This project aims to create a song book for storing, managing and viewing songs. The songs are loaded once and then all the filtering/searching happens on the client, which enables it to be used even in low-internet environment. It can also automatically generate PDFs of the selected categories. Songs use Markdown with custom extensions for chords

• Use markdown to add songs
• Load-once site with all songs available
• Categorize songs into different Categories
• Generate PDFs of the selected categories/songs automatically
• Host multiple site (based on hostname) with only one instance

• Override any setting you want in chords/settings/production.py
  • Set ALLOWED_HOSTS, CSRF_TRUSTED_ORIGINS to actual domain you want the site to exist on
  • Generate SECRET_KEY unique for this site (https://docs.djangoproject.com/en/dev/ref/settings/#std:setting-SECRET_KEY)
  • Override both CACHES and DATABASES to point to your Redis and PostgreSQL (or other DB engine) respectively
  • Set TENANT_HOSTNAME to the hostname that the site should use
• Setup gunicorn or any other WSGI server
• Setup Worker
  • poetry run python manage.py run_huey --worker-type process
  • Responsible for async PDF generation
• Setup NGINX or any other reverse proxy to expose the website

• Python 3.9+
• gettext
  • Used for compiling locales
• Redis
  • Used as both cache and messaging queue for PDF generation

First clone the repository from GitHub and switch to the new directory:

git clone https://github.com/pehala/song-book.git
cd song-book

Install pipenv and dependencies

python -m pip install poetry
poetry install --with dev

Then simply initialize the website:

make init

You can now run the development server:

make run

Song book can generate PDF for entire categories automatically when changed or on demand for any number of songs. Scheduling is done via Huey and generation itself uses Weasyprint.

For enabling PDF generation for local development without having a separate worker, I recommend adding this line to settings.py:

HUEY = {"immediate": True}

For production, using separate worker is recommended as it does not block the main thread and subsequent request. You can configure it using Redis like this:

pool = ConnectionPool(host="localhost", port=6379, max_connections=20, db=2)
HUEY = RedisHuey("default", connection_pool=pool)

You can run worker through run_huey manage command

make worker

1. poetry install throws

   ERROR: Couldn't install package: rcssmin
   Package installation failed...
   

   Install python3-dev for Debian-based distro or python3-devel for RHEL-based distribution