ktx/packages/cli/test/context/scan/data-dictionary.test.ts

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import { describe, expect, it } from 'vitest';
import {
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defaultKtxDataDictionarySettings,
isKtxDataDictionaryCandidate,
shouldKtxSampleColumnForDictionary,
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
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} from '../../../src/context/scan/data-dictionary.js';
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const defaultPatterns = defaultKtxDataDictionarySettings.excludePatterns;
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describe('KTX scan data dictionary policy', () => {
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it('includes text-like and boolean categorical types', () => {
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expect(isKtxDataDictionaryCandidate('varchar(50)', 'status', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('VARCHAR', 'category', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('text', 'region', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('string', 'payment_method', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('nvarchar(100)', 'tier', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('enum', 'status', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('boolean', 'active', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('bool', 'verified', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('character varying(50)', 'region', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('character(1)', 'flag', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('ntext', 'category', defaultPatterns)).toBe(true);
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});
it('excludes non-categorical primitive types', () => {
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expect(isKtxDataDictionaryCandidate('integer', 'count', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('bigint', 'total', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('timestamp', 'created', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('date', 'birth', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('numeric', 'amount', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('decimal(10,2)', 'price', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('float', 'rate', defaultPatterns)).toBe(false);
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});
it('excludes configured high-cardinality or sensitive name patterns', () => {
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expect(isKtxDataDictionaryCandidate('varchar', 'user_id', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('varchar', 'session_uuid', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('varchar', 'api_key', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('varchar', 'password_hash', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('varchar', 'auth_token', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('varchar', 'id', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('varchar', 'created_at', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('varchar', 'birth_date', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('text', 'description', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('text', 'email_body', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('varchar', 'image_url', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('varchar', 'email', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('varchar', 'phone_number', defaultPatterns)).toBe(false);
expect(isKtxDataDictionaryCandidate('varchar', 'street_address', defaultPatterns)).toBe(false);
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});
it('keeps business categorical names eligible', () => {
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expect(isKtxDataDictionaryCandidate('varchar', 'status', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('varchar', 'region', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('varchar', 'country', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('varchar', 'payment_method', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('varchar', 'currency', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('varchar', 'plan', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('varchar', 'category', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('varchar', 'tier', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('varchar', 'gender', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('varchar', 'language', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('varchar', 'order_type', defaultPatterns)).toBe(true);
expect(isKtxDataDictionaryCandidate('varchar', 'order_status', defaultPatterns)).toBe(true);
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});
it('respects host-provided exclusion patterns and skips invalid regex patterns', () => {
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expect(isKtxDataDictionaryCandidate('varchar', 'company_size', ['company'])).toBe(false);
expect(isKtxDataDictionaryCandidate('varchar', 'status', ['company'])).toBe(true);
expect(isKtxDataDictionaryCandidate('varchar', 'status', ['[invalid', '(unclosed'])).toBe(true);
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});
it('skips columns that already have persisted dictionary state', () => {
expect(
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shouldKtxSampleColumnForDictionary({
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columnType: 'varchar',
columnName: 'status',
sampleValues: ['paid'],
cardinality: null,
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settings: defaultKtxDataDictionarySettings,
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}),
).toEqual({ sample: false, reason: 'already_populated' });
expect(
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shouldKtxSampleColumnForDictionary({
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columnType: 'varchar',
columnName: 'empty_status',
sampleValues: null,
cardinality: 0,
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settings: defaultKtxDataDictionarySettings,
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}),
).toEqual({ sample: false, reason: 'empty_column' });
expect(
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shouldKtxSampleColumnForDictionary({
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columnType: 'varchar',
columnName: 'customer_name',
sampleValues: null,
cardinality: 300,
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settings: defaultKtxDataDictionarySettings,
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}),
).toEqual({ sample: false, reason: 'high_cardinality' });
expect(
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shouldKtxSampleColumnForDictionary({
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columnType: 'varchar',
columnName: 'status',
sampleValues: null,
cardinality: null,
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settings: defaultKtxDataDictionarySettings,
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}),
).toEqual({ sample: true });
});
});