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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
This commit is contained in:
Andrey Avtomonov
GitHub
parent
924868841d
commit
56985b7e09
548 changed files with 5048 additions and 2228 deletions
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@ -0,0 +1,178 @@
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import { describe, expect, it, vi } from 'vitest';
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import { createHttpSqlAnalysisPort } from '../../../src/context/sql-analysis/http-sql-analysis-port.js';
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describe('createHttpSqlAnalysisPort', () => {
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it('calls the SQL-analysis fingerprint endpoint and maps snake_case response fields', async () => {
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const requestJson = vi.fn(async () => ({
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fingerprint: 'fingerprint-template',
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normalized_sql: 'SELECT * FROM analytics.orders WHERE status = ?',
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tables_touched: ['analytics.orders'],
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literal_slots: [{ position: 1, type: 'string', example_value: 'paid' }],
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}));
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const port = createHttpSqlAnalysisPort({ baseUrl: 'http://python.test', requestJson });
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await expect(
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port.analyzeForFingerprint("SELECT * FROM analytics.orders WHERE status = 'paid'", 'postgres'),
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).resolves.toEqual({
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fingerprint: 'fingerprint-template',
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normalizedSql: 'SELECT * FROM analytics.orders WHERE status = ?',
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tablesTouched: ['analytics.orders'],
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literalSlots: [{ position: 1, type: 'string', exampleValue: 'paid' }],
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});
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expect(requestJson).toHaveBeenCalledWith('/api/sql/analyze-for-fingerprint', {
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sql: "SELECT * FROM analytics.orders WHERE status = 'paid'",
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dialect: 'postgres',
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});
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});
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it('preserves SQL-analysis parse errors in the mapped result', async () => {
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const requestJson = vi.fn(async () => ({
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fingerprint: '',
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normalized_sql: '',
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tables_touched: [],
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literal_slots: [],
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error: 'Invalid expression / Unexpected token',
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}));
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const port = createHttpSqlAnalysisPort({ baseUrl: 'http://python.test', requestJson });
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await expect(port.analyzeForFingerprint('SELECT * FROM WHERE', 'postgres')).resolves.toEqual({
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fingerprint: '',
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normalizedSql: '',
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tablesTouched: [],
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literalSlots: [],
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error: 'Invalid expression / Unexpected token',
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});
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});
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it('calls the SQL batch endpoint and maps snake_case response fields into a Map', async () => {
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const requestJson = vi.fn(async () => ({
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results: {
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orders: {
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tables_touched: ['public.orders', 'public.customers'],
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columns_by_clause: {
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select: ['status'],
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where: ['created_at'],
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join: ['customer_id', 'id'],
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},
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error: null,
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},
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broken: {
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tables_touched: [],
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columns_by_clause: {},
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error: 'Invalid expression / Unexpected token',
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},
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},
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}));
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const port = createHttpSqlAnalysisPort({ baseUrl: 'http://python.test', requestJson });
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await expect(
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port.analyzeBatch(
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[
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{ id: 'orders', sql: 'select status from public.orders' },
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{ id: 'broken', sql: 'select * from where' },
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],
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'postgres',
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),
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).resolves.toEqual(
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new Map([
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[
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'orders',
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{
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tablesTouched: ['public.orders', 'public.customers'],
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columnsByClause: {
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select: ['status'],
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where: ['created_at'],
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join: ['customer_id', 'id'],
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},
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error: null,
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},
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],
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[
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'broken',
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{
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tablesTouched: [],
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columnsByClause: {},
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error: 'Invalid expression / Unexpected token',
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},
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],
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]),
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);
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expect(requestJson).toHaveBeenCalledWith('/sql/analyze-batch', {
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dialect: 'postgres',
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items: [
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{ id: 'orders', sql: 'select status from public.orders' },
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{ id: 'broken', sql: 'select * from where' },
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],
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});
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});
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it('maps read-only SQL validation responses', async () => {
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const requests: Array<{ path: string; payload: Record<string, unknown> }> = [];
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const port = createHttpSqlAnalysisPort({
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baseUrl: 'http://127.0.0.1:8765',
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requestJson: async (path, payload) => {
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requests.push({ path, payload });
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return { ok: false, error: 'SQL contains read/write operation: Insert' };
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},
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});
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await expect(
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port.validateReadOnly('with x as (insert into t values (1)) select * from x', 'postgres'),
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).resolves.toEqual({
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ok: false,
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error: 'SQL contains read/write operation: Insert',
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});
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expect(requests).toEqual([
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{
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path: '/sql/validate-read-only',
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payload: {
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dialect: 'postgres',
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sql: 'with x as (insert into t values (1)) select * from x',
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},
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},
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]);
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});
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it('rejects malformed read-only validation responses', async () => {
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const port = createHttpSqlAnalysisPort({
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baseUrl: 'http://127.0.0.1:8765',
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requestJson: async () => ({ ok: 'yes' }),
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});
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await expect(port.validateReadOnly('select 1', 'postgres')).rejects.toThrow(
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'sql analysis response is missing boolean field ok',
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);
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});
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it('rejects malformed SQL batch responses instead of inventing defaults', async () => {
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const requestJson = vi.fn(async () => ({
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results: {
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orders: {
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tables_touched: ['public.orders'],
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columns_by_clause: { select: ['status'], where: [42] },
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error: null,
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},
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},
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}));
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const port = createHttpSqlAnalysisPort({ baseUrl: 'http://python.test', requestJson });
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await expect(port.analyzeBatch([{ id: 'orders', sql: 'select status from public.orders' }], 'postgres')).rejects
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.toThrow('sql analysis response is missing string[] field columns_by_clause.where');
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});
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it('rejects malformed daemon responses instead of inventing defaults', async () => {
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const requestJson = vi.fn(async () => ({
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fingerprint: 'abc',
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normalized_sql: 'SELECT ?',
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tables_touched: 'orders',
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literal_slots: [],
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}));
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const port = createHttpSqlAnalysisPort({ baseUrl: 'http://python.test', requestJson });
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await expect(port.analyzeForFingerprint('SELECT 1', 'postgres')).rejects.toThrow(
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'sql analysis response is missing string[] field tables_touched',
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);
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});
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});
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