docker-compose.yml.jinja

version: "3"

# Date created: {{ date }}
# Species: {{ species.replace("_", " ").upper() }}

volumes:
  # Volume to store conda environments created by Snakemake. This volume can be
  # shared across workflows so a conda env doesn't need to be recreated
  # if it has been used in a previous workflow.
  conda-envs:
    external: true

    # For testing on a PC with a small root partition, create a named bind mount
    # with the following command first.
    #
    #   mkdir /media/user/data/conda-envs
    #   docker volume create --opt type=none --opt o=bind --opt device=/media/user/data/conda-envs conda-envs
    

  # Volume to store reference genome workflows and data
  # To make it easy to access the files on the host, it is best to create a 
  # named bind mount first something like the command below.
  # You can replace device= with whatever location you want the data saved.
  #
  #   mkdir /media/user/data/genomes
  #   docker volume create --opt type=none --opt o=bind --opt device=/media/user/data/genomes genomes
  genomes:
    external: true


services:
  # The service to run the workflow
  workflow:
    build:
      context: .
      dockerfile: Dockerfile
      target: workflow
      args:
        WORKFLOW_PATH: /mnt/genomes/{{ species }}
    image: {{ species }}:{{ date }}
    command: ["snakemake","--use-conda","-c2","-p"]
    working_dir: "/mnt/genomes/{{ species }}"
    volumes:
      # Path to store conda environments, created externally
      - conda-envs:/conda-envs
      
      # External genomes volumne
      - genomes:/mnt/genomes

      - "./config:/mnt/genomes/{{ species }}/config"
      - "./logs:/mnt/genomes/{{ species }}/logs"
      - "./resources:/mnt/genomes/{{ species }}/resources"
      - "./workflow:/mnt/genomes/{{ species }}/workflow"