2026-05-10 23:12:26 +02:00
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import { describe, expect, it, vi } from 'vitest';
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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
2026-05-26 08:49:05 +02:00
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import { validateSingleSource } from '../../../../src/context/sl/tools/sl-warehouse-validation.js';
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2026-05-10 23:12:26 +02:00
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function makeDeps(opts: { sourceYaml: string; executeQuery: ReturnType<typeof vi.fn> }) {
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return {
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semanticLayerService: {
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readSourceFile: vi.fn().mockResolvedValue({ content: opts.sourceYaml, path: 'x' }),
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isManifestBacked: vi.fn().mockResolvedValue(false),
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listManifestSourceNames: vi.fn().mockResolvedValue([]),
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loadSource: vi.fn().mockResolvedValue(null),
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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.
2026-05-15 02:11:04 +02:00
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loadAllSources: vi.fn().mockResolvedValue({ sources: [], loadErrors: [] }),
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2026-05-12 16:56:58 -04:00
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validatePhysicalTableReferences: vi.fn().mockResolvedValue([]),
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2026-05-10 23:12:26 +02:00
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} as never,
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connections: {
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executeQuery: opts.executeQuery,
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getConnectionById: vi.fn().mockResolvedValue({ id: 'conn-1', name: 'conn-1', connectionType: 'bigquery' }),
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listEnabledConnections: vi.fn().mockResolvedValue([]),
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} as never,
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configService: {} as never,
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gitService: {} as never,
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slSourcesRepository: { deleteByConnectionAndName: vi.fn().mockResolvedValue(undefined) } as never,
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probeRowCount: 1,
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};
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}
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describe('validateSingleSource warehouse dry-run', () => {
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it('surfaces warehouse error when dry-run fails on unknown column', async () => {
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const yaml = `name: fct_arr_delta
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source_type: sql
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sql: |
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SELECT * FROM analytics.fct_arr_delta WHERE date_date < CURRENT_DATE()
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grain: [date_date]
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columns:
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- name: date_date
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type: time
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measures:
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- name: count_delta_events
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expr: count(*)
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joins: []
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`;
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const executeQuery = vi.fn().mockRejectedValue(new Error('Unrecognized name: date_date at [1:42]'));
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const deps = makeDeps({ sourceYaml: yaml, executeQuery });
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const result = await validateSingleSource(deps, 'conn-1', 'fct_arr_delta');
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expect(result.errors.join('\n')).toMatch(/Unrecognized name: date_date/);
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expect(result.errors.join('\n')).toMatch(/embedded sql dry-run failed/);
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});
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it('flags declared columns missing from the dry-run result', async () => {
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const yaml = `name: fct_arr_delta
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source_type: sql
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sql: |
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SELECT date, customer_id FROM analytics.fct_arr_delta
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columns:
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- name: date_date
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type: time
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- name: customer_id
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type: string
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measures:
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- name: count_delta
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expr: count(*)
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joins: []
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grain: [customer_id]
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`;
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const executeQuery = vi.fn().mockResolvedValue({
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headers: ['date', 'customer_id'],
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rows: [],
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totalRows: 0,
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error: null,
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});
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const deps = makeDeps({ sourceYaml: yaml, executeQuery });
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const result = await validateSingleSource(deps, 'conn-1', 'fct_arr_delta');
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expect(result.errors.join('\n')).toMatch(/declared columns absent from sql result — date_date/);
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expect(result.errors.join('\n')).toMatch(/warehouse returned:/);
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});
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it('passes cleanly when dry-run succeeds and declared columns match', async () => {
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const yaml = `name: lab_results
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source_type: sql
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sql: |
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SELECT lab_order_id, admin_user_id FROM analytics.raw_lab_results
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grain: [lab_order_id]
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columns:
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- name: lab_order_id
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type: string
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- name: admin_user_id
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type: string
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measures:
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- name: count_lab_results
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expr: count(lab_order_id)
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joins: []
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`;
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const executeQuery = vi.fn().mockResolvedValue({
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headers: ['lab_order_id', 'admin_user_id'],
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rows: [],
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totalRows: 0,
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error: null,
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});
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const deps = makeDeps({ sourceYaml: yaml, executeQuery });
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const result = await validateSingleSource(deps, 'conn-1', 'lab_results');
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expect(result.errors).toEqual([]);
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});
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it('uses LIMIT 1 (not LIMIT 0) so runtime policies fire', async () => {
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const yaml = `name: foo
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source_type: sql
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sql: |
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SELECT a FROM analytics.bar
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grain: [a]
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columns:
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- {name: a, type: string}
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measures: []
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joins: []
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`;
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const executeQuery = vi.fn().mockResolvedValue({ headers: ['a'], rows: [], totalRows: 0, error: null });
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const deps = makeDeps({ sourceYaml: yaml, executeQuery });
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await validateSingleSource(deps, 'conn-1', 'foo');
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const probeSql = executeQuery.mock.calls[0][1] as string;
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expect(probeSql).toMatch(/LIMIT 1\b/);
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expect(probeSql).not.toMatch(/LIMIT 0\b/);
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});
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2026-05-12 16:56:58 -04:00
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it('adds physical manifest errors for table-backed sources', async () => {
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const yaml = `name: int_active_contract_arr
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table: orbit_analytics.int_active_contract_arr
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grain: [contract_id]
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columns:
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- {name: contract_id, type: string}
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- {name: arr_cents, type: number}
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measures:
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- {name: arr, expr: sum(arr_cents)}
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joins: []
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`;
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const executeQuery = vi.fn();
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const deps = makeDeps({ sourceYaml: yaml, executeQuery }) as any;
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deps.semanticLayerService.validatePhysicalTableReferences.mockResolvedValue([
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'int_active_contract_arr.yaml: declared column(s) absent from physical table: arr_cents',
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]);
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const result = await validateSingleSource(deps, 'conn-1', 'int_active_contract_arr');
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expect(result.errors).toContain(
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'int_active_contract_arr.yaml: declared column(s) absent from physical table: arr_cents',
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);
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expect(executeQuery).not.toHaveBeenCalled();
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});
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2026-05-10 23:12:26 +02:00
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});
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