# django-video-encoding





django-video-encoding helps to convert your videos into different formats and resolutions.
## Requirements
* Python 3.6.1 or newer
* ffmpeg and ffprobe
## Installation
1. Install django-video-encoding
```sh
pip install django-video-encoding
```
2. Add `video_encoding` to your `INSTALLED_APPS`.
## Integration
Add a `VideoField` and a `GenericRelation(Format)` to your model.
You can optionally store the `width`, `height` and `duration` of the video
by supplying the corresponding field names to the `VideoField`.
```python
from django.contrib.contenttypes.fields import GenericRelation
from django.db import models
from video_encoding.fields import VideoField
from video_encoding.models import Format
class Video(models.Model):
width = models.PositiveIntegerField(editable=False, null=True)
height = models.PositiveIntegerField(editable=False, null=True)
duration = models.FloatField(editable=False, null=True)
file = VideoField(width_field='width', height_field='height',
duration_field='duration')
format_set = GenericRelation(Format)
```
To show all converted videos in the admin, you should add the `FormatInline`
to your `ModelAdmin`
```python
from django.contrib import admin
from video_encoding.admin import FormatInline
from .models import Video
@admin.register(Video)
class VideoAdmin(admin.ModelAdmin):
inlines = (FormatInline,)
list_dispaly = ('get_filename', 'width', 'height', 'duration')
fields = ('file', 'width', 'height', 'duration')
readonly_fields = fields
```
The conversion of the video should be done in a separate process. Typical
options are [django-rq] or [celery]. We will use `django-rq` in the
following example. The configuration for `celery` is similar.
`django-video-encoding` already provides a task (`convert_all_videos`)
for converting all videos on a model.
This task should be triggered when a video was uploaded. Hence we listen to
the `post-save` signal and enqueue the saved instance for processing.
```python
# signals.py
from django.db.models.signals import post_save
from django.dispatch import receiver
from django_rq import enqueue
from video_encoding import tasks
from .models import Video
@receiver(post_save, sender=Video)
def convert_video(sender, instance, **kwargs):
enqueue(tasks.convert_all_videos,
instance._meta.app_label,
instance._meta.model_name,
instance.pk)
```
After a while You can access the converted videos using
```python
video = Video.objects.get(...)
for format in video.format_set.complete().all():
# do something
```
[django-rq]: https://github.com/ui/django-rq
[celery]: http://www.celeryproject.org/
### Generate a video thumbnail
The backend provides a `get_thumbnail()` method to extract a thumbnail from a video.
Here is a basic example on how to generate the thumbnail and store it in the model.
```python
# models.py
from django.db import models
class Video(models.Model):
width = models.PositiveIntegerField(editable=False, null=True)
height = models.PositiveIntegerField(editable=False, null=True)
duration = models.FloatField(editable=False, null=True)
thumbnail = ImageField(blank=True)
file = VideoField(width_field='width', height_field='height',
duration_field='duration')
format_set = GenericRelation(Format)
# tasks.py
from django.core.files import File
from video_encoding.backends import get_backend
from .models import Video
def create_thumbnail(video_pk):
video = Video.objects.get(pk=video_pk)
if not video.file:
# no video file attached
return
if video.thumbnail:
# thumbnail has already been generated
return
encoding_backend = get_backend()
thumbnail_path = encoding_backend.get_thumbnail(video.file.path)
filename = os.path.basename(self.url),
try:
with open(thumbnail_path, 'rb') as file_handler:
django_file = File(file_handler)
video.thumbnail.save(filename, django_file)
video.save()
finally:
os.unlink(thumbnail_path)
```
You should run this method in a separate process by using `django-rq`, `celery`
or similar) and enqueue execution from within a `post_save` signal.
```python
# signals.py
from django.db.models.signals import post_save
from django.dispatch import receiver
from django_rq import enqueue
from . import tasks
from .models import Video
@receiver(post_save, sender=Video)
def create_thumbnail(sender, instance, **kwargs):
enqueue(tasks.create_thumbnail, instance.pk)
```
### Signals
During the encoding multiple signals are emitted to report the progress.
You can register to the signals as described in the [Django documentation](https://docs.djangoproject.com/en/3.1/topics/signals/#connecting-to-signals-sent-by-specific-senders).
This simple example demonstrates, on how to update the "video model" once the convertion is finished.
```python
# apps.py
from django.apps import AppConfig
class MyAppConfig(AppConfig):
# ...
def ready(self) -> None:
from . import signals # register signals
# signals.py
from typing import Type
from django.dispatch import receiver
from video_encoding import signals
from myapp.models import Video
@receiver(signals.encoding_finished, sender=Video)
def mark_as_finished(sender: Type[Video], instance: Video) -> None:
"""
Mark video as "convertion has been finished".
"""
video.processed = True
video.save(update_fields=['processed'])
```
#### `signals.encoding_started`
This is sent before the encoding starts.
_Arguments_
`sender: Type[models.Model]`: Model which contains the `VideoField`.
`instance: models.Model)`: Instance of the model containing the `VideoField`.
#### `signals.encoding_finished`
Like `encoding_started()`, but sent after the file had been converted into all formats.
_Arguments_
`sender: Type[models.Model]`: Model which contains the `VideoField`.
`instance: models.Model)`: Instance of the model containing the `VideoField`.
#### `signals.format_started`
This is sent before the video is converted to one of the configured formats.
_Arguments_
`sender: Type[models.Model]`: Model which contains the `VideoField`.
`instance: models.Model)`: Instance of the model containing the `VideoField`.
`format: Format`: The format instance, which will reference the encoded video file.
#### `signals.format_finished`
Like `format_finished`, but sent after the video encoding process and includes whether the encoding was succesful or not.
_Arguments_
`sender: Type[models.Model]`: Model which contains the `VideoField`.
`instance: models.Model)`: Instance of the model containing the `VideoField`.
`format: Format`: The format instance, which will reference the encoded video file.
`result: ConversionResult`: Instance of `video_encoding.signals.ConversionResult` and indicates whether the convertion `FAILED`, `SUCCEEDED` or was `SKIPPED`.
## Configuration
**VIDEO_ENCODING_THREADS** (default: `1`)
Defines how many threads should be used for encoding. This may not be supported
by every backend.
**VIDEO_ENCODING_BACKEND** (default: `'video_encoding.backends.ffmpeg.FFmpegBackend'`)
Choose the backend for encoding. `django-video-encoding` only supports `ffmpeg`,
but you can implement your own backend. Feel free to pulish your plugin and
submit a pull request.
**VIDEO_ENCODING_BACKEND_PARAMS** (default: `{}`)
If your backend requires some special configuration, you can specify them here
as `dict`.
**VIDEO_ENCODING_FORMATS** (for defaults see `video_encoding/config.py`)
This dictionary defines all required encodings and has some resonable defaults.
If you want to customize the formats, you have to specify `name`,
`extension` and `params` for each format. For example
```python
VIDEO_ENCODING_FORMATS = {
'FFmpeg': [
{
'name': 'webm_sd',
'extension': 'webm',
'params': [
'-b:v', '1000k', '-maxrate', '1000k', '-bufsize', '2000k',
'-codec:v', 'libvpx', '-r', '30',
'-vf', 'scale=-1:480', '-qmin', '10', '-qmax', '42',
'-codec:a', 'libvorbis', '-b:a', '128k', '-f', 'webm',
],
},
]
```
## Encoding Backends
### video_encoding.backends.ffmpeg.FFmpegBackend (default)
Backend for using `ffmpeg` and `ffprobe` to convert your videos.
#### Options
**VIDEO_ENCODING_FFMPEG_PATH**
Path to `ffmpeg`. If no path is provided, the backend uses `which` to
locate it.
**VIDEO_ENCODING_FFPROBE_PATH**
Path to `ffprobe`. If no path is provided, the backend uses `which` to
locate it.
### Custom Backend
You can implement a custom encoding backend. Create a new class which inherits from
[`video_encoding.backends.base.BaseEncodingBackend`](video_encoding/backends/base.py).
You must set the property `name` and implement the methods `encode`, `get_media_info`
and `get_thumbnail`. For further details see the reference implementation:
[`video_encoding.backends.ffmpeg.FFmpegBackend`](video_encoding/backends/ffmpeg.py).
If you want to open source your backend, follow these steps.
1. create a packages named django-video-encoding-BACKENDNAME
2. publish your package to [pypi]
3. Submit a pull requests with the following changes:
* add the package to `extra_requires`
* provide reasonable defaults for `VIDEO_ENCODING_FORMATS`
[pypi]: https://pypi.python.org/pypi
## Development
This project uses [poetry](https://poetry.eustace.io/) for packaging and
managing all dependencies and [pre-commit](https://pre-commit.com/) to run
[flake8](http://flake8.pycqa.org/), [isort](https://pycqa.github.io/isort/),
[mypy](http://mypy-lang.org/) and [black](https://github.com/python/black).
Clone this repository and run
```bash
poetry install
poetry run pre-commit install
```
to create a virtual enviroment containing all dependencies.
Afterwards, You can run the test suite using
```bash
poetry run pytest
```
This repository follows the [Conventional Commits](https://www.conventionalcommits.org/)
style.
### Cookiecutter template
This project was created using [cruft](https://github.com/cruft/cruft) and the
[cookiecutter-pyproject](https://github.com/escaped/cookiecutter-pypackage) template.
In order to update this repository to the latest template version run
```sh
cruft update
```
in the root of this repository.