Treeherder developer ergonomics

In the last few months I’ve worked with contributors who wanted to be selected to work on Treeherder during this year’s Google Summer of Code. The initial proposal was to improve various Treeherder developer ergonomics (read: make Treeherder development easier). I’ve had three very active contributors that have helped to make a big difference (in alphabetical order): Shubham, Shubhank and Suyash.

In this post I would like to thank them publicly for all the work they have accomplished as well as list some of what has been accomplished. There’s also listed some work from Kyle who tackled the initial work of allowing normal Python development outside of Docker (more about this later).

After all, I won’t be participating in GSoC due to burn-out and because this project is mostly completed (thanks to our contributors!). Nevertheless, two of the contributors managed to get selected to help with Treeherder (Suyash) and Firefox Accounts (Shubham) for GSoC. Congratulations!

Some of the developer ergonomics improvements that landed this year are:

  • Support running Treeherder & tests outside of Docker. Thanks to Kyle we can now set up a Python virtualenv outside of Docker and interact with all dependent services (mysql, redis and rabbitmq). This is incredibly useful to run tests and the backend code outside of Docker and to help your IDE install all Python packages in order to better analyze and integrate with your code (e.g., add breakpoints from your IDE). See PR here.
  • Support manual ingestion of data. Before, you could only ingest data when you would set up the Pulse ingestion. This mean that you could only ingest real-time data (and all of it!) and you could not ingest data from the past. Now, you can ingest pushes, tasks and even Github PRs. See documentation.
  • Add pre-commit hooks to catch linting issues. Prior to this, linting issues would require you to remember to run a script with all the linters or Travis to let you know. You can now get the linters to execute automatically on modified files (instead of all files in the repo), shortening the linting-feedback cycle. See hooks in pre-commit file
  • Use Poetry to generate the docs. Serving locally the Treeherder docs is now as simple as running “poetry install && poetry run mkdocs serve.” No more spinning up Docker containers or creating and activating virtualenvs. We also get to introduce Poetry as a modern dependency and virtualenv manager. See code in pyproject.toml file
  • Automatic syntax formatting. The black pre-commit hook now formats files that the developer touches. No need to fix the syntax after Travis fails with linting issues.
  • Ability to run the same tests as Travis locally. In order to reduce differences between what Travis tests remotely and what we test locally, we introduced tox. The Travis code simplifies, the tox code can even automate starting the Docker containers and it removed a bash script that was trying to do what tox does (Windows users cannot execute bash scripts).
  • Share Pulse credentials with random queue names. In the past we required users to set up an account with Pulse Guardian and generate their own PULSE_URL in order to ingest data. Last year, Dustin gave me the idea that we can share Pulse credentials; however, each consumer must ingest from dynamically generated queue names. This was initially added to support Heroku Review Apps, however, this works as well for local consumers. This means that a developer ingesting data would not be taking away Pulse messages from the queue of another developer.
  • Automatically delete Pulse queues. Since we started using shared credentials with random queue names, every time a developer started ingesting data locally it would leave some queues behind in Pulse. When the local consumers stopped, these queues would overgrow and send my team and I alerts about it. With this change, the queues would automatically be destroyed when the consumers ceased to consume.
  • Docker set up to automatically ingest data. This is useful since ingesting data locally required various steps in order to make it work. Now, the Docker set up ingests data without manual intervention.
  • Use pip-compile to generate requirement files with hashes. Before, when we needed to update or add a Python package, we also had to add the hashes manually. With pip-compile, we can generate the requirement files with all hashes and subdepencies automatically. You can see the documentation here.

There’s many more changes that got fixed by our contributors, however, I won’t cover all of them. You can see the complete list in here.

Thank you for reading this far and thanks again to our contributors for making development on Treeherder easier!

Follower of Christ writing developer tools, web fullstack & automation solutions.