ktx/packages/cli/test/context/sql-analysis/http-sql-analysis-port.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

178 lines
5.9 KiB
TypeScript

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