graphql-engine/server/tests-hspec

tests-hspec

Graphql-engine integration tests written in Haskell using the hspec testing framework.

For motivation, rationale, and more, see the test suite rfc.

Table of Contents

• tests-hspec
  • Required setup for BigQuery tests
  • Running the test suite
  • Enabling logging
  • Test suite structure
    • Harness
    • Test
  • Adding a new test
    • Specifying contexts
      • Make local testEnvironment action
      • Setup action
      • Teardown action
    • Writing tests
  • Debugging
  • Style guide
    • Stick to Simple Haskell
    • Write small, atomic, autonomous specs
    • Use the Harness.* hierarchy for common functions
  • Troubleshooting
    • Database 'hasura' already exists. Choose a different database name.

Required setup for BigQuery tests

Running integration tests against a BigQuery data source is a more involved due to the necessary service account requirements:

HASURA_BIGQUERY_PROJECT_ID=# the project ID of the service account
HASURA_BIGQUERY_SERVICE_KEY=# the service account key
# optional variable used to verify the account setup in step 4 below
HASURA_BIGQUERY_SERVICE_ACCOUNT_EMAIL=# eg. "<<SERVICE_ACCOUNT_NAME>>@<<PROJECT_NAME>>.iam.gserviceaccount.com"

Before running the test suite:

1. Ensure you have access to a Google Cloud Console service account. Store the project ID and account email in HASURA_BIGQUERY_PROJECT_ID variable.
2. Create and download a new service account key. Store the contents of file in a HASURA_BIGQUERY_SERVICE_KEY variable.

   export HASURA_BIGQUERY_SERVICE_KEY=$(cat /path/to/service/account)
   

3. Login and activate the service account, if it is not already activated.
4. Verify the service account is accessible via the BigQuery API:
   1. Run the following command:

   source scripts/verify-bigquery-creds.sh $HASURA_BIGQUERY_PROJECT_ID $HASURA_BIGQUERY_SERVICE_KEY $HASURA_BIGQUERY_SERVICE_ACCOUNT_EMAIL
   

   If the query succeeds, the service account is setup correctly to run tests against BigQuery locally.
5. Finally, run the BigQuery tests once the HASURA_BIGQUERY_SERVICE_KEY and HASURA_BIGQUERY_PROJECT_ID environment variables set. For example:

cabal run tests-hspec -- -m "BigQuery"

Note to Hasura team: a service account is already setup for internal use, please check the wiki for further details.

Running the test suite

1. To run the Haskell integration test suite, we'll first need to start the backends:

   docker-compose up
   

   This will start up Postgres, SQL Server, Citus and MariaDB.

   Note

   : on ARM64 architecture we'll need additional steps in order to test mssql properly.

   Preparation

   1. Switch the docker image in docker-compose/sqlserver/Dockerfile to azure-sql-edge:

   - FROM mcr.microsoft.com/mssql/server:2019-latest@sha256:a098c9ff6fbb8e1c9608ad7511fa42dba8d22e0d50b48302761717840ccc26af
   + FROM mcr.microsoft.com/azure-sql-edge
   

   2. Install sqlcmd locally. On MacOS, this can be done with brew: brew install mssql-tools.

   Start the backends

   1. Run docker-compose up

   2. Initialize the SQL Server database

      (cd docker-compose/sqlserver && bash run-init.sh 65003)
      

2. Once the containers are up, you can run the test suite via

   cabal run tests-hspec
   

   You can also further refine which tests to run using the -m flag:

   cabal run tests-hspec -- -m "SQLServer"
   

   For additional information, consult the help section:

   cabal run tests-hspec -- --help
   

3. The local databases persist even after shutting down docker-compose. If this is undesirable, delete the databases using the following command:

   docker-compose down --volumes
   

Enabling logging

In order to enable logging, you have to manually edit the engineLogLevel term in Harness/Constants.hs.

This pairs well with running a single test via the -m flag (see the section above).

Test suite structure

Harness

Modules under the Harness/ namespace provide the infrastructure and supporting code for writing and running the tests. It includes quasiquoters, interacting with backends, interfacing with HTTP, constants, and so on.

Supporting code should be added under the Harness.* namespace instead of added ad-hoc in test specs, to improve readability and reuse.

Test

Modules under the Test/ namespace define integration test specifications for various features and backends.

Adding a new test

The module Test.HelloWorldSpec contains a starting point which can be built upon.

To create a new test:

1. Create a new module based on Test.HelloWorldSpec
2. Specify each relevant context on which the tests will run in spec
3. Specify the tests and expectations in tests

When creating a new test, make sure that:

1. The module name is suffixed by the word Spec
2. The module exports the entry point spec :: SpecWith TestEnvironment
3. The module is listed in the cabal file under other-modules

(1) and (2) are required for hspec-discover to find and run the test.

Specifying contexts

We often want to run the same tests several times with slightly different configuration. Most commonly, we want to assert that a given behaviour works consistently across different backends.

Harness.Test.Context defines two functions for running test trees in terms of a list of Context as.

Each Context a requires:

• a unique name, of type ContextName
• a mkLocalTestEnvironment action, of type TestEnvironment -> IO a
• a setup action, of type (TestEnvironment, a) -> IO ()
• a teardown action, of type (TestEnvironment, a) -> IO ()
• an customOptions parameter, which will be threaded through the tests themselves to modify behavior for a particular Context

Of these two functions, whether one wishes to use Harness.Test.Context.run or Harness.Test.Context.runWithLocalTestEnvironment will depend on if their test can be written in terms of information provided by the global TestEnvironment type or if it depends on some additional "local" state.

More often than not, test authors should use Harness.Test.Context.run, which is written in terms of Context (). This uses () for the local test which does not carry any "useful" state information, and is therefore omitted from the body of the tests themselves.

In the rare cases where some local state is necessary (either for the test itself, or as an argument to the teardown action for some Context), test authors should use Harness.Test.Context.runWithLocalTestEnvironment. This function takes a type parameter for its local testEnvironment, which will be provided to both the teardown action specified in Context as well as the body of tests themselves.

Make local testEnvironment action

This refers to the function mkLocalTestEnvironment defined for Context:

mkLocalTestEnvironment :: TestEnvironment -> IO a

Its return value, IO a, matches the a of Context a: it is the additional local state that is required throughout the tests, in addition to the global TestEnvironment. Some tests, such as tests which check remote relationships, need to keep some state which is local to the context, but most tests do not need additional state, and define mkLocalTestEnvironment to be Harness.Test.Context.noLocalTestEnvironment.

This local state will be pass to the setup function and the teardown function. The teardown function is responsible to destroy the local state as well, if needed.

Setup action

A setup action is a function of type (TestEnvironment, a) -> IO () which is responsible for creating the environment for the test. It needs to:

1. Clear and reconfigure the metadata
2. Setup tables and insert values
3. Track tables, add relationships, permissions

etc.

These actions can be created by running POST requests against graphql-engine using Harness.GraphqlEngine.post_, or by running SQL requests against the backend using Backend.<backend>.run_.

Teardown action

The teardown action is another function of type (TestEnvironment, a) -> IO () which is responsible for removing the environment created by the test or setup, so that other tests can have a "clean slate" with no artifacts. The (TestEnvironment, a) parameter is constructed from the a parameter of the Context a: it is the local state that is passed throughout the tests.

This action is responsible for freeing acquired resources, and reverting all local modifications: dropping newly created tables, deleting custom functions, removing the changes made to the metadata, and so on.

These actions can be created by running POST requests against graphql-engine using Harness.GraphqlEngine.post_, or by running SQL requests against the backend using Backend.<backend>.run_.

Writing tests

Test should be written (or reachable from) tests :: SpecWith TestEnvironment, or tests :: SpecWith (TestEnvironment, Foo) for tests that use an additional local state.

A typical test will look similar to this:

  it "Where id=1" \testEnvironment ->
    shouldReturnYaml
      ( GraphqlEngine.postGraphql
          testEnvironment
          [graphql|
query {
  hasura_author(where: {id: {_eq: 1}}) {
    name
    id
  }
}
|]
      )
      [yaml|
data:
  hasura_author:
  - name: Author 1
    id: 1
|]

• it specifies the name of the test
• shouldReturnYaml creates an Expectation which does the following:
  • Runs a POST request against graphql-engine which can be specified using the graphql quasi-quoter.
  • Compares the response to an expected result which can be specified using the yaml quasi-quoter.

Note: these quasi-quoter can also perform string interpolation. See the relevant modules under the Harness.Quoter namespace.

Debugging

There are times when you would want to debug a test failure by playing around with the Hasura's Graphql engine or by inspecting the database. The default behavior of the test suite is to drop all the data and the tables onces the test suite finishes. To prevent that, you can modify your test module to prevent teardown. Example:

spec :: SpecWith TestEnvironment
spec =
  Context.run
    [ Context.Context
        { name = Context.Backend Context.MySQL,
          mkLocalTestEnvironment = Context.noLocalTestEnvironment,
          setup = Mysql.setup schema,
-         teardown = Mysql.teardown schema,
+         teardown = const $ pure (),
          customOptions = Nothing
        }]

Now re-run the particular test case again so that the local database is setup. You will still have access to that data once the test suite finishes running. Now based on what you want to, you can either run the Hasura's Graphql engine to debug this further or directly inspect the database using any of it's clients.

Style guide

Stick to Simple Haskell

This test suite should remain accessible to contributors who are new to Haskell and/or the GraphQL engine codebase. Consider the power-to-weight ratio of features, language extensions or abstractions before you introduce them. For example, try to fully leverage Haskell '98 or 2010 features before making use of more advanced ones.

Write small, atomic, autonomous specs

Small: Keep specs short and succinct wherever possible. Consider reorganising modules that grow much longer than ~200-300 lines of code.

For example: The TestGraphQLQueryBasic* pytest class was ported to the hspec suite as separate BasicFields, LimitOffset, Where, Ordering, Directives and Views specs.

Atomic: Each spec should test only one feature against the backends (or contexts) that support it. Each module should contain only the context setup and teardown, and the tests themselves. The database schema, test data, and feature expectations should be easy to reason about without navigating to different module.

For example: BasicFieldsSpec.hs

Autonomous: Each test should run independently of other tests, and not be dependent on the results of a previous test. Shared test state, where unavoidable, should be made explicit.

For example: Remote relationship tests explicitly require shared state.

Use the Harness.* hierarchy for common functions

Avoid functions or types in tests, other than calls to the Harness.* API.

Any supporting code should be in the Harness.* hierarchy and apply broadly to the test suites overall.

Troubleshooting

Database 'hasura' already exists. Choose a different database name. or schema "hasura" does not exist

This typically indicates persistent DB state between test runs. Try docker-compose down --volumes to delete the DBs and restart the containers.