Docker images are a common deployment format.
Docker images typically bundle build artifacts, such as PEX files, wheels, loose files, and so on, with other runtime requirements, such as a Python interpreter.
Pants makes it easy to embed the artifacts it builds into your Docker images, for easy deployment.
To use Pants's Docker support you must enable the appropriate backend:
backend_packages = [ ... "pants.backend.experimental.docker", ... ]
We expect the Docker backend to graduate out of the "experimental" area soon!
A docker image is built from a recipe specified by a Dockerfile. When you build docker images with Pants, instead of running
docker on the Dockerfile directly, you let Pants do that for you.
docker_image targets to indicate which Dockerfiles you want Pants to know about, and to add any necessary metadata.
You can autogenerate initial BUILD files for your Docker images, using tailor:
$ ./pants tailor Created src/docker/app1/BUILD: - Added docker_image target src/docker/app1:docker Created src/docker/app2/BUILD: - Added docker_image target src/docker/app2:docker
Or you can add them manually, such as:
A Dockerfile executes in a context - a set of files that the commands in the Dockerfile can reference, e.g., by copying them into the image).
When you run
docker directly, the context is usually a directory within your repo. That directory must contain the Dockerfile (typically at the root of the context) and any files that the build requires. If those files are themselves the product of a build step, or if they are sources from elsewhere in the repo, then you have to copy them into the context.
Pants, however, takes care of assembling the context for you. It does so using the dependencies of the
docker_image can depend on loose files belonging to files targets, and on artifacts packaged from a variety of targets, such as pex_binary , python_distribution, archive, or any other target that can be built via the package goal.
The context is assembled as follows:
- The sources of
filestargets are assembled at their relative path from the repo root.
- The artifacts of any packageable targets are built, as if by running
./pants package, and placed in the context under a subdirectory named for the target's path from the repo root.
You build Docker images using the
$ ./pants package path/to/Dockerfile
To see this in action, look at the following example:
files( name="msg", sources=["msg.txt"] ) docker_image( name="helloworld", dependencies=[":msg", "src/python/hw:bin"], )
FROM python:3.8 ENTRYPOINT ["/bin/helloworld"] COPY msg.txt /var/msg COPY src.python.hw/bin.pex /bin/helloworld
python_library(interpreter_constraints=["=3.8"]) pex_binary( name="bin", entry_point="main.py", )
import os if os.path.exists("/var/msg"): with open("/var/msg") as fp: msg = fp.read().strip() else: msg = "Hello" print(msg)
$ ./pants package src/docker/hw/Dockerfile [...] 18:07:29.66 [INFO] Completed: Building src.python.hw/bin.pex 18:07:31.83 [INFO] Completed: Building docker image helloworld:latest 18:07:31.83 [INFO] Built docker image: helloworld:latest To try out the image interactively: docker run -it --rm helloworld:latest [entrypoint args...] To push your image: docker push helloworld:latest $ docker run -it --rm helloworld:latest Hello, Docker!
By default the built image gets a
latest tag. To select another value to use, provide a
version value to
docker_image( name="helloworld", version="1.2.0", dependencies=[":msg", "src/python/hw:bin"], )
Generating custom tags at runtime based on Git state or image inputs requires you to write some custom plugin code. Don't hesitate to reach out for help with this.
We are looking into adding this functionality into the core Docker plugin in the future.
Pants can run
hadolint on your Dockerfiles to check for errors and mistakes:
$ ./pants lint src/docker/hw/Dockerfile
This must first be enabled by adding the following configuration:
[GLOBAL] backend_packages.add = ["pants.backend.experimental.docker.lint.hadolint"]
Updated about 2 years ago