Development
Setting up an initial dev environment
We can set up a local development environment sufficient for navigating, editing, and testing PRQL’s compiler code in two minutes:
Install rustup & cargo.
[Optional but highly recommended] Install
cargo-insta
, our testing framework:cargo install cargo-insta
That’s it! Running the unit tests for the
prql-compiler
crate after cloning the repo should complete successfully:cargo test --package prql-compiler --lib
…or, to run tests and update the test snapshots:
cargo insta test --accept --package prql-compiler --lib
There’s more context on our tests in How we test below.
That’s sufficient for making an initial contribution to the compiler.
Setting up a full dev environment
Info
We really care about this process being easy, both because the project benefits from more contributors like you, and to reciprocate your future contribution. If something isn’t easy, please let us know in a GitHub Issue. We’ll enthusiastically help you, and use your feedback to improve the scripts & instructions.
For more advanced development; for example compiling for wasm or previewing the website, we have two options:
Option 1: Use the project’s task
Note
This is tested on macOS, should work on amd64 Linux, but won’t work on others (include Windows), since it relies on brew
.
Then run the
setup-dev
task. This runs commands from our Taskfile.yml, installing dependencies withcargo
,brew
,npm
&pip
, and suggests some VS Code extensions.task setup-dev
Option 2: Install tools individually
We’ll need
cargo-insta
, to update snapshot tests:cargo install cargo-insta
We’ll need Python, which most systems will have already. The easiest way to check is to try running the full tests:
cargo test
…and if that doesn’t complete successfully, ensure we have Python >= 3.7, to compile
prql-python
.For more involved contributions, such as building the website, playground, book, or some release artifacts, we’ll need some additional tools. But we won’t need those immediately, and the error messages on what’s missing should be clear when we attempt those things. When we hit them, the Taskfile.yml will be a good source to copy & paste instructions from.
Option 3: Use aDev Container
This project has a devcontainer.json file and a pre-built dev container base Docker image.
Currently, the tools for Rust are already installed in the pre-built image, and, Node.js, Python and others are configured to be installed when build the container.
While there are a variety of tools that support Dev Containers, the focus here is on developing with VS Code in a container by GitHub Codespaces or VS Code Dev Containers extension.
To use a Dev Container on a local computer with VS Code, install the VS Code Dev Containers extension and its system requirements. Then refer to the links above to get started.
Option 4: Use nix development environment
A nix flake flake.nix
provides 3 development environments:
- default, for building the compiler
- web, for the compiler and the website,
- full, for the compiler, the website and the compiler bindings.
To load the shell:
Install nix (the package manager). (only first time)
Enable flakes, which are a (pretty stable) experimental feature of nix. (only first time)
For non-NixOS users:
mkdir -p ~/.config/nix/
tee 'experimental-features = nix-command flakes' >> ~/.config/nix/nix.conf
For NixOs users, follow instructions here.
Run:
nix develop
If you want “web” or “full” shell, run:
nix develop .#web
Optionally, you can install direnv, to automatically load the shell when you enter this repo. The easiest way is to also install direnv-nix and configure your .envrc
with:
# .envrc
use flake .#full
Contribution workflow
We’re similar to most projects on GitHub — open a Pull Request with a suggested change!
Commits
- If a change is user-facing, please add a line in CHANGELOG.md, with
{message}, ({@contributor, #X})
whereX
is the PR number.- If there’s a missing entry, a follow-up PR containing just the changelog entry is welcome.
- We’re using Conventional Commits message format, enforced through action-semantic-pull-request.
Merges
- We merge any code that makes PRQL better
- A PR doesn’t need to be perfect to be merged; it doesn’t need to solve a big problem. It needs to:
- be in the right direction,
- make incremental progress,
- be explicit on its current state, so others can continue the progress.
- That said, there are a few instances when we need to ensure we have some consensus before merging code — for example non-trivial changes to the language, or large refactorings to the library.
- If you have merge permissions, and are reasonably confident that a PR is suitable to merge (whether or not you’re the author), feel free to merge.
- If you don’t have merge permissions and have authored a few PRs, ask and ye shall receive.
- The primary way we ratchet the code quality is through automated tests.
- This means PRs almost always need a test to demonstrate incremental progress.
- If a change breaks functionality without breaking tests, our tests were probably insufficient.
- If a change breaks existing tests (for example, changing an external API), that indicates we should be careful about merging a change, including soliciting others’ views.
- We use PR reviews to give general context, offer specific assistance, and collaborate on larger decisions.
- Reviews around ‘nits’ like code formatting / idioms / etc are very welcome. But the norm is for them to be received as helpful advice, rather than as mandatory tasks to complete. Adding automated tests & lints to automate these suggestions is welcome.
- If you have merge permissions and would like a PR to be reviewed before it merges, that’s great — ask or assign a reviewer.
- If a PR hasn’t received attention after a day, please feel free to ping the pull request.
- People may review a PR after it’s merged. As part of the understanding that we can merge quickly, contributors are expected to incorporate substantive feedback into a future PR.
- We should revert quickly if the impact of a PR turns out not to be consistent with our expectations, or there isn’t as much consensus on a decision as we had hoped. It’s very easy to revert code and then re-revert when we’ve resolved the issue; it’s a sign of moving quickly. Other options which resolve issues immediately are also fine, such as commenting out an incorrect test or adding a quick fix for the underlying issue.
Docs
We’re very keen on contributions to improve our documentation.
This includes our docs in the book, on the website, in our code, or in a Readme. We also appreciate issues pointing out that our documentation was confusing, incorrect, or stale — if it’s confusing for you, it’s probably confusing for others.
Some principles for ensuring our docs remain maintainable:
- Docs should be as close as possible to the code. Doctests are ideal on this dimension — they’re literally very close to the code and they can’t drift apart since they’re tested on every commit. Or, for example, it’s better to add text to a
--help
message, rather than write a paragraph in the Readme explaining the CLI. - We should have some visualization of how to maintain docs when we add them. Docs have a habit of falling out of date — the folks reading them are often different from those writing them, they’re sparse from the code, generally not possible to test, and are rarely the by-product of other contributions. Docs that are concise & specific are easier to maintain.
- Docs should be specifically relevant to PRQL; anything else we can instead link to.
If something doesn’t fit into one of these categories, there are still lots of ways of getting the word out there — a blog post / gist / etc. Let us know and we’re happy to link to it / tweet it.
How we test
We use a pyramid of tests — we have fast, focused tests at the bottom of the pyramid, which give us low latency feedback when developing, and then slower, broader tests which ensure that we don’t miss anything as PRQL develops1.
Info
If you’re making your first contribution, you don’t need to engage with all this — it’s fine to just make a change and push the results; the tests that run in GitHub will point you towards any errors, which can be then be run locally if needed. We’re always around to help out.
Our tests, from the bottom of the pyramid to the top:
Static checks — we run a few static checks to ensure the code stays healthy and consistent. They’re defined in .pre-commit-config.yaml, using pre-commit. They can be run locally with
task test-lint
# or
pre-commit run -a
The tests fix most of the issues they find themselves. Most of them also run on GitHub on every commit; any changes they make are added onto the branch automatically in an additional commit.
- Checking by MegaLinter, which includes more Linters, is also done automatically on GitHub. (experimental)
Unit tests & inline insta snapshots — we rely on unit tests to rapidly check that our code basically works. We extensively use Insta, a snapshot testing tool which writes out the values generated by our code, making it fast & simple to write and modify tests2
These are the fastest tests which run our code; they’re designed to run on every save while you’re developing. We include a
task
which does this:task test-rust-fast
# or
cargo insta test --accept --package prql-compiler --lib
# or, to run on every change:
task -w test-rust-fast
Documentation — we compile all examples from our documentation in the Website, README, and PRQL Book, to test that they produce the SQL we expect, and that changes to our code don’t cause any unexpected regressions. These are included in:
cargo insta test --accept
Integration tests — we run tests with example queries against databases with actual data to ensure we’re producing correct SQL across our supported dialects. The in-process tests can be run locally with:
task test-rust
# or
cargo insta test --accept --features=test-dbs
More details on running with external databases are in the Readme.
Note