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CONTRIBUTING.md

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Contributing

This guide explains how to set up the graphql-engine server for development on your own machine and how to contribute.

Prerequisites

The following tools are required. Versions are typically specified in VERSIONS.json.

  • GHC
    • There are various ways this can be installed, but ghcup is a good choice if you’re not sure.
    • If you are not using ghcup, make sure you install the GHC version specified in .ghcversion.
  • Cabal
    • if you use ghcup, you can get Cabal from there too.
  • There are few system packages required like libpq-dev, libssl-dev, etc. The best place to get the entire list is from the Dockerfile
  • Additional Haskell tools:
    • HLint, for linting Haskell code
    • Ormolu, for formatting Haskell code
  • Docker
  • Docker Compose

For running the test suite:

  • node.js (see .nvmrc for the version), and the bundled NPM version
  • Python >= 3.9 with pip3 and virtualenv

For building the Console:

  • node.js, as above

Additionally, you will need a way to run a PostgreSQL database server. The dev.sh script (described below) can set up a PostgreSQL instance for you via Docker, but if you want to run it yourself, you’ll need:

Installing tooling with Nix

Simply install Nix and type nix develop.

If you don't want to start a new shell each time, you can also use direnv and nix-direnv, then create a .envrc.local file with the contents:

#!/usr/bin/env bash

use flake

Installing tooling with direnv

This project contains scripts for installing project dependencies automatically with direnv. For more information, see the .envrc file in the root.

Development workflow

You should fork the repo on github and then git clone https://github.com/<your-username>/graphql-engine. After making your changes

Compile

...console assets:

$ cd frontend
$ nvm use
$ npm ci
$ npm run server-build:ce
$ cd ..

...and the server:

$ ln -s cabal/dev.project cabal.project.local
$ cabal new-update
$ cabal new-build graphql-engine

To set up the project configuration to coincide with the testing scripts below, thus avoiding recompilation when testing locally, rather use cabal/dev-sh.project.local instead of cabal/dev.project:

$ ln -s cabal/dev-sh.project.local cabal.project.local

Compiling on MacOS

If you are on MacOS, or experiencing any errors related to missing dependencies on MacOS, please try this alternative setup guide, or try Nix (as above).

IDE Support

You may want to use hls/ghcide if your editor has LSP support. A sample configuration has been provided which can be used as follows:

ln -s sample.hie.yaml hie.yaml

If you have to customise any of the options for ghcide/hls, you should instead copy the sample file and make necessary changes in hie.yaml file. Note that hie.yaml is gitignored so the changes will be specific to your machine.

cp sample.hie.yaml hie.yaml

Run and test via run-new.sh

The run-new.sh scripts are an active work in progress, and will eventually replace the dev.sh option below.

Run the Python integration tests with ./server/tests-py/run-new.sh.

Filter on specific test files with ./server/tests-py/run-new.sh -- create_async_action_with_nested_output_and_relation.py

If you have any issues with run-new.sh, please create a GitHub issue and run and test via dev.sh instead.

Run and test via dev.sh

The dev.sh script in the top-level scripts/ directory is a turnkey solution to build, run, and test graphql-engine using a Docker container to run a Postgres database. Docker is necessary to use dev.sh.

To use dev.sh, first launch a new postgres container with:

$ scripts/dev.sh postgres

Then in a new terminal launch graphql-engine in dev mode with:

$ scripts/dev.sh graphql-engine

This command also starts the GraphQL Engine console, which you can access at http://localhost:8181/console.

The dev.sh will print some helpful information and logs from both services will be printed to screen.

You can run the test suite with:

$ scripts/dev.sh test

This should run in isolation. The output format is described in the pytest documentation. Errors and failures are indicated by Fs and Es.

Optionally, launch a new container for alternative (MSSQL) backend with:

$ scripts/dev.sh mssql

Tests can be run against a specific backend (defaulting to Postgres) with the backend flag, for example:

$ scripts/dev.sh test --integration -k TestGraphQLQueryBasicCommon --backend (bigquery|citus|mssql|postgres)

Run and test manually

If you want, you can also run the server and test suite manually against an instance of your choosing.

Run

The following command can be used to build and launch a local graphql-engine instance:

$ cabal new-run -- exe:graphql-engine \
    --database-url='postgres://<user>:<password>@<host>:<port>/<dbname>' \
    serve --enable-console --console-assets-dir=frontend/dist/apps/server-assets-console-ce

This will launch a server on port 8080, and it will serve the console assets if they were built with npm run server-build:ce as mentioned above.

Test

graphql-engine has several test suites, among them:

  1. A small set of unit tests and integration tests written in Haskell, in server/src-test.

  2. A new integration test suite written in Haskell, in server/lib/api-tests.

  3. An extensive set of end-to-end tests written in Python, in server/tests-py.

All sets of tests require running databases:

  • some unit tests hit the database, and running the unit test suite requires passing in a postgres connection string,
  • the Haskell integration test suite requires databases to run (they can be started via the docker command listed below),
  • the Python integration test suite also requires databases AND the engine to be running, which can be started via either the dev.sh script, or manually.
Running py tests

The easiest way to run the Python integration test suite is by running:

$ scripts/dev.sh test --integration

For more details please check out the README.

Running the Haskell test suite

There are three categories of unit tests:

  • unit tests
  • PostgreSQL integration tests (requires a PostgreSQL instance)
  • MS SQL Server integration tests (requires a MS SQL Server instance)

The easiest way to run these tests is through make, which will automatically spin up and shut down Docker containers for the databases:

$ make test-unit
$ make test-integration-postgres
$ make test-integration-mssql

If you want to limit to a specific set of tests, use HSPEC_MATCH:

$ make test-unit HSPEC_MATCH='Memoize'

Alternatively, you can use Cabal directly (though you'll have to start the databases yourself):

$ cabal run -- graphql-engine:test:graphql-engine-tests
$ HASURA_GRAPHQL_DATABASE_URL='postgres://<user>:<password>@<host>:<port>/<dbname>' \
    cabal run -- graphql-engine:test:graphql-engine-test-postgres
Running the Haskell integration test suite

Run make test-backends. This effectively runs the following two commands:

$ docker compose up --detach --wait
$ cabal run api-tests:exe:api-tests

For more details please check out the README.

Running unit tests and recompiling

While working on features, you might want to add unit tests and work through getting them to pass. This is generally a slow process, but there is a workaround to allow loading both the graphql-engine library and the unit testing library in ghcid at the same time:

$ ghcid -a -c "cabal repl graphql-engine-tests -f -O0 -fghci-load-test-with-lib" --test Main.main

This assumes you already have HASURA_GRAPHQL_DATABASE_URL and HASURA_MSSQL_CONN_STR exported as environment variables.

If you just want to run all unit tests, you can add --setup ":set args unit" to the command line above. If you want to run specific test(s), you can instead do --setup ":set args unit --match name_of_test(s)".

Building with profiling

To build with profiling support, you need to both enable profiling via cabal and set the profiling flag. E.g.

$ cabal build exe:graphql-engine -f profiling --enable-profiling

Create Pull Request

  • Make sure your commit messages meet the guidelines.
  • If you changed the versions of any dependencies, run scripts/cabal-freeze-update.sh --all to update the freeze file.
  • Create a pull request from your forked repo to the main repo.
  • Every pull request will automatically build and run the tests.

Code conventions

The following conventions help us maintain a uniform style for all committers: make sure your contributions are in line with them.

We enforce these by means of CI hooks which will fail the build if any of these are not met.

  • No compiler warnings: Make sure your code builds with no warnings (adding -Werror to ghc-options in your cabal.project is a good way of checking this.)
  • No lint failures: Use hlint with our custom config to validate your code, using hlint --hint=../.hlint.yaml.
  • Consistent formatting: Use ormolu to format your code. ormolu -ei '*.hs' will format all files with a .hs extension in the current directory.
  • Consistent style: Consider the style guide when writing new code.

Testing

Please see testing-guidelines for details on how to add tests.

Local hoogle instance

Hoogle is a Haskell API search engine. The server at hoogle.haskell.org provides a version of Hoogle that enables searching through all packanges available in Stackage. Following instructions help in setting up a local hoogle server that enables searching through graphql-engine server code.

Step 1: Installing hoogle

Installing hoogle is fairly simple with cabal.

$ cabal install hoogle

Step 2: Generating hoogle database

A Hoogle database is a prebuilt index of a set of packages. The hoogle.sh script in the top-level scripts/ directory helps in generating the hoogle database for GraphQL Engine server code and store it in dist-newstyle/ directory.

$ scripts/hoogle.sh generate

Step 3: Running hoogle instance

Running the following hoogle.sh script command starts a local hoogle server with the database generated in Step 2.

$ scripts/hoogle.sh serve

Use --port option to specify custom port to start hoogle server.

$ scripts/hoogle.sh serve --port 8181