ktx/packages/cli/test/context/sl/tools/sl-warehouse-validation.test.ts

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import { describe, expect, it, vi } from 'vitest';
test: split cli tests from source tree (#216) * feat(cli): define full warehouse dialect contract * test(cli): keep dialect edge tests focused * fix(cli): stabilize dialect contract foundation * refactor(connectors): own read-only query preparation * refactor(connectors): resolve dialects through registry * refactor(connectors): keep concrete dialect classes internal * chore(workspace): enforce dialect import boundary * refactor(cli): resolve relationship dialect at scan boundary * refactor(cli): use dialect display parsing for entity details * refactor(cli): use dialect display parsing for warehouse catalog * refactor(cli): use dialect SQL in relationship workflows * test(cli): verify solid dialect scan workflow closure * test: split cli tests from source tree * refactor(cli): standardize BigQuery scope listing * feat(sqlite): implement connector scope listing * test(connectors): cover required table listing * feat(cli): add warehouse driver registry * refactor(setup): route scope discovery through driver registry * refactor(cli): route local query execution through driver registry * refactor(historic-sql): route dialect support through driver registry * refactor(cli): test warehouse connections through driver registry * fix(cli): close driver registry type export gaps * Improve setup daemon diagnostics * refactor(setup): centralize rail-prefixed diagnostics + query-history fallback Extract errorMessage, writePrefixedLines, and flushPrefixedBufferedCommandOutput into clack.ts so the setup wizard, managed daemons, and embedding/agent steps share one rail-formatted writer. setup-databases.ts also adds a "disable query history and retry" option when the schema-context build fails and query history is the likely culprit, surfaced via a new failed-query-history-unavailable status. * fix(cli): carry catalog through the picker so BigQuery/Snowflake/SQL Server scope filters match The setup picker's KtxTableListEntry was a 2-level { schema, name }, so qualifiedTableId always wrote db.name into enabled_tables. When BigQuery, Snowflake, or SQL Server later ran fast ingest, their introspect step filtered the scope set with scopedTableNames(scope, { catalog: projectId|database, db }) — catalog was non-null on the introspect side but null in the scope refs, so every entry was rejected, the live-database adapter staged zero table files, and detect() failed with 'Adapter "live-database" did not recognize fetched source output'. Align the picker boundary with the canonical 3-level KtxTableRef: - Add catalog: string | null to KtxTableListEntry. - BigQuery/Snowflake/SQL Server listTables populate catalog from the resolved projectId / database; Postgres/MySQL/ClickHouse/SQLite set null. - qualifiedTableId emits catalog.schema.name when catalog is non-null (resolveEnabledTables already accepts the 3-part shape) and schemasFromEnabledTables now goes through parseDottedTableEntry so it recovers the schema correctly from both 2-part and 3-part entries. - Export parseDottedTableEntry from enabled-tables.ts (@internal) for picker reuse. Update listTables expectations in all seven connector tests and the setup / picker test fixtures. Add a picker regression test that covers the catalog-bearing round-trip (save + refine). * fix(cli): allow debug telemetry under opt-out env
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import { validateSingleSource } from '../../../../src/context/sl/tools/sl-warehouse-validation.js';
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function makeDeps(opts: { sourceYaml: string; executeQuery: ReturnType<typeof vi.fn> }) {
return {
semanticLayerService: {
readSourceFile: vi.fn().mockResolvedValue({ content: opts.sourceYaml, path: 'x' }),
isManifestBacked: vi.fn().mockResolvedValue(false),
listManifestSourceNames: vi.fn().mockResolvedValue([]),
loadSource: vi.fn().mockResolvedValue(null),
fix(context): merge overlay columns onto manifest columns by name (#94) * fix(context): merge overlay columns onto manifest columns by name composeOverlay was appending overlay columns to the manifest column list, producing duplicate entries when dbt/metabase overlays declared a column just to attach descriptions. The duplicates carried no `type`, so the pydantic SourceDefinition rejected them at semantic-query time and broke `ktx sl query` for every overlay-backed measure. Now overlay columns match base columns by name (case-insensitive): same-name entries merge onto the manifest (overlay fields win, type/role fall back to the base, descriptions merge per source key) and only new names append. * refactor(sl): split overlay columns from column_overrides and enforce TS/Python wire contract Overlay sources now have two distinct collections: `columns:` for computed columns (requiring `expr` + `type`) and `column_overrides:` for metadata patches to inherited manifest columns. Composing or loading an overlay that mixes the two — or references an unknown column — fails with a typed error. Introduce `ResolvedSemanticLayerSource` / `resolvedSourceSchema` / `toResolvedWire` as the strict shape sent to the Python engine, and add a schema contract test that diffs Zod against the Pydantic JSON schema dumped by `python -m semantic_layer dump-schema`. `SourceDefinition` is now `extra="forbid"` on the Python side. `loadAllSources` surfaces per-file load errors instead of swallowing them, so validation/query paths can report manifest shard parse failures. * fix(context): make scan description generation resilient and quiet A transient sampleTable failure during ingest used to take out every table in a connection: generateTableDescription returned a hardcoded 'Table not found' string into descriptions.ai, and KtxDescriptionGenerator was constructed without a logger, so the failure left no trail anywhere. - sampleTable / sampleColumn calls retry 3x with 200/400/800ms backoff, honouring KtxScanContext.signal via a new KtxAbortedError. - On retry exhaustion or missing capability, table generation falls back to a metadata-only prompt built from column name / native type / comment / rawDescriptions. The column path follows the same rule -- call the LLM when any of samples or rawDescriptions are available; skip only when both are absent. - Logger is now threaded from KtxScanContext into the generator. Failures emit structured KtxScanWarning entries (new description_fallback_used code, plus existing sampling_failed / enrichment_failed / connector_capability_missing). ktx scan groups warnings by code so a batch of identical failures collapses to one summary line plus sample. - Returns null on failure instead of the 'Table not found' sentinel; the manifest writer's existing guard already skips empty descriptions, so schema YAML no longer carries misleading text. SCAN_MANAGED_DESCRIPTION_KEYS already strips stale 'ai' on merge, so existing YAML clears on next run. Also suppress AI SDK v6 'system in messages' warning: pull system messages out of KtxMessageBuilder.wrapSimple's output via a new splitKtxSystemMessages helper and pass them top-level to generateText (preserves cacheControl providerOptions on the SystemModelMessage). Agent-runner's local splitSystemPromptMessages dedupes onto the shared helper. * test(docs): align examples-docs assertions with revamped docs PR #103 (setup/guide doc revamp) reworded several CLI examples and connection labels; the assertions in scripts/examples-docs.test.mjs still referenced the pre-revamp wording and were failing in CI on main. Update the regexes to match the post-revamp content: - drop the `--json` flag from the sl-query example expectation - move the `Driver:` / `Status: ok` probe to the connection reference, which is where that output now lives (driver id is lowercase `postgres`, not the display name `PostgreSQL`) - drop the obsolete `Install \`uv\`...` troubleshooting line - accept `<connectionId>` everywhere; the docs no longer use the hyphenated `<connection-id>` form - match the `warehouse` connection id used in the quickstart instead of the `postgres-warehouse` id only used in the README and setup ref * fix(sl): skip TS/Python schema contract test when uv is unavailable The TypeScript checks CI job does not install uv or Python, so the module-level `execFileSync('uv', ...)` in schemas.contract.test.ts threw ENOENT and failed the suite. Wrap the schema dump in a try/catch and guard the describe block with `describe.skipIf` so the test skips in environments without uv. Local dev and any CI job that has uv on PATH still runs the cross-language contract assertion.
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loadAllSources: vi.fn().mockResolvedValue({ sources: [], loadErrors: [] }),
validatePhysicalTableReferences: vi.fn().mockResolvedValue([]),
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} as never,
connections: {
executeQuery: opts.executeQuery,
getConnectionById: vi.fn().mockResolvedValue({ id: 'conn-1', name: 'conn-1', connectionType: 'bigquery' }),
listEnabledConnections: vi.fn().mockResolvedValue([]),
} as never,
configService: {} as never,
gitService: {} as never,
slSourcesRepository: { deleteByConnectionAndName: vi.fn().mockResolvedValue(undefined) } as never,
probeRowCount: 1,
};
}
describe('validateSingleSource warehouse dry-run', () => {
it('surfaces warehouse error when dry-run fails on unknown column', async () => {
const yaml = `name: fct_arr_delta
source_type: sql
sql: |
SELECT * FROM analytics.fct_arr_delta WHERE date_date < CURRENT_DATE()
grain: [date_date]
columns:
- name: date_date
type: time
measures:
- name: count_delta_events
expr: count(*)
joins: []
`;
const executeQuery = vi.fn().mockRejectedValue(new Error('Unrecognized name: date_date at [1:42]'));
const deps = makeDeps({ sourceYaml: yaml, executeQuery });
const result = await validateSingleSource(deps, 'conn-1', 'fct_arr_delta');
expect(result.errors.join('\n')).toMatch(/Unrecognized name: date_date/);
expect(result.errors.join('\n')).toMatch(/embedded sql dry-run failed/);
});
it('flags declared columns missing from the dry-run result', async () => {
const yaml = `name: fct_arr_delta
source_type: sql
sql: |
SELECT date, customer_id FROM analytics.fct_arr_delta
columns:
- name: date_date
type: time
- name: customer_id
type: string
measures:
- name: count_delta
expr: count(*)
joins: []
grain: [customer_id]
`;
const executeQuery = vi.fn().mockResolvedValue({
headers: ['date', 'customer_id'],
rows: [],
totalRows: 0,
error: null,
});
const deps = makeDeps({ sourceYaml: yaml, executeQuery });
const result = await validateSingleSource(deps, 'conn-1', 'fct_arr_delta');
expect(result.errors.join('\n')).toMatch(/declared columns absent from sql result — date_date/);
expect(result.errors.join('\n')).toMatch(/warehouse returned:/);
});
it('passes cleanly when dry-run succeeds and declared columns match', async () => {
const yaml = `name: lab_results
source_type: sql
sql: |
SELECT lab_order_id, admin_user_id FROM analytics.raw_lab_results
grain: [lab_order_id]
columns:
- name: lab_order_id
type: string
- name: admin_user_id
type: string
measures:
- name: count_lab_results
expr: count(lab_order_id)
joins: []
`;
const executeQuery = vi.fn().mockResolvedValue({
headers: ['lab_order_id', 'admin_user_id'],
rows: [],
totalRows: 0,
error: null,
});
const deps = makeDeps({ sourceYaml: yaml, executeQuery });
const result = await validateSingleSource(deps, 'conn-1', 'lab_results');
expect(result.errors).toEqual([]);
});
it('uses LIMIT 1 (not LIMIT 0) so runtime policies fire', async () => {
const yaml = `name: foo
source_type: sql
sql: |
SELECT a FROM analytics.bar
grain: [a]
columns:
- {name: a, type: string}
measures: []
joins: []
`;
const executeQuery = vi.fn().mockResolvedValue({ headers: ['a'], rows: [], totalRows: 0, error: null });
const deps = makeDeps({ sourceYaml: yaml, executeQuery });
await validateSingleSource(deps, 'conn-1', 'foo');
const probeSql = executeQuery.mock.calls[0][1] as string;
expect(probeSql).toMatch(/LIMIT 1\b/);
expect(probeSql).not.toMatch(/LIMIT 0\b/);
});
it('adds physical manifest errors for table-backed sources', async () => {
const yaml = `name: int_active_contract_arr
table: orbit_analytics.int_active_contract_arr
grain: [contract_id]
columns:
- {name: contract_id, type: string}
- {name: arr_cents, type: number}
measures:
- {name: arr, expr: sum(arr_cents)}
joins: []
`;
const executeQuery = vi.fn();
const deps = makeDeps({ sourceYaml: yaml, executeQuery }) as any;
deps.semanticLayerService.validatePhysicalTableReferences.mockResolvedValue([
'int_active_contract_arr.yaml: declared column(s) absent from physical table: arr_cents',
]);
const result = await validateSingleSource(deps, 'conn-1', 'int_active_contract_arr');
expect(result.errors).toContain(
'int_active_contract_arr.yaml: declared column(s) absent from physical table: arr_cents',
);
expect(executeQuery).not.toHaveBeenCalled();
});
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});