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* 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
51 lines
2.1 KiB
TypeScript
51 lines
2.1 KiB
TypeScript
import { mkdir, mkdtemp, rm, writeFile } from 'node:fs/promises';
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import { tmpdir } from 'node:os';
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import { join } from 'node:path';
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import { afterEach, beforeEach, describe, expect, it } from 'vitest';
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import { detectMetricFlowStagedDir } from '../../../../../src/context/ingest/adapters/metricflow/detect.js';
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async function touch(stagedDir: string, relPath: string, body = ''): Promise<void> {
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const abs = join(stagedDir, relPath);
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await mkdir(join(abs, '..'), { recursive: true });
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await writeFile(abs, body, 'utf-8');
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}
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describe('detectMetricFlowStagedDir', () => {
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let stagedDir: string;
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beforeEach(async () => {
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stagedDir = await mkdtemp(join(tmpdir(), 'mf-detect-'));
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});
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afterEach(async () => {
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await rm(stagedDir, { recursive: true, force: true });
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});
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it('returns true when any YAML has top-level semantic_models:', async () => {
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await touch(stagedDir, 'models/a.yml', 'semantic_models:\n - {name: a, model: x, measures: []}\n');
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expect(await detectMetricFlowStagedDir(stagedDir)).toBe(true);
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});
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it('returns true when any YAML has top-level metrics:', async () => {
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await touch(stagedDir, 'metrics/m.yaml', 'metrics:\n - {name: m, type: simple, type_params: {measure: x}}\n');
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expect(await detectMetricFlowStagedDir(stagedDir)).toBe(true);
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});
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it('returns false for a directory with only dbt_project.yml', async () => {
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await touch(stagedDir, 'dbt_project.yml', 'name: my_proj\nversion: "1.0.0"\n');
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expect(await detectMetricFlowStagedDir(stagedDir)).toBe(false);
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});
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it('returns false for an empty directory', async () => {
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expect(await detectMetricFlowStagedDir(stagedDir)).toBe(false);
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});
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it('returns false for only broken YAML', async () => {
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await touch(stagedDir, 'broken.yml', '{ not: valid :::');
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expect(await detectMetricFlowStagedDir(stagedDir)).toBe(false);
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});
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it('ignores non-YAML files and returns false when no YAML qualifies', async () => {
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await touch(stagedDir, 'readme.md', '# readme');
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await touch(stagedDir, 'script.py', 'print("hi")');
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expect(await detectMetricFlowStagedDir(stagedDir)).toBe(false);
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});
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});
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