ktx/packages/cli/test/context/ingest/adapters/looker/evidence-documents.test.ts
Andrey Avtomonov 56985b7e09
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

188 lines
6.7 KiB
TypeScript

import { mkdir, mkdtemp, readFile, rm, writeFile } from 'node:fs/promises';
import { tmpdir } from 'node:os';
import { dirname, join } from 'node:path';
import { afterEach, beforeEach, describe, expect, it } from 'vitest';
import { getLookerTriageSignals, writeLookerEvidenceDocuments } from '../../../../../src/context/ingest/adapters/looker/evidence-documents.js';
async function writeJson(root: string, relPath: string, value: unknown): Promise<void> {
const target = join(root, relPath);
await mkdir(dirname(target), { recursive: true });
await writeFile(target, `${JSON.stringify(value, null, 2)}\n`, 'utf-8');
}
async function readJson<T>(root: string, relPath: string): Promise<T> {
return JSON.parse(await readFile(join(root, relPath), 'utf-8')) as T;
}
describe('Looker evidence documents', () => {
let stagedDir: string;
beforeEach(async () => {
stagedDir = await mkdtemp(join(tmpdir(), 'looker-evidence-docs-'));
await writeJson(stagedDir, 'explores/b2b/sales_pipeline.json', {
modelName: 'b2b',
exploreName: 'sales_pipeline',
label: 'Sales Pipeline',
description: 'Pipeline analysis explore.',
fields: {
dimensions: [
{ name: 'opportunities.stage', label: 'Stage', type: 'string', sql: '${TABLE}.stage', description: null },
],
measures: [
{
name: 'opportunities.arr',
label: 'ARR',
type: 'sum',
sql: '${TABLE}.arr',
description: 'Annual recurring revenue.',
},
],
},
joins: [{ name: 'accounts', type: 'left_outer', relationship: 'many_to_one' }],
});
await writeJson(stagedDir, 'dashboards/10.json', {
lookerId: '10',
title: 'Sales Pipeline Overview',
description: 'Executive dashboard for open pipeline ARR.',
folderId: '7',
ownerId: '3',
updatedAt: '2026-04-30T10:00:00.000Z',
tiles: [
{
id: '100',
title: 'Open Pipeline ARR',
lookId: null,
query: {
model: 'b2b',
view: 'sales_pipeline',
fields: ['opportunities.arr', 'opportunities.stage'],
filters: { 'opportunities.stage': 'open' },
sorts: ['opportunities.arr desc'],
limit: '500',
},
},
],
});
await writeJson(stagedDir, 'looks/20.json', {
lookerId: '20',
title: 'Active Opportunity Pipeline',
description: 'Saved Look for active opportunity pipeline review.',
folderId: '7',
ownerId: '3',
updatedAt: '2026-04-30T11:00:00.000Z',
query: {
model: 'b2b',
view: 'sales_pipeline',
fields: ['opportunities.arr'],
filters: { 'opportunities.stage': 'open' },
sorts: [],
limit: '500',
},
});
await writeJson(stagedDir, 'signals/dashboard_usage.json', [
{
contentId: '10',
queryCount30d: 80,
uniqueUsers30d: 12,
lastRunAt: '2026-04-30T09:00:00.000Z',
topUsers: ['3'],
},
]);
await writeJson(stagedDir, 'signals/look_usage.json', [
{
contentId: '20',
queryCount30d: 2,
uniqueUsers30d: 1,
lastRunAt: '2026-04-29T09:00:00.000Z',
topUsers: ['3'],
},
]);
await writeJson(stagedDir, 'signals/scheduled_plans.json', [
{ contentId: '10', contentType: 'dashboard', isScheduled: true, scheduleCount: 2, recipientCount: 5 },
]);
await writeJson(stagedDir, 'signals/favorites.json', [
{ contentId: '10', contentType: 'dashboard', favoriteCount: 4 },
]);
});
afterEach(async () => {
await rm(stagedDir, { recursive: true, force: true });
});
it('writes indexable metadata and markdown for explores, dashboards, and Looks', async () => {
await writeLookerEvidenceDocuments(stagedDir);
await expect(readJson(stagedDir, 'evidence/explores/b2b/sales_pipeline/metadata.json')).resolves.toMatchObject({
objectType: 'looker_explore',
id: 'looker:explore:b2b.sales_pipeline',
title: 'Sales Pipeline',
path: 'Looker / Explores / b2b.sales_pipeline',
properties: {
rawPath: 'explores/b2b/sales_pipeline.json',
modelName: 'b2b',
exploreName: 'sales_pipeline',
},
});
await expect(readJson(stagedDir, 'evidence/dashboards/10/metadata.json')).resolves.toMatchObject({
objectType: 'looker_dashboard',
id: 'looker:dashboard:10',
title: 'Sales Pipeline Overview',
path: 'Looker / Dashboards / Sales Pipeline Overview',
lastEditedAt: '2026-04-30T10:00:00.000Z',
properties: {
rawPath: 'dashboards/10.json',
lookerId: '10',
},
});
await expect(readJson(stagedDir, 'evidence/looks/20/metadata.json')).resolves.toMatchObject({
objectType: 'looker_look',
id: 'looker:look:20',
title: 'Active Opportunity Pipeline',
path: 'Looker / Looks / Active Opportunity Pipeline',
properties: {
rawPath: 'looks/20.json',
lookerId: '20',
},
});
const dashboardMarkdown = await readFile(join(stagedDir, 'evidence/dashboards/10/page.md'), 'utf-8');
expect(dashboardMarkdown).toContain('# Sales Pipeline Overview');
expect(dashboardMarkdown).toContain('Executive dashboard for open pipeline ARR.');
expect(dashboardMarkdown).toContain('## Tile: Open Pipeline ARR');
expect(dashboardMarkdown).toContain('- model: b2b');
expect(dashboardMarkdown).toContain('- explore: sales_pipeline');
expect(dashboardMarkdown).toContain('- opportunities.stage = open');
expect(dashboardMarkdown).not.toContain('80');
expect(dashboardMarkdown).not.toContain('queryCount30d');
expect(dashboardMarkdown).not.toContain('recipient');
expect(dashboardMarkdown).not.toContain('favorite');
expect(dashboardMarkdown).not.toContain('owner');
});
it('returns usage-aware triage signals without exposing usage as document prose', async () => {
await writeLookerEvidenceDocuments(stagedDir);
await expect(getLookerTriageSignals(stagedDir, 'looker:dashboard:10')).resolves.toEqual({
objectType: 'looker_dashboard',
propertyHints: {
contentType: 'dashboard',
queryCount30d: '80',
uniqueUsers30d: '12',
isScheduled: 'true',
favoriteCount: '4',
},
lastEditedAt: '2026-04-30T10:00:00.000Z',
});
await expect(getLookerTriageSignals(stagedDir, 'looker:look:20')).resolves.toEqual({
objectType: 'looker_look',
propertyHints: {
contentType: 'look',
queryCount30d: '2',
uniqueUsers30d: '1',
isScheduled: 'false',
favoriteCount: '0',
},
lastEditedAt: '2026-04-30T11:00:00.000Z',
});
});
});