| Name | wandarr JSON |
| Version |
1.1.1
JSON |
| download |
| home_page | None |
| Summary | A ffmpeg transcoding workflow engine with clustered host support |
| upload_time | 2024-06-28 18:52:47 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | None |
| keywords |
cuda
encode
ffmpeg
qsv
transcode
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
## wandarr - the Distributed Transcoding Toolkit
This CLI tool is a transcoding workflow manager that makes transcoding video files easier and optionally across multiple
machines in parallel, using ffmpeg. It is the successor to pytranscoder and is based on the fundamental codebase of that project.
## NOTE that ffmpeg version 7.0 has some wonky status output that confuses wandarr. For the time being I recommend setting your wandarr.yml "rich=" setting to "off" -- ie rich=off
#### Features:
* Sequential or concurrent transcoding.
* Concurrent mode allows you to make maximum use of your
nVidia CUDA-enabled graphics card, Intel accelerated video (QSV), or Apple VideoToolkit.
* Preserves all streams but allows for filtering by audio and subtitle language.
* Configurable transcoding templates
* Transcode from a list of files (queue) or all on the command line
* Clustering allows use of other machines.
* On-the-fly compression monitoring and optional early job termination if not compressing as expected.
#### Requirements
* Linux or MacOS, Windows.
* latest *ffmpeg* (3.4.3-2 or higher, lower versions may still work)
* nVidia graphics card with latest nVidia CUDA drivers (_optional_)
* Intel CPU with QSV enabled (_optional_)
* MacOS VideoToolkit (_optional_)
* Python 3 (3.10 or higher)
### Installation
```bash
pip3 install wandarr
```
#### Upgrading
Whatever method above for installing works for you, just use the --upgrade option to update, ie:
```bash
pip3 install --upgrade wandarr
```
### Support
Please log issues or questions via the github home page for now.
### Configuration
There is a supplied sample *wandarr.yml* config file, or you can download it from the git home. This can be customized all you like, however be
sure to preserve the YAML formatting. Either specify this file on the commandline with the *-y* option
or copy it to your home directory as *.wandarr.yml* (default)
In short, you will define your machine(s) used for transcoding, the transcoding capabilities of those machines, and template to tie it all together.
There are 4 sections in the file:
#### Section 1 - config - Global configuration information
Sample
```yaml
config:
ffmpeg: '/opt/homebrew/bin/ffmpeg' # path to ffmpeg for this config
rich: yes # use rich text library for nicer output
```
#### Section 2 - host definition(s)
The *cluster:* section is where you define all the machines in your network you intend to use for asynchronous transcoding jobs.
This is optional - you need only define a single machine if that's all you are using.
Single-host sample - you can just start out like this:
```yaml
cluster:
mbp:
os: macos
type: local # the host you will run wandarr on.
working_dir: /tmp # best if this is an SSD
ffmpeg: '/opt/homebrew/bin/ffmpeg'
engines:
- vt
status: enabled
```
Multi-host Sample:
All fields in these samples are required for their respective host type and there are no optional ones.
This sample cluster defines 3 hosts that will participate in a transcode job. The video files reside on a NAS.
The first host, "homeserver", is an Ubuntu machine with an NFS mount to the NAS (type=mounted). It has both a QSV-enabled
Intel CPU and a discrete nVidia graphics card with CUDA support.
The second host, "winpc", is a Windows 11 machine running wandarr as an agent (type=agent). It also has an nVidia card
installed but not QSV-enabled.
The final host, "mbp", is a MacBook Pro (M1 Pro) where this process is running from (type=local). It will also handle
transcoding using the Apple VideoToolbox hardware acceleration feature.
```yaml
cluster:
# sample linux machine with an Intel i5 CPU/iGPU and nVidia graphics card
homeserver:
os: linux
type: mounted # files to transcode are available via a network mount
working_dir: /tmp # dir to use for temp files during transcode, best to place on an SSD
ip: 192.168.2.64 # ip or hostname of the machine
user: marshall # your ssh user login name. You must be able to ssh into this host w/o a password
ffmpeg: '/usr/bin/ffmpeg' # location of ffmpeg on the host
engines: # list one of more of the video "engines" defined in the next section. This identifies
# the video handling capabilities of the host. In this sample, this host can do QSV and CUDA
- qsv
- cuda
- cpu
path-substitutions: # for mounted types only - maps the local drive path to remote mounted one (more later)
- '/Volumes/USB11/ /mnt/media/'
- '/Volumes/media/ /mnt/media/'
- '/mnt/downloads/ /mnt/downloads/'
status: enabled # enabled or disabled
# sample Windows 11 machine with an nVidia graphics card
winpc:
os: win10
type: agent # this host is running wandarr in agent mode (more later). No mounts or ssh used.
ip: 192.168.2.61
ffmpeg: 'c:\ffmpeg\bin\ffmpeg.exe'
engines:
- cuda
- cpu
working_dir: 'c:/temp'
path-substitutions:
- '/Volumes/media m:'
- '/Volumes/USB11/media m:'
- '/mnt/merger/media/video/ n:video\'
- '/mnt/downloads/ z:\'
status: enabled
# sample MacBook Pro (M1 Pro silicon) using VideoToolkit hw acceleration
mbp:
os: macos
type: local # the host you will run wandarr on. Not required if you will not transcode on this machine
working_dir: /tmp
ffmpeg: '/opt/homebrew/bin/ffmpeg'
engines:
- vt
- cpu
status: enabled
```
Host Types:
- local
- The machine running wandarr. It's either your only single transcoding machine, or a member of a cluster. If you have multiple machines and will not use your "local" machine to also transcode them you need no local host defined.
- mounted
- This machine can access the media via a network mount. Besides local, this is the next fasted option as the files can be immediately accessed. You must have an ssh password-less login to this host. You can use the ssh-copy_id tool to establish trust between machines.
- streaming
- This machine has no network mount, so copy the file to it over first, transcode, then copy the resulting file back. This still requires ssh access like mounted.
- agent
- This machine is running as a remote wandarr agent and requires no ssh or mounted filesystem. The tool must be installed there and started with ```wandarr --agent```. It will use port 9567 to communicate with wandarr on your local machine to transfer files and perform transcoding. Note that this is insecure - this should only be used on your private network where you have control.
#### Section 3 - engines
This section defines the video transcoding capabilities of your host(s). The labels and values can be anything you like.
Each section under *engines* defines a hardware capability. Here you see 3 - vt, qsv, and cuda representing the 3 types of hardware transcoding available to the sample hosts.
Each section under *quality* defines as many named configurations as you need. In the sample here you see low, medium, high, and copy.
These are ffmpeg options that control how your video is transformed. These are *only* the video options as they are the ones that can vary between hardware.
While these are usable samples, you may alter then to suit your needs or add many more.
Also keep in mind you do not need to use hardware acceleration, but it does make things go faster.
Sample:
```yaml
engines:
vt: # videotoolkit hardware acceleration
quality:
low: "-c:v hevc_videotoolbox -qp 25 -b:v 5000K -f matroska"
medium: "-c:v hevc_videotoolbox -preset medium -qp 23 -b:v 6000K -f matroska -max_muxing_queue_size 1024"
high: "-c:v hevc_videotoolbox -preset medium -qp 21 -b:v 8000K -f matroska -max_muxing_queue_size 1024"
qsv: # qsv hardware acceleration
quality:
medium: "-c:v hevc_qsv -preset medium -qp 23 -b:v 7000K -f matroska -max_muxing_queue_size 1024"
high: "-c:v hevc_qsv -preset medium -qp 21 -b:v 7000K -f matroska -max_muxing_queue_size 1024"
cuda: # nvidia hardware acceleration
quality:
high: "-c:v hevc_nvenc -cq:v 21 -rc vbr -rc-lookahead 20 -bufsize 3M -b:v 6M -profile:v main -maxrate:v 6M -preset medium -b_ref_mode 0 -f matroska -max_muxing_queue_size 1024"
medium: "-c:v hevc_nvenc -cq:v 23 -rc vbr -rc-lookahead 20 -bufsize 3M -b:v 7M -profile:v main -maxrate:v 7M -preset medium -b_ref_mode 0 -f matroska -max_muxing_queue_size 1024"
cpu: # transcode using only the CPU (ick!)
quality:
high-hevc: "-c:v hevc -cq:v 21 -rc vbr -rc-lookahead 20 -bufsize 3M -b:v 6M -profile:v main -maxrate:v 6M -preset medium -b_ref_mode 0 -f matroska -max_muxing_queue_size 1024"
medium-hevc: "-c:v hevc -cq:v 23 -rc vbr -rc-lookahead 20 -bufsize 3M -b:v 7M -profile:v main -maxrate:v 7M -preset medium -b_ref_mode 0 -f matroska -max_muxing_queue_size 1024"
high-264: "-c:v x264 -cq:v 21 -rc vbr -rc-lookahead 20 -bufsize 3M -b:v 6M -profile:v main -maxrate:v 6M -preset medium -b_ref_mode 0 -f matroska -max_muxing_queue_size 1024"
medium-264: "-c:v x264 -cq:v 23 -rc vbr -rc-lookahead 20 -bufsize 3M -b:v 7M -profile:v main -maxrate:v 7M -preset medium -b_ref_mode 0 -f matroska -max_muxing_queue_size 1024"
copy: "-c:v copy -f matroska"
```
#### Section 4 - templates
Templates define overall how to handle a video. As with engine definitions above, the *cli* section here defines the ffmpeg options for handling audio and subtitles.
In the samples below you will see examples of video-only transcoding (preserve audio as-is), full audio and video transcoding,
and special case template used just to scrub out unwanted languages.
Note the *video-quality* element. This is used to complete the linkage from template to engine to hosts.
Sample:
```yaml
templates:
vid-only: # name of the template - you will use this on the commandline
cli: # section for non-video ffmpeg commandline options
audio: "-c:a copy"
subtitles: "-c:s copy"
video-quality: medium # match this template to the "medium" quality defined in *engines*
audio-lang: eng # preserve only English audio tracks (opt).
subtitle-lang: eng # preserve only English subtitle tracks (opt).
threshold: 15 # minimum required compression is %15, or terminate transcode (opt)
threshold_check: 20 # start checking for minimum threshold at 20% (opt)
extension: '.mkv' # use this file extension
vid-only-anime:
cli:
audio: "-c:a copy"
subtitles: "-c:s copy"
video-quality: medium
audio-lang: "eng jpn" # preserve English and Japanese audio
subtitle-lang: eng
threshold: 15
threshold_check: 20
extension: '.mkv'
best-medium:
cli:
audio: "-c:a ac3 -b:a 768k"
subtitles: "-c:s copy"
video-quality: medium
audio-lang: eng
subtitle-lang: eng
threshold: 15
threshold_check: 20
extension: '.mkv'
best-medium-anime:
cli:
audio: "-c:a ac3 -b:a 768k"
subtitles: "-c:s copy"
video-quality: medium
audio-lang: "eng jpn"
subtitle-lang: eng
threshold: 15
threshold_check: 30
extension: '.mkv'
scrub: # this template used only to scrub out undesired audio and subtitle tracks. no transcoding done.
cli:
audio: "-c:a copy"
subtitles: "-c:s copy"
video-quality: copy
audio-lang: eng
subtitle-lang: eng
extension: '.mkv'
scrub-anime: # this template used only to scrub out undesired audio and subtitle tracks. no transcoding done.
cli:
audio: "-c:a copy"
subtitles: "-c:s copy"
video-quality: copy
audio-lang: "eng jpn"
subtitle-lang: eng
extension: '.mkv'
```
### Putting it all together
Here's how to read the samples above in their entirety.
In the *vid-only* template above, we defined the ffmpeg options to handle audio and subtitles. In this case, we're just copying with no changes.
Now we need to know the ffmpeg options for handling video.
The video-quality value of *medium* matches all *medium* definitions in engines. This tells wandarr that any hosts that match an
engine definition containing a *medium* will be a eligible match for this template. So for medium we have told wandarr how to transcode
video for video toolbox, intel qsv, and nvidia cuda. Whichever hosts are associated to those engines may be selected to do the job.
So, a template relates to an engine quality. A quality defines ffmpeg options for all supported hardware to accomplish the same result.
A host relates to one or more engines. This is how a host is selected for transcoding, and how to do it.
You can be as basic or complex as you need. The typical user only needs 2 or 3 templates.
### Running
**The default behavior is to remove the original video file after encoding** and replace it with the new version.
If you want to keep the source *be sure to use the -k* parameter. The work file will be placed in the same
folder as the source with the same name and a .tmp extension while being encoded.
```text
usage: main.py [-h] [-v] [-i] [-k] [--dry-run] [-y CONFIGFILE_NAME] [--agent] [-t TEMPLATE] [--hosts HOST_OVERRIDE] [--from-file FROM_FILE] [filename ...]
wandarr (ver 1.0.0)
positional arguments:
filename
options:
-h, --help show this help message and exit
-v verbose mode
-i show technical info on files and stop
-k keep source (do not replace)
--dry-run Test run, show steps but don't change anything
-y CONFIGFILE_NAME Full path to configuration file. Default is ~/.wandarr.yml
--agent Start in agent mode on a host and listen for transcode requests from other wandarr.
-t TEMPLATE Template name to use for transcode jobs
--hosts HOST_OVERRIDE
Only run transcode on given host(s), comma-separated
--from-file FROM_FILE
Filename that contains list of full paths of files to transcode
```
#### Examples:
To get help and version number:
```bash
wandarr -h
```
Show me the technical goods on some files:
```bash
wandarr -i *.mkv
```
To transcode 2 files using a specific template:
```bash
wandarr -t my_fave_x264 /tmp/video1.mp4 /tmp/video2.mp4
```
To auto transcode everything listed in a specific file:
```bash
wandarr -t tv --from-file /tmp/queue.txt
```
To do a test run without transcoding:
```bash
wandarr -t movie-high --dry-run atestvideo.mp4
```
To use a specific yml file:
```bash
wandarr -y /home/me/etc/quickstart.yml -t tv *.mp4
```
To transcode on a specific host only:
```bash
wandarr -t tv --host workstation *.mp4
```
Raw data
{
"_id": null,
"home_page": null,
"name": "wandarr",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.10",
"maintainer_email": null,
"keywords": "cuda, encode, ffmpeg, qsv, transcode",
"author": null,
"author_email": "Marshall L Smith Jr <marshallsmithjr@gmail.com>",
"download_url": "https://files.pythonhosted.org/packages/c2/b3/a4b6a20aacfb58b8638516ebd528877f96f289e1a659710419744d48277b/wandarr-1.1.1.tar.gz",
"platform": null,
"description": "## wandarr - the Distributed Transcoding Toolkit\nThis CLI tool is a transcoding workflow manager that makes transcoding video files easier and optionally across multiple\nmachines in parallel, using ffmpeg. It is the successor to pytranscoder and is based on the fundamental codebase of that project.\n\n## NOTE that ffmpeg version 7.0 has some wonky status output that confuses wandarr. For the time being I recommend setting your wandarr.yml \"rich=\" setting to \"off\" -- ie rich=off\n\n#### Features:\n* Sequential or concurrent transcoding. \n* Concurrent mode allows you to make maximum use of your \nnVidia CUDA-enabled graphics card, Intel accelerated video (QSV), or Apple VideoToolkit.\n* Preserves all streams but allows for filtering by audio and subtitle language.\n* Configurable transcoding templates\n* Transcode from a list of files (queue) or all on the command line\n* Clustering allows use of other machines.\n* On-the-fly compression monitoring and optional early job termination if not compressing as expected.\n\n#### Requirements\n\n* Linux or MacOS, Windows. \n* latest *ffmpeg* (3.4.3-2 or higher, lower versions may still work)\n* nVidia graphics card with latest nVidia CUDA drivers (_optional_)\n* Intel CPU with QSV enabled (_optional_)\n* MacOS VideoToolkit (_optional_)\n* Python 3 (3.10 or higher)\n\n### Installation\n```bash\npip3 install wandarr\n```\n\n#### Upgrading\n\nWhatever method above for installing works for you, just use the --upgrade option to update, ie:\n```bash\npip3 install --upgrade wandarr\n```\n\n### Support\nPlease log issues or questions via the github home page for now.\n\n\n### Configuration\n\nThere is a supplied sample *wandarr.yml* config file, or you can download it from the git home. This can be customized all you like, however be\nsure to preserve the YAML formatting. Either specify this file on the commandline with the *-y* option\nor copy it to your home directory as *.wandarr.yml* (default)\n\nIn short, you will define your machine(s) used for transcoding, the transcoding capabilities of those machines, and template to tie it all together.\n\nThere are 4 sections in the file:\n\n#### Section 1 - config - Global configuration information\n\nSample\n```yaml\nconfig:\n ffmpeg: '/opt/homebrew/bin/ffmpeg' # path to ffmpeg for this config\n rich: yes # use rich text library for nicer output\n```\n\n#### Section 2 - host definition(s)\n\nThe *cluster:* section is where you define all the machines in your network you intend to use for asynchronous transcoding jobs.\nThis is optional - you need only define a single machine if that's all you are using.\n\nSingle-host sample - you can just start out like this:\n```yaml\ncluster:\n mbp:\n os: macos\n type: local # the host you will run wandarr on.\n working_dir: /tmp # best if this is an SSD\n ffmpeg: '/opt/homebrew/bin/ffmpeg'\n engines:\n - vt\n status: enabled\n```\n\nMulti-host Sample:\n\nAll fields in these samples are required for their respective host type and there are no optional ones.\nThis sample cluster defines 3 hosts that will participate in a transcode job. The video files reside on a NAS.\n\nThe first host, \"homeserver\", is an Ubuntu machine with an NFS mount to the NAS (type=mounted). It has both a QSV-enabled\nIntel CPU and a discrete nVidia graphics card with CUDA support.\n\nThe second host, \"winpc\", is a Windows 11 machine running wandarr as an agent (type=agent). It also has an nVidia card\ninstalled but not QSV-enabled.\n\nThe final host, \"mbp\", is a MacBook Pro (M1 Pro) where this process is running from (type=local). It will also handle\ntranscoding using the Apple VideoToolbox hardware acceleration feature.\n\n```yaml\ncluster:\n # sample linux machine with an Intel i5 CPU/iGPU and nVidia graphics card\n homeserver:\n os: linux\n type: mounted # files to transcode are available via a network mount\n working_dir: /tmp # dir to use for temp files during transcode, best to place on an SSD\n ip: 192.168.2.64 # ip or hostname of the machine\n user: marshall # your ssh user login name. You must be able to ssh into this host w/o a password\n ffmpeg: '/usr/bin/ffmpeg' # location of ffmpeg on the host\n engines: # list one of more of the video \"engines\" defined in the next section. This identifies\n # the video handling capabilities of the host. In this sample, this host can do QSV and CUDA\n - qsv\n - cuda\n - cpu\n path-substitutions: # for mounted types only - maps the local drive path to remote mounted one (more later)\n - '/Volumes/USB11/ /mnt/media/'\n - '/Volumes/media/ /mnt/media/'\n - '/mnt/downloads/ /mnt/downloads/'\n status: enabled # enabled or disabled\n\n # sample Windows 11 machine with an nVidia graphics card\n winpc:\n os: win10\n type: agent # this host is running wandarr in agent mode (more later). No mounts or ssh used.\n ip: 192.168.2.61\n ffmpeg: 'c:\\ffmpeg\\bin\\ffmpeg.exe'\n engines:\n - cuda\n - cpu\n working_dir: 'c:/temp'\n path-substitutions:\n - '/Volumes/media m:'\n - '/Volumes/USB11/media m:'\n - '/mnt/merger/media/video/ n:video\\'\n - '/mnt/downloads/ z:\\'\n status: enabled\n\n # sample MacBook Pro (M1 Pro silicon) using VideoToolkit hw acceleration\n mbp:\n os: macos\n type: local # the host you will run wandarr on. Not required if you will not transcode on this machine\n working_dir: /tmp\n ffmpeg: '/opt/homebrew/bin/ffmpeg'\n engines:\n - vt\n - cpu\n status: enabled\n```\n\nHost Types:\n\n- local\n - The machine running wandarr. It's either your only single transcoding machine, or a member of a cluster. If you have multiple machines and will not use your \"local\" machine to also transcode them you need no local host defined.\n- mounted\n - This machine can access the media via a network mount. Besides local, this is the next fasted option as the files can be immediately accessed. You must have an ssh password-less login to this host. You can use the ssh-copy_id tool to establish trust between machines.\n- streaming\n - This machine has no network mount, so copy the file to it over first, transcode, then copy the resulting file back. This still requires ssh access like mounted.\n- agent\n - This machine is running as a remote wandarr agent and requires no ssh or mounted filesystem. The tool must be installed there and started with ```wandarr --agent```. It will use port 9567 to communicate with wandarr on your local machine to transfer files and perform transcoding. Note that this is insecure - this should only be used on your private network where you have control.\n\n#### Section 3 - engines\nThis section defines the video transcoding capabilities of your host(s). The labels and values can be anything you like.\nEach section under *engines* defines a hardware capability. Here you see 3 - vt, qsv, and cuda representing the 3 types of hardware transcoding available to the sample hosts.\nEach section under *quality* defines as many named configurations as you need. In the sample here you see low, medium, high, and copy.\nThese are ffmpeg options that control how your video is transformed. These are *only* the video options as they are the ones that can vary between hardware.\nWhile these are usable samples, you may alter then to suit your needs or add many more.\nAlso keep in mind you do not need to use hardware acceleration, but it does make things go faster.\n\nSample:\n```yaml\nengines:\n vt: # videotoolkit hardware acceleration\n quality:\n low: \"-c:v hevc_videotoolbox -qp 25 -b:v 5000K -f matroska\"\n medium: \"-c:v hevc_videotoolbox -preset medium -qp 23 -b:v 6000K -f matroska -max_muxing_queue_size 1024\"\n high: \"-c:v hevc_videotoolbox -preset medium -qp 21 -b:v 8000K -f matroska -max_muxing_queue_size 1024\"\n\n qsv: # qsv hardware acceleration\n quality:\n medium: \"-c:v hevc_qsv -preset medium -qp 23 -b:v 7000K -f matroska -max_muxing_queue_size 1024\"\n high: \"-c:v hevc_qsv -preset medium -qp 21 -b:v 7000K -f matroska -max_muxing_queue_size 1024\"\n\n cuda: # nvidia hardware acceleration\n quality:\n high: \"-c:v hevc_nvenc -cq:v 21 -rc vbr -rc-lookahead 20 -bufsize 3M -b:v 6M -profile:v main -maxrate:v 6M -preset medium -b_ref_mode 0 -f matroska -max_muxing_queue_size 1024\"\n medium: \"-c:v hevc_nvenc -cq:v 23 -rc vbr -rc-lookahead 20 -bufsize 3M -b:v 7M -profile:v main -maxrate:v 7M -preset medium -b_ref_mode 0 -f matroska -max_muxing_queue_size 1024\"\n\n cpu: # transcode using only the CPU (ick!)\n quality:\n high-hevc: \"-c:v hevc -cq:v 21 -rc vbr -rc-lookahead 20 -bufsize 3M -b:v 6M -profile:v main -maxrate:v 6M -preset medium -b_ref_mode 0 -f matroska -max_muxing_queue_size 1024\"\n medium-hevc: \"-c:v hevc -cq:v 23 -rc vbr -rc-lookahead 20 -bufsize 3M -b:v 7M -profile:v main -maxrate:v 7M -preset medium -b_ref_mode 0 -f matroska -max_muxing_queue_size 1024\"\n high-264: \"-c:v x264 -cq:v 21 -rc vbr -rc-lookahead 20 -bufsize 3M -b:v 6M -profile:v main -maxrate:v 6M -preset medium -b_ref_mode 0 -f matroska -max_muxing_queue_size 1024\"\n medium-264: \"-c:v x264 -cq:v 23 -rc vbr -rc-lookahead 20 -bufsize 3M -b:v 7M -profile:v main -maxrate:v 7M -preset medium -b_ref_mode 0 -f matroska -max_muxing_queue_size 1024\"\n copy: \"-c:v copy -f matroska\"\n```\n\n#### Section 4 - templates\nTemplates define overall how to handle a video. As with engine definitions above, the *cli* section here defines the ffmpeg options for handling audio and subtitles.\n\nIn the samples below you will see examples of video-only transcoding (preserve audio as-is), full audio and video transcoding, \nand special case template used just to scrub out unwanted languages.\n\nNote the *video-quality* element. This is used to complete the linkage from template to engine to hosts.\n\nSample:\n```yaml\ntemplates:\n vid-only: # name of the template - you will use this on the commandline\n cli: # section for non-video ffmpeg commandline options\n audio: \"-c:a copy\"\n subtitles: \"-c:s copy\"\n video-quality: medium # match this template to the \"medium\" quality defined in *engines*\n audio-lang: eng # preserve only English audio tracks (opt).\n subtitle-lang: eng # preserve only English subtitle tracks (opt).\n threshold: 15 # minimum required compression is %15, or terminate transcode (opt)\n threshold_check: 20 # start checking for minimum threshold at 20% (opt)\n extension: '.mkv' # use this file extension\n\n vid-only-anime:\n cli:\n audio: \"-c:a copy\"\n subtitles: \"-c:s copy\"\n video-quality: medium\n audio-lang: \"eng jpn\" # preserve English and Japanese audio\n subtitle-lang: eng\n threshold: 15\n threshold_check: 20\n extension: '.mkv'\n\n best-medium:\n cli:\n audio: \"-c:a ac3 -b:a 768k\"\n subtitles: \"-c:s copy\"\n video-quality: medium\n audio-lang: eng\n subtitle-lang: eng\n threshold: 15\n threshold_check: 20\n extension: '.mkv'\n\n best-medium-anime:\n cli:\n audio: \"-c:a ac3 -b:a 768k\"\n subtitles: \"-c:s copy\"\n video-quality: medium\n audio-lang: \"eng jpn\"\n subtitle-lang: eng\n threshold: 15\n threshold_check: 30\n extension: '.mkv'\n\n scrub: # this template used only to scrub out undesired audio and subtitle tracks. no transcoding done.\n cli:\n audio: \"-c:a copy\"\n subtitles: \"-c:s copy\"\n video-quality: copy\n audio-lang: eng\n subtitle-lang: eng\n extension: '.mkv'\n\n scrub-anime: # this template used only to scrub out undesired audio and subtitle tracks. no transcoding done.\n cli:\n audio: \"-c:a copy\"\n subtitles: \"-c:s copy\"\n video-quality: copy\n audio-lang: \"eng jpn\"\n subtitle-lang: eng\n extension: '.mkv'\n ```\n\n### Putting it all together\n\nHere's how to read the samples above in their entirety.\n\nIn the *vid-only* template above, we defined the ffmpeg options to handle audio and subtitles. In this case, we're just copying with no changes.\nNow we need to know the ffmpeg options for handling video.\nThe video-quality value of *medium* matches all *medium* definitions in engines. This tells wandarr that any hosts that match an\nengine definition containing a *medium* will be a eligible match for this template. So for medium we have told wandarr how to transcode\nvideo for video toolbox, intel qsv, and nvidia cuda. Whichever hosts are associated to those engines may be selected to do the job.\n\nSo, a template relates to an engine quality. A quality defines ffmpeg options for all supported hardware to accomplish the same result.\nA host relates to one or more engines. This is how a host is selected for transcoding, and how to do it.\n\nYou can be as basic or complex as you need. The typical user only needs 2 or 3 templates.\n\n### Running\n\n**The default behavior is to remove the original video file after encoding** and replace it with the new version.\nIf you want to keep the source *be sure to use the -k* parameter. The work file will be placed in the same\nfolder as the source with the same name and a .tmp extension while being encoded.\n\n```text\nusage: main.py [-h] [-v] [-i] [-k] [--dry-run] [-y CONFIGFILE_NAME] [--agent] [-t TEMPLATE] [--hosts HOST_OVERRIDE] [--from-file FROM_FILE] [filename ...]\n\nwandarr (ver 1.0.0)\n\npositional arguments:\n filename\n\noptions:\n -h, --help show this help message and exit\n -v verbose mode\n -i show technical info on files and stop\n -k keep source (do not replace)\n --dry-run Test run, show steps but don't change anything\n -y CONFIGFILE_NAME Full path to configuration file. Default is ~/.wandarr.yml\n --agent Start in agent mode on a host and listen for transcode requests from other wandarr.\n -t TEMPLATE Template name to use for transcode jobs\n --hosts HOST_OVERRIDE\n Only run transcode on given host(s), comma-separated\n --from-file FROM_FILE\n Filename that contains list of full paths of files to transcode\n```\n\n#### Examples:\n\nTo get help and version number:\n```bash\n wandarr -h\n```\n\nShow me the technical goods on some files:\n```bash\n wandarr -i *.mkv\n```\n\nTo transcode 2 files using a specific template:\n```bash\n wandarr -t my_fave_x264 /tmp/video1.mp4 /tmp/video2.mp4\n```\n\nTo auto transcode everything listed in a specific file:\n```bash\n wandarr -t tv --from-file /tmp/queue.txt\n```\nTo do a test run without transcoding:\n```bash\n wandarr -t movie-high --dry-run atestvideo.mp4\n```\n\nTo use a specific yml file:\n```bash\n wandarr -y /home/me/etc/quickstart.yml -t tv *.mp4\n```\n\nTo transcode on a specific host only:\n```bash\n wandarr -t tv --host workstation *.mp4\n```\n",
"bugtrack_url": null,
"license": null,
"summary": "A ffmpeg transcoding workflow engine with clustered host support",
"version": "1.1.1",
"project_urls": {
"Homepage": "https://github.com/mlsmithjr/wandarr"
},
"split_keywords": [
"cuda",
" encode",
" ffmpeg",
" qsv",
" transcode"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "fd54bac26e8ac92ea1b9df61be28a76846717a5b5de1a26d29bea5065ad62230",
"md5": "6f74fcc3b3b7228f0f5bf52bce3d745c",
"sha256": "978a97879768dfa408da839bfa89a0ae5c41536eda9d237ff3cf36e36dd22898"
},
"downloads": -1,
"filename": "wandarr-1.1.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "6f74fcc3b3b7228f0f5bf52bce3d745c",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.10",
"size": 46806,
"upload_time": "2024-06-28T18:52:45",
"upload_time_iso_8601": "2024-06-28T18:52:45.926753Z",
"url": "https://files.pythonhosted.org/packages/fd/54/bac26e8ac92ea1b9df61be28a76846717a5b5de1a26d29bea5065ad62230/wandarr-1.1.1-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "c2b3a4b6a20aacfb58b8638516ebd528877f96f289e1a659710419744d48277b",
"md5": "ecbbf39ffa18fb0c09a35ffd321a0226",
"sha256": "2bbdd89e675b240abd98dc8e4678db69b485c53856bdd9bf7f38da03d906a41f"
},
"downloads": -1,
"filename": "wandarr-1.1.1.tar.gz",
"has_sig": false,
"md5_digest": "ecbbf39ffa18fb0c09a35ffd321a0226",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.10",
"size": 463612,
"upload_time": "2024-06-28T18:52:47",
"upload_time_iso_8601": "2024-06-28T18:52:47.793085Z",
"url": "https://files.pythonhosted.org/packages/c2/b3/a4b6a20aacfb58b8638516ebd528877f96f289e1a659710419744d48277b/wandarr-1.1.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-06-28 18:52:47",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "mlsmithjr",
"github_project": "wandarr",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "wandarr"
}
