Intro

An opinionated template repo for multi-lingual projects using Bazel, built around the principle that wherever possible projects should be hermetic and reproducible. It includes:

• Automated linting for Bazel, Python, Markdown, and Golang sources with a wide variety of hermetically-provided linters including:
  • Buildifier
  • Flake8
  • Black
  • Isort
  • Prettier
  • go fmt
• Python test helpers to simplify unit test targets
• Hermetic Python & Golang toolchains
• Hermetic pip dependencies sourced from requirements.txt
• Python & Golang Docker image support, including a matching runtime version as the hermetic toolchains.

It does not seek to provide a continual submodule that can pick up upstream changes from the template, but is more like a create-react-app template where you can eject from the template and proceed with your project. That being said, if you don't change any paths you can likely git cherry-pick or otherwise patch in changes from upstream and then run eject.sh again to update paths for your project.

Setup

1. Install Bazel. Instructions for doing so can be found here: https://docs.bazel.build/versions/master/install.html
   • Also consider using bazelisk to automatically install the proper bazel version
2. Run the template eject script, providing your project's name. ./eject.sh <project_name>

Development

Pull requests are welcome! Open one against this repo and it will be reviewed & merged.

Adding New Dependencies

Python

To add a new python pip dependency:

1. Add the new dependency to requirements.in
2. Run bazel run //:requirements.update
3. Commit the updates to requirements_lock.txt

Golang

To add a new golang dependency:

1. Begin using the dependency in your Go code

2. Run bazel run @rules_go//go get <dependency> to add the dependency to go.mod

3. Run bazel run @rules_go//go mod tidy to pull in the transitive deps and update go.mod to show it as used

4. Run bazel run //:gazelle to update your build files. This will print a warning like the following

   $ bazel run //:gazelle
   WARNING: /Users/jcureton/development/personal/python_bazel_template/MODULE.bazel:39:24: The module extension go_deps defined in @gazelle//:extensions.bzl reported incorrect imports of repositories via use_repo():
   
   Not imported, but reported as direct dependencies by the extension (may cause the build to fail):
      io_rsc_quote
   
   ** You can use the following buildozer command to fix these issues:
   
   buildozer 'use_repo_add @gazelle//:extensions.bzl go_deps io_rsc_quote' //MODULE.bazel:all

5. Run the printed buildozer command with bazel run -- //tools/buildozer ...

6. Commit the updates to go.mod, go.sum, MODULE.bazel, MODULE.bazel.lock, and any build files.

Linting

In general, lint by running the lint.sh script.

The first time you run lint, you'll see a warning like:

UserWarning: `known_${project}` setting is defined, but ${project} is not included in `sections`
config option: ('FUTURE', 'STDLIB', 'THIRDPARTY', '${project}', 'FIRSTPARTY', 'LOCALFOLDER').

To resolve this, open pyproject.toml in the repo root, and update the <project> reference in SECTIONS on line 11 to be capitalized. This is a known issue with the basic templating script used in the repo, and PRs are welcome if you have a resolution :)

You can manually run ${Buildifier/Flake8/Black/Isort/Prettier} with the following if you want to, though you'll have to handle paths manually to prevent them from working on the Bazel sandbox.

• bazel run //tools/${tool}

Testing

Unit tests are run using the bazel test command. A test wrapper is provided that invokes pytest with reasonable defaults and configures the entrypoint. You just write pytest test cases in normal Python files, and pass these as srcs to a ${project}_py_test rule. The test runner handles the rest.

Language Support

Currently this Bazel workspace supports building/running on macOS and Linux. Windows support is explicitly unscoped. The currently-supported languages are:

• Python
• Golang

Python

Running an interactive python session

You can run an interactive python session via either an ipython shell or a Jupyter notebook. By default, both include the //${project} bazel target so you can make use of ${project} code interactively.

1. iPython - bazel run //tools/ipython. You'll be dropped into a python shell in the Bazel sandbox
2. Jupyter - bazel run //tools/jupyter. You'll be dropped into a Jupyter web interface. You can create a new Notebook to experiment. In general, consider these environments to be ephemeral, but if needed the notebook is created inside bazel-bin/tools/jupyter/jupyter.runfiles/__main__. Alternatively, consider downloading the notebook from the web UI if you will continue to need it.

By default this includes the //${project} target, so you can make use of ${project} code interactively

Containerization

We provide builtin ${project}_py_image and ${project}_go_image macros that make it easy to containerize any binary target. By default, these are built for the same architecture as the current host.

You can manually override this and build for a different platform using the --platforms=//tools/platforms:container_{arch}_linux build flag.

${project}_py_image(
    name = "${project}_img",
    binary = ":${project}_bin",
    image_tags = ["${project}:latest"],
)

# Build default image for current host architecture and load it into docker
bazel run //${project}:${project}_img_load_docker
# Build default image for specific architecture
bazel run --platforms=//tools/platforms:container_x86_64_linux //${project}:${project}_img_load_docker