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volunteer-planner.org Docker

An easy setup for using the Volunteer-Planner in a development or test environment is to user Docker. The Docker configuration files are included in the git package of volunteer-planner.

Do not use this setup for production environments. The web container is not secure. If you want to use docker for production you have to exchange the webserver in the web container.

Project setup for development

1. Install docker

Follow the instructions relevant to your operating system.

2. Prepare the docker files

2.1 Prepare the DB

By default, the application will be using MySQL. If you prefer PostgreSQL, edit the Dockerfile and docker-compose.yml files, uncommenting the PostgreSQL related parts, and commenting out the MySQL related ones.

2.1 Initialize the DB container

Run docker-compose up db, and wait for the initialization to be over. You can now kill the container with CTRL-c.

2.3 Initalize the web container and run migrate management command to setup non-existing tables

$ docker-compose run --rm web migrate

2.4 Add a superuser

$ docker-compose run --entrypoint=python --rm web manage.py createsuperuser --username admin --email admin@localhost

You will be asked for password twice. Remember that password. (Sorry for the lengthy command line, but our work to make the Django app shut down properly removes it's TTY access when using the default entrypoint.)

3. Run the server

$ docker-compose up

Try opening http://localhost:8000/ in your browser. If you want to shutdown you can start the shutdown of the containers with CTRL-c.

4. Switch database

4.1 Stop all running services

To stop all eventually running servics, please execute the command

$ docker-compose stop

4.2 Modify configuration

Adjust the configuration in docker-compose.yml to reflect your desired database type. Look for all "MySQL" or "PostgreSQL" comments to find all locations you need to switch.

4.3 Recreate containers

To switch the database one needs to recreate used containers. The DB container needs to be started from a different image, using different configuration and volume. The Web container needs to use different Django settings, while startup.

One has to forcibly remove the current containers and create new ones. The final step is to update-initialize the database.

$ docker-compose rm -a -v -f
$ docker-compose create --force-recreate
$ docker-compose start db
$ docker-compose run --rm web migrate

If you haven't created the superuser in the new database environment, you need to execute the command from above to create it.

Create dummy data

If you want to create dummy data you can run:

$ docker-compose run --rm web create_dummy_data 5 --flush True

to get 5 days of dummy data and delete tables in advance.

The number (5 in the above example) creates 5 days dummy data count from today. If you just use create_dummy_data 5 without --flush True it is NOT deleting data before putting new data in.

Additional information

Running with docker container from within PyCharm (2016)

  • Make sure, docker plugin is installed and activated
    • Preferences / Plugins / Docker integration
  • Configure docker
    • Preferences / Build, Execution, Deployments / Docker
    • Create new configuration using + (or modify existing)
    • Choose a reasonable name
    • Add (or modify) API URL
      • see docker-machine env and it's DOCKER_HOST value, replace tcp:// with http://
    • Add (or modify) Certificated folder
      • see DOCKER_CERT_PATH
    • Fill Docker Compose executable
    • Check Import credentials from Docker Machine
    • Fill Docker Machine executable
    • Use Detect
    • Choose Machine
  • Set up remote python interpreter
    • Preferences / Project: ... / Project Interpreter
    • Create Project Interpreter by using [...] and choose Àdd Remote
      • Configure Remote Python Interpreter by choosing Docker
      • Choose Server
      • Use volunteer_web:latest as Image name
      • Use /usr/local/bin/python as Python interpreter path
  • Create run configuration
    • Open run configurations, by choosing Edit Configurations...
    • Create new Python run configuration
    • Choose a reasonable name
    • Choose manage.py within project as Script
    • Use runserver 0.0.0.0:8000 as Script parameter
    • Configure Environment variables
      • PYTHONUNBUFFERED=1
      • DJANGO_SETTINGS_MODULE=volunteer_planner.settings.docker_mysql (if using PostgreSQL modify appropriately)
    • Choose created remote python interpreter as Python interpreter
    • Set project directory as Working directory
    • Set Path mappings
      • <project directory>=/opt/vpcode
    • Check Add content roots to PYTHONPATH
    • Uncheck Add source roots to PYTHONPATH
    • Configure Docker container settings
      • Network mode: volunteer_default
      • Container port: 8000/tcp = 0.0.0.0:8000
      • Link name: volunteer_db_1 aliased to db
      • Volume bindings: Container path /opt/vpcode = Host path <project path>
      • Environment variables: DJANGO_SETTINGS_MODULE=volunteer_planner.settings.docker_mysql (or _postgres)
  • Eventually add IP address used by pydevd to connect to PyCharm as alias
    • IP seems to be 'more or less fixed'
    • sudo ifconfig lo0 alias 10.0.2.2
    • pydevd can now connect from within docker container to PyCharm listener

Speeding up debugging

For better debugger performance PyCharm contains some improvements, starting in version 5.1. See http://blog.jetbrains.com/pycharm/2016/02/faster-debugger-in-pycharm-5-1/ for more information.

To enable debugger speedups using Cython within the docker container we need some preparation.

$ docker ps -a -f name=pycharm_helpers --format '{{.Names}}' |sort
$ PYCHARM_VERSION=<choose from above output, matching 'About PyCharm' / 'Build'
$ printf 'apk add --no-cache gcc musl-dev &&
    /usr/local/bin/python /opt/.pycharm_helpers/pydev/setup_cython.py build_ext --inplace' | \
     docker run --rm -i -u root --volumes-from=${PYCHARM_VERSION} --entrypoint=/bin/sh volunteer_web:latest

This needs to be repeated after PyCharm updates