Overview
How to build Docker images containing artifacts built by Pants
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 Pants builds into your Docker images, for easy deployment.
Enabling the Docker backend
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!
Adding docker_image
targets
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.
Pants uses docker_image
targets to indicate which Dockerfiles you want Pants to know about, and to add any necessary metadata.
You can generate initial BUILD files for your Docker images, using tailor:
❯ ./pants tailor
Created src/docker/app1/BUILD:
- Add docker_image target docker
Created src/docker/app2/BUILD:
- Add docker_image target docker
Or you can add them manually, such as:
docker_image(name="docker")
Alternatively you may provide the Docker build instructions inline in your BUILD file as instructions
on your docker_image
if you don't want to create a Dockerfile
.
docker_image(
name="docker",
instructions=[
"FROM python:3.8",
"RUN ..",
]
)
docker_image
instructions
fieldEach docker_image
uses a Dockerfile
referred to by the source
field, unless you have provided a value to the instructions
field.
When using the instructions
field, make sure that the default value for source
does not match a file, or there will be a conflict which information to use.
Adding dependencies to your docker_image
targets
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
target.
A docker_image
can depend on loose files belonging to file
/ 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
file
/files
targets 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 using the artifact'soutput_path
field.- The
output_path
defaults to the schemepath.to.directory/tgt_name.ext
, e.g.src.python.helloworld/bin.pex
.
- The
Dependency inference
When you COPY
PEX binaries into your image, the dependency on the pex_binary
target will be inferred, so you don't have to add that explicitly to the list of dependencies
on your docker_image
target.
For example, the pex_binary
target src/python/helloworld/bin.pex
has the default output_path
of src.python.helloworld/bin.pex
. So, Pants can infer a dependecy based on the line COPY src.python.helloworld/bin.pex /bin/helloworld
.
Building a Docker image
You build Docker images using the package
goal:
❯ ./pants package path/to/Dockerfile
Build arguments
To provide values to any build ARG
s in the Dockerfile, you can list them in the [docker].build_args
configuration option which will apply for all images, and list any image specific build args in the field extra_build_args
for the docker_image
target.
The build args use the same syntax as the docker build --build-arg command line option: VARNAME=VALUE
, where the value is optional, and if left out, the value is taken from the environment instead.
- pants.toml
- example/BUILD
- example/Dockerfile
[docker]
build_args = [
"VAR1=value1",
"VAR2"
]
docker_image(
name="docker",
extra_build_args=["VAR1=my_value", "VAR3"]
)
FROM python:3.8
ARG VAR1
ARG VAR2
ARG VAR3=default
...
Target build stage
When your Dockerfile
is a multi stage build file, you may specify which stage to build with the --docker-build-target-stage
for all images, or provide a per image setting with the docker_image
field target_stage
.
FROM python:3.8 AS base
RUN <install required tools>
FROM base AS img
COPY files /
❯ ./pants package --docker-build-target-stage=base Dockerfile
Build time secrets
Secrets are supported for docker_image
targets with the secrets
field. The defined secrets may then be mounted in the Dockerfile
as usual.
- BUILD
- dockerfile
- mysecret.txt
docker_image(
secrets={
"mysecret": "mysecret.txt",
}
)
FROM python:3.8
# shows secret from default secret location:
RUN cat /run/secrets/mysecret
# shows secret from custom secret location:
RUN cat /foobar
very-secret-value
Secrets should not be checked into version control. Use absolute paths to reference a file that is not in the project source tree. However, to keep the BUILD file as hermetic as possible, the files may be placed within the project source tree at build time for instance, and referenced with a path relative to the project root by default, or relative to the directory of the BUILD file when prefixed with ./
.
See the example for the secrets
field.
Build Docker image example
This example copies both a file
and pex_binary
:
- src/docker/hw/BUILD
- src/docker/hw/Dockerfile
- src/docker/hw/msg.txt
- src/py/hw/BUILD
- src/py/hw/main.py
file(name="msg", source="msg.txt")
docker_image(
name="docker",
dependencies=[":msg", "src/python/hw:bin"],
)
FROM python:3.8
ENTRYPOINT ["/bin/helloworld"]
COPY src/docker/hw/msg.txt /var/msg
COPY src.python.hw/bin.pex /bin/helloworld
Hello, Docker!
python_sources(name="lib")
pex_binary(name="bin", entry_point="main.py")
import os
msg = "Hello"
if os.path.exists("/var/msg"):
with open("/var/msg") as fp:
msg = fp.read().strip()
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
Running a Docker image
You can ask Pants to run a Docker image on your local system with the run
goal:
❯ ./pants run src/docker/hw/Dockerfile
Hello, Docker!
Any arguments for the Docker container may be provided as pass through args to the run
goal, as usual. That is, use either the --args
option or after all other arguments after a separating double-dash:
❯ ./pants run src/docker/hw/Dockerfile -- arguments for the container
Hello, Docker!
To provide any command line arguments to the docker run
command, you may use the --docker-run-args
option:
❯ ./pants run --docker-run-args="-p 8080 --name demo" src/docker/hw/Dockerfile
As with all configuration options, this is not limited to the command line, but may be configured in a Pants rc file (such as pants.toml
) in the [docker].run_args
section or as an environment variable, PANTS_DOCKER_RUN_ARGS
as well.
Publishing images
Pants can push your images to registries using ./pants publish
:
❯ ./pants publish src/docker/hw:helloworld
# Will build the image and push it to all registries, with all tags.
See here for how to set up registries.
Docker configuration
To configure the Docker binary, set [docker].env_vars
in your pants.toml
configuration file. You use that key to list environment variables such as DOCKER_CONTEXT
or DOCKER_HOST
, that will be set in the environment of the docker
binary when Pants runs it. Each listed value can be of the form NAME=value
, or just NAME
, in which case the value will be inherited from the Pants process's own environment.
[docker]
env_vars = [
"DOCKER_CONTEXT=pants_context",
"DOCKER_HOST"
]
Linting Dockerfiles with Hadolint
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 activating the Hadolint backend:
[GLOBAL]
backend_packages.add = ["pants.backend.experimental.docker.lint.hadolint"]