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An audiobook library cleanup and management tool built with Python and Django. Leveraging m4b-merge for audiobook standardization and editing. Ideal for enhancing audiobook library management.

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Bragibooks

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An audiobook library cleanup & management app, written as a frontend for web use of m4b-merge.

πŸ“ Table of Contents

🧐 About

Bragi - (god of poetry in Norse mythology): Bragibooks provides a minimal and straightforward webserver that you can run remotely or locally on your server. Since Bragibooks runs in a docker, you no longer need to install dependencies on whichever OS you are on. You can

Some basics of what Bragi does:

  • Merge multiple files
  • Convert mp3(s)
  • Cleanup existing data on an m4b file
  • More features on m4b-merge's help page

Screens

Folder/file selection ASIN input
file-selection asin-auto-search
Folder/file selection Post-proccess overview
asin-custom-search post-process

🏁 Getting Started

You can either install this project directly or run it prepackaged in Docker.

Prerequisites

Docker

  • All prerequisites are included in the image.

Direct (Gunicorn)

  • You'll need to install m4b-tool and it's dependants from the project's readme
  • Run pip install -r requirements.txt from this project's directory.

Installing

Docker

To run Bragibooks as a container, you need to pass some paramaters in the run command:

Parameter Function
-v /path/to/input:/input Input folder
-v /path/to/output:/output Output folder
-v /appdata/bragibooks/config:/config Persistent config storage
-p 8000:8000/tcp Port for your browser to use
-e LOG_LEVEL=WARNING Choose any logging level
-e DEBUG=False Turn django debug on or off (default False)
-e UID=99 User ID to run the container as (default 99)
-e GID=100 Group ID to run the container as (default 100)
-e CELERY_WORKERS=1 The number or celery workers for processing books (default 1)
-e CSRF_TRUSTED_ORIGINS=https://bragibooks.mydomain.com Domains to trust if bragibooks is hosted behind a reverse proxy.

Which all together should look like:

docker run --rm -d --name bragibooks -v /path/to/input:/input -v /path/to/output:/output -v /appdata/bragibooks/config:/config -p 8000:8000/tcp -e LOG_LEVEL=WARNING ghcr.io/djdembeck/bragibooks:main

Docker Compose

version: '3'

services:
  bragi:
    image: ghcr.io/djdembeck/bragibooks:main
    container_name: bragibooks
    environment:
      - CSRF_TRUSTED_ORIGINS=https://bragibooks.mydomain.com
      - LOG_LEVEL=INFO
      - DEBUG=False
      - UID=1000
      - GID=1000
    volumes:
      - path/to/config:/config
      - path/to/input:/input
      - path/to/output/output:/output
      - path/to/done:/done
    ports:
      - 8000:8000
    restart: unless-stopped

Direct Build (Gunicorn)

  • Copy static assets to project folder:
    python manage.py collectstatic
    
  • Create the database:
    python manage.py migrate
    
  • Run the celery worker for processing books:
    celery -A bragibooks_proj worker \
    --loglevel=info \ 
    --concurrency 1 \
    -E
    
  • Run the web server:
    gunicorn bragibooks_proj.wsgi \
    --bind 0.0.0.0:8000 \
    --timeout 1200 \
    --worker-tmp-dir /dev/shm \
    --workers=2 \
    --threads=4 \
    --worker-class=gthread \
    --reload \
    --enable-stdio-inheritance
    

🎈 Usage

The Bragibooks process is a linear, 3 step process:

  1. Select input - Use the file multi-select box to choose which books to process this session, and click next.
  2. Submit ASINs - Bragi will auto search for the audiobook data on Audible.com (US only). If the data found is incorrect you can do a custom search to find the correct title and then submit for processing.
  3. Wait for books to finish processing. This can take anywhere from 10 seconds to a few hours, depending on the number and type of files submitted. This will be done in the background.
  4. Books page - Page where you can see the data assigned to each book after it has finished processing. You can also check the status of the books still being processed.

⛏️ Built Using

✍️ Authors

@djdembeck - Idea & Initial work

Contributors ✨

Thanks goes to these wonderful people (emoji key):

Koby Huckabee
Koby Huckabee

πŸ’» πŸ€” πŸ“–
Andreas
Andreas

πŸ”§

This project follows the all-contributors specification. Contributions of any kind welcome!

About

An audiobook library cleanup and management tool built with Python and Django. Leveraging m4b-merge for audiobook standardization and editing. Ideal for enhancing audiobook library management.

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