_HD_STANDARD = [50, 60]\nTRANSCODING_FPS_AUDIO_MERGE = 25\nTRANSCODING_FPS_AVERAGE = 30\nTRANSCODING_FPS_MAX = 60\nTRANSCODING_FPS_KEEP_ORIGIN_FPS_RESOLUTION_MIN = 720\n\n# Max number of times a job can fail before being marked as failed\nTRANSCODING_RUNNER_MAX_FAILURE = 5\n\n# The callback path to a function that will be called when a video transcoding ended\nTRANSCODING_ENDED_CALLBACK_PATH = \"\"\n\n# The django-peertube-runner-connector app uses the django storage system to store the transcoded videos.\n# It uses the \"videos\" storage where you can configure the storage backend you want to use.\nSTORAGES = {\n \"default\": {\n \"BACKEND\": \"django.core.files.storage.FileSystemStorage\",\n },\n \"videos\": { # This is the storage used to store the transcoded videos\n \"BACKEND\": \"app.storage.MyCustomFileSystemVideoStorage\", # You can use the storage backend you want\n },\n \"staticfiles\": {\n \"BACKEND\": \"django.contrib.staticfiles.storage.StaticFilesStorage\",\n },\n}\n```\n\n\n#### Storage\n\nDjango-peertube-runner-connector uses the django storage system to store the transcoded videos. It uses the \"videos\" storage where you can configure the storage backend you want to use. To use an S3 like storage, you can use the [django-storages](https://django-storages.readthedocs.io/en/latest/) library. Here is an example of a custom storage backend that uses the S3 storage:\n\n```python\n# app/storage.py\nfrom storages.backends.s3boto3 import S3Boto3Storage\n\n\nclass MyS3VideoStorage(S3Boto3Storage):\n \"\"\"Custom S3 storage class.\"\"\"\n\n bucket_name = \"my-bucket\"\n```\n\nthen you can use it in your settings:\n\n```python\n# settings.py\n\n# ... S3 settings\n\nSTORAGES = {\n \"default\": {\n \"BACKEND\": \"django.core.files.storage.FileSystemStorage\",\n },\n \"videos\": { \n \"BACKEND\": \"app.storage.MyS3VideoStorage\", # Your custom storage backend\n },\n \"staticfiles\": {\n \"BACKEND\": \"django.contrib.staticfiles.storage.StaticFilesStorage\",\n },\n}\n```\n\n#### Server\n\nTo make use of the SocketIO server, you need to have ASGi server like [uvicorn](https://www.uvicorn.org/).\n\nHere is an example on how to configure your asgi server to use the SocketIO server:\n\n\n```python\nfrom configurations.asgi import get_asgi_application\n\ndjango_asgi_app = get_asgi_application()\n\n\n# its important to make all other imports below this comment\nimport socketio \n\nfrom django_peertube_runner_connector.socket import sio \n\n\napplication = socketio.ASGIApp(sio, django_asgi_app)\n\n```\n\nAdd the runners api views to your urls:\n\n```python\n# urls.py\nfrom django_peertube_runner_connector.urls import (\n urlpatterns as django_peertube_runner_connector_urls,\n)\n\nurlpatterns += django_peertube_runner_connector_urls\n```\n\nIf your application is distributed on multiple servers, you will probably need\nto use a message queue. We manage redis and redis sentinel manager. For this,\nyou have to define this settings\n\n#### Redis sentinel\n\n- `DJANGO_PEERTUBE_RUNNER_CONNECTOR_SENTINELS`: A list of sentinel nodes. \nEach node is represented by a pair (hostname, port). Example: [('localhost', 26379)]\n- `DJANGO_PEERTUBE_RUNNER_CONNECTOR_SENTINELS_MASTER`: The master sentinel name. Example: mymaster\n\n#### Redis\n\n- `DJANGO_PEERTUBE_RUNNER_CONNECTOR_REDIS`: The redis url. Example: `redis://localhost:6379`\n\nVoil\u00e0! Your server should be ready!\n\n\n### Demo application\n\nFor testing purpose, you can find a basic django app using the django-peertube-runner-connector library in the `tests` directory. You use run it with the following commands:\n\nCreate your virtual environment:\n```shell\npython -m venv env\nsource env/bin/activate\n```\n\nInstall the dependencies:\n```shell\npip install -e .\"[dev]\"\n```\n\nGo to the tests directory:\n```shell\ncd tests\n```\n\nCreate the database and run the migrations:\n```shell\npython manage.py migrate\n```\n\nCollect the static files:\n```shell\npython manage.py collectstatic\n```\n\nCreate a super user:\n```shell\npython manage.py createsuperuser\n```\n\nLaunch the server with an asgi server like uvicorn:\n```shell\npython -m uvicorn app.asgi:application --reload\n```\n\nOnce the server is running, you can register your server to a peertube runner. \n\n#### Registering a Peertube runner\n\nFirst you will to generate a registration token. To do so, use the following command and keep the registrationToken for late:\n```shell\npython tests/manage.py create_runner_registration_token\n```\n\nFirst you will need a Peertube runner. To launch one, follow the instructions (theses instructions are made by me and for development purpose only)\n\nClone and go to the [peertube repository](https://github.com/Chocobozzz/PeerTube)\n```shell\ngit clone https://github.com/Chocobozzz/PeerTube\n```\n```shell\ncd PeerTube\n```\n\nInstall the dependencies\n```shell\ncd apps/peertube-runner\nnpm install\ncd ../../\n```\nBuild the runner\n```shell\nnpm run build:peertube-runner\n```\n\nLaunch the runner\n```shell\n./apps/peertube-runner/dist/peertube-runner.js server\n```\n\nOpen a new terminal in the same directory and register your runner to your django app\n```shell\n./apps/peertube-runner/dist/peertube-runner.js register --url http://localhost:8000 --registration-token $MY_TOKEN --runner-name transcode-api\n```\n\n#### Created a transcoding jobs and receive the transcoded video\n\nYou can now launch a transcoding job with using the ``http://127.0.0.1:8000/videos/upload`` end point of the django app by sending a multipart/form-data request with your file as the value of the ``videoFile`` key. This video view is given by the test app not by the django-peertube-runner-connector app. This should population a directory named ``video-[uuid]`` in the root of the project with the result of the transcoding job.\n\n### Launch test\n\nTo launch the tests, enter the following commands at the root of the project:\n\nCreate your virtual environment:\n```shell\npython -m venv env\nsource env/bin/activate\n```\n\nInstall the dependencies:\n```shell\npip install -e .\"[dev]\"\n```\n\nLaunch the tests:\n```shell\nmake test\n```\n\n\n## License\n\nThis work is released under the MIT License (see [LICENSE](./LICENSE)).\nMIT License\n\nCopyright (c) 2023 France Universit\u00e9 Num\u00e9rique\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n",
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