First, follow the Docker installation instructions to setup your Docker environment and create the project Docker containers.
We use docker-compose
to run an Elasticsearch container, a PostgreSQL container, an Apache container,
and Django in a Python container.
All of these containers are configured in our
docker-compose.yml
file.
See the Docker documentation
for more about the format and use of this file.
The following URLs are mapped to your host from the containers:
- Access consumerfinance.gov directly running in the Python container: http://localhost:8000/
- Access Apache proxying to the Python container: http://localhost:8080/
- Access Elasticsearch: http://localhost:9200/
To build and run the containers for the first time, run:
docker-compose up
Environment variables from your .env
file are sourced
when the Python container starts
and when you access the running Python container.
Your local shell environment variables, however,
are not visible to applications running in Docker.
To add new environment variables, simply add them to the .env
file,
stop docker-compose with Ctrl+C,
and start it again with docker-compose up
.
Django manage.py
commands can only be run after you've
opened up a shell in the Python container.
From there, commands like cfgov/manage.py migrate
should run as expected.
The same goes for scripts like ./refresh-data.sh
and ./initial-data.sh
—
they will work as expected once you’re inside the Python container.
- Python:
docker-compose exec python sh
- Elasticsearch:
docker-compose exec elasticsearch bash
- PostgreSQL:
docker-compose exec postgres bash
The first line
of Dockerfile
sets the base Python Interpreter version for all cfgov
images. Our current pattern is python:MAJOR.MINOR-alpine
for the base image.
This allows us to rapidly incorporate PATCH
versions without the need
for explicit commits.
To update the PATCH
version on your local Docker, replace <MAJOR.MINOR>
with your target and run:
PYTHONVERSION=<MAJOR.MINOR>; \
docker pull python:${PYTHONVERSION}-alpine && \
docker-compose build --no-cache python
If the Python package requirements files have changed,
you will need to stop docker-compose
(if it is running)
and rebuild the Python container using:
docker-compose up --build python
See “Using Docker” on the Related Projects page.
If you have inserted a PDB breakpoint in your code
and need to interact with the running Django process when the breakpoint is reached
you can run docker attach
:
docker attach consumerfinancegov-python-1
When you're done, you can detach with Ctrl+P Ctrl+Q
.
!!! note
`docker attach` takes the specific container name or ID.
Yours may or may not be `consumerfinancegov-python-1`.
To verify, use `docker container ls`
to get the Python container's full name or ID.
!!! note
`docker attach` will ONLY work with the dev image, not prod.
For docker-compose
commands,
[SERVICE]
is the service name that is defined in docker-compose.yml
.
For docker
commands, [CONTAINER]
is the container name displayed with docker ps
.
docker ps
will list all containers.docker logs [CONTAINER]
will print the logs of a container.docker top [CONTAINER]
will display the running processes in a container.docker-compose build [SERVICE]
will build any of our configured containers.
This repository includes a "production-like" Docker image, created for experimenting with how cf.gov could be built and run as a Docker container in production.
This includes:
- all relevant
consumerfinance.gov
source code - all OS, Python, and JS dependencies for building and running cf.gov
- procedures for executing Django
collectstatic
andyarn
-based frontend build process
If you just want to build the image:
docker build . -t your-desired-image-name
You can also launch the full cf.gov stack locally via docker-compose
. This setup is
a nice way to test out new Apache config changes. It includes volumes that mount your
local checkout cfgov/apache
config directories into the container, allowing you to
change configs locally without having to rebuild the image each time.
-
Launch the stack.
docker-compose -f docker-compose.yml -f docker-compose.prod.yml up --build
This creates a container running cf.gov on Python, as well as Postgres and Elasticsearch containers, much like the development environment.
-
Load the
cfgov
database (optional). If you do not already have a runningcfgov
database, you will need to download and load it from within the container.docker-compose exec python sh # Once in the container... export CFGOV_PROD_DB_LOCATION=<database-dump-url> ./refresh-data.sh
-
Browse to your new local cf.gov site:
http://localhost:8080 (Apache)
Or directly to Gunicorn running Django:
http://localhost:8000 (Gunicorn)
-
Adjust an Apache
cfgov/apache
config and restart the Apache container.docker-compose restart apache
-
Switch back to the development Compose setup.
docker-compose rm -sf python docker-compose up --build python
This project heavily utilizes "multi-stage builds".
There are a few layers at work here, with the hierarchy represented by the list structure:
python
, the base Python layer for building up any further layers. It includes OS and Python-level application requirements.node-builder
, a Node-based image that runs our frontend build.dev
, based onpython
, which copies frontend assets fromnode-builder
, sets up some initial data, and runs Django withlocal
settings viarunserver
on port 8000.prod
, based onpython
, which copies frontend assets fromnode-builder
, and runs the application withproduction
settings via Gunicorn on port 8000.