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test infrastructure is complicated because some tests are meant to be run once, and some tests are meant to be run once for each dialect, or once for each dialect from a set of dialects. Work is happening to clean this up and clarify how to deal with ","maintainers":[{"name":"malloy-lang-user","email":"bporterfield@google.com"},{"name":"gmaden","email":"maden@google.com"},{"name":"scullin","email":"scullin@scullinsteel.com"},{"name":"mtoy","email":"mtoy@malloydata.org"},{"name":"ben-malloy","email":"ben@malloydata.org"}],"readme":"## Tests\nThe test infrastructure is complicated because some tests are meant to be run once, and some tests are meant to be run once for each dialect, or once for each dialect from a set of dialects. Work is happening to clean this up and clarify how to deal with this.  \n  \nAt one time you could run `npm run test`  and all tests would run against all databases. The number of dialects has grown so that this is no longer feasible. If you have made changes and want general assurance that your changes might be safe, run `npm run test-duckdb` which runs the full test suite, but only against the DuckDB database which is fast and local.  \n  \nIf you have the credentials and the test server set up, there is an `npm run ci-DIALECTNAME` test for each dialect which will run just the portion of the test suite which communicates with the database.  \n  \nPushing A PR will require it to pass CI for all dialects.  \n  \nIf you have a multi-dialect test (such as the ones in `test/src/databases/all`) most of the time a developer will set up one database to test against when something is broken (commonly duckdb, but it could be anything where a server is available) and the command to run that one test file is ..  \n  \n`MALLOY_DATABASE=duckdb npx jest test/src/databases/all/MY_FILE.spec.ts`  \n  \n_(another common setup is to set the environment variable `MALLOY_DATABASE=duckdb` before launching VS Code, and then running tests inside the IDE with the \"JestRunner\" extension will pick that up and run the tests against only that dialect)_\n\n# Building test database for DuckDB\n\n1. At top-level, run `sh test/duckdb/load_test_data.sh`\n2. A file called `duckdb_test.db` should be created in the test/data/duckdb folder - tests will automatically look there.\n\n# Starting other database servers\nMany other dialects have scripts  \n* `test/DIALECT/DIALECTstart.sh`*  \n* `test/DIALECT/DIALECTstop.sh`*  \n  \nWhich will spin up or down an instance of a server for that dialect loaded with the correct test database. With the correct hidden knowledge, you can use these to test any supported dialect locally. Not all people have access to all the hidden knowledge. This is an area of active concern.\n\n# Using the test matchers\n\nThe test infrastructure is exported from `@malloydata/malloy/test`. Import matchers to register them with Jest:\n\n```typescript\nimport '@malloydata/malloy/test/matchers';\nimport {mkTestModel, TV} from '@malloydata/malloy/test';\n```\n\n## Creating test data with mkTestModel\n\nUse `mkTestModel` to create in-memory test tables with type-safe data:\n\n```typescript\nconst tm = mkTestModel(runtime, {\n  users: [\n    {id: 1, name: 'alice', active: true},\n    {id: 2, name: 'bob', active: false},\n  ],\n});\n\nawait expect('run: users -> { select: * }').toMatchResult(tm, {name: 'alice'});\n```\n\n### Type hints with TV namespace\n\nMost types are inferred, but some need explicit hints:\n\n```typescript\nconst tm = mkTestModel(runtime, {\n  data: [\n    {\n      count: 42,              // inferred as integer\n      price: TV.float(19.99), // explicit float\n      created: TV.date('2024-01-15'),\n      updated: TV.timestamp('2024-01-15T10:30:00Z'),\n      nothing: TV.int(null),  // typed null\n    },\n  ],\n});\n```\n\n## Result matchers\n\n### toMatchResult - partial matching\n\nChecks that expected fields match. Actual rows can have extra fields. Extra rows are allowed.\n\n```typescript\n// Single row - just checks first row has matching fields\nawait expect('run: users -> { select: * }').toMatchResult(tm, {name: 'alice'});\n\n// Multiple rows - variadic arguments\nawait expect('run: users -> { select: * }').toMatchResult(tm,\n  {name: 'alice'},\n  {name: 'bob'}\n);\n\n// Empty match {} checks at least one row exists\nawait expect('run: users -> { select: * }').toMatchResult(tm, {});\n```\n\n### toMatchRows - partial fields, exact row count\n\nLike `toMatchResult` but requires exactly the specified number of rows:\n\n```typescript\n// Must have exactly 2 rows\nawait expect('run: users -> { select: * }').toMatchRows(tm, [\n  {name: 'alice'},\n  {name: 'bob'},\n]);\n```\n\n### toEqualResult - exact matching\n\nRequires exact field match (no extra fields) and exact row count:\n\n```typescript\nawait expect('run: users -> { select: name }').toEqualResult(tm, [\n  {name: 'alice'},\n  {name: 'bob'},\n]);\n```\n\n## Schema-aware matching\n\nThe matchers use schema information for intelligent comparisons:\n\n```typescript\n// Dates - plain strings work for date fields\nawait expect(query).toMatchResult(tm, {\n  birth_date: '2024-01-15',  // matches date field automatically\n});\n\n// Timestamps - ISO strings or Date objects\nawait expect(query).toMatchResult(tm, {\n  created_at: '2024-01-15T10:30:00.000Z',\n});\n```\n\n## Nested data with toMatchPaths\n\nFor queries with `nest:`, use `toMatchPaths` to navigate nested arrays: This is useful when a query returns a long nested array of records and you only care about the value of the first record.\n\n```typescript\nawait expect(`\n  run: src -> { nest: by_state is {...} }\n`).toMatchPaths(tm, {\n  'by_state.state': 'TX',\n  'by_state.count': 1845,\n});\n```\n\n## Reading failure output\n\n### Data differences\n\nWhen tests fail, you see a `DATA DIFFERENCES` section showing actual vs expected:\n\n```\nDATA DIFFERENCES\n  Expected 3 rows, got 2\n  0: { id: 1, name: 'alice' }        <- green (matched)\n  1! { id: 2, name: 'bob' }          <- red (field mismatch)\n    Expected age: 99\n  2! (missing)                        <- red\n    Expected: { name: 'charlie' }\n```\n\n- Matched rows use `:` and are shown in green\n- Mismatched rows use `!` and are shown in red with expected values indented below\n- Extra rows use `!` and are shown in red\n- Missing rows use `!` and show what was expected\n\nThe `!` marker makes it easy to identify problems even in non-colored output.\n\n### Bad Malloy Code\n\nSyntax errors show the query with a `!!!!!` marker at the error:\n\n```\nError in query compilation\n    |\n    |         rug: duckdb.sql(\"\"\"\n!!!!!         ^ no viable alternative at input 'rug'\n    |           SELECT 42 as num\n    |         \"\"\")\n    |\n```\n\n## Debugging with # test.debug\n\nAdd `# test.debug` to force a test to fail and print the result data:\n\n```typescript\nawait expect(`\n  # test.debug\n  run: users -> { select: * }\n`).toMatchResult(tm, {name: 'alice'});\n```\n\nOutput:\n```\nTest forced failure (# test.debug)\nResult: [ { id: 1, name: 'alice' }, { id: 2, name: 'bob' } ]\n```\n\nThis is useful when developing tests to see what data is actually returned.\n\n## Logging SQL with MALLOY_LOG_SQL\n\nSet the `MALLOY_LOG_SQL` environment variable to log the generated SQL to the console before each query run by the test matchers (`toMatchResult`, `toMatchRows`, `toEqualResult`, `toMatchPaths`):\n\n```sh\nMALLOY_LOG_SQL=1 npx jest test/src/databases/all/expr.spec.ts\n```\n\nThis is useful for debugging SQL generation issues without modifying test code.\n","readmeFilename":"README.md"}