- Add AS _cnt alias to COUNT(*) subquery (BQ Standard SQL requires it)
- Catch ImportError in _get_bq_client() and raise RemoteQueryError
so API endpoint returns proper 400 instead of 500
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- _reattach_remote_extensions: query table_catalog instead of table_schema
(DuckDB ATTACHed databases use table_catalog for the alias)
- _query_hybrid: forward --limit flag to RemoteQueryEngine.max_result_rows
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- cli/commands/query.py: --stdin mode now reads register_bq from the
JSON payload and merges it into the register_bq option list, matching
the documented {"register_bq": {...}, "sql": "..."} contract.
- src/remote_query.py: add _validate_bq_sql() with a narrower blocklist
(writes only); register_bq() now calls _validate_bq_sql() so legitimate
BQ operations like INFORMATION_SCHEMA, CALL, IMPORT are not blocked.
The final DuckDB execute() path still uses the full _validate_sql().
- tests/test_remote_query.py: add TestValidateBqSql covering allowed
INFORMATION_SCHEMA queries and blocked write operations.
Add _reattach_remote_extensions() helper that reads _remote_attach
tables from attached extract.duckdb files and LOADs the corresponding
DuckDB extensions, so BigQuery and other remote views resolve correctly
in read-only analytics connections.
- Validate view names with _SAFE_IDENTIFIER regex and check path traversal in _initialize_duckdb()
- find_by_table() and get_table_map() now also search the tables[] array field
- Add POST /api/admin/metrics/import endpoint for YAML file upload
- Replace generic except in _connect_to_instance() with specific HTTPStatusError/TimeoutException handlers
- Generate .claude/settings.json in _generate_claude_md() bootstrap
- Update test_find_by_table and test_get_table_map to cover tables[] array lookups
- Add test_import_metrics_yaml in TestMetricsAPI
Adds YAML-based bulk import/export to MetricRepository, supporting
list-wrapped and plain-dict YAML formats, table→table_name field
mapping, and sql_by_* → sql_variants collection (and reverse on export).
All 24 tests pass.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Implements MetricRepository following the table_registry pattern — raw SQL,
dict returns, ON CONFLICT upsert, and json.dumps for sql_variants/validation.
Includes 18 tests covering create, read, list, update, delete, find_by_table,
find_by_synonym, and get_table_map.
Add SCHEMA_VERSION = 4, _V3_TO_V4_MIGRATIONS list, and if current < 4 block
in _ensure_schema(). Both new tables are also added to _SYSTEM_SCHEMA for
fresh installs. Tests cover fresh install, all columns, and v3→v4 migration path.
- CalVer retry loop now exits with error if all 5 attempts fail
(prevents pushing Docker image with unclaimed version tag)
- discover_tables endpoint reads data_source.keboola.url (consistent
with configure_instance and _discover_and_register_tables)
- Pre-migration snapshot flushes WAL via CHECKPOINT before copying
and copies .wal file if it still exists after flush
663 tests pass.
- services/telegram_bot/config.py: NOTIFICATIONS_DIR now uses DATA_DIR fallback
- src/profiler.py: DATA_DIR now uses main DATA_DIR env var instead of PROFILER_DATA_DIR
- services/telegram_bot/dispatch.py: WS_GATEWAY_SOCKET_PATH now uses WS_GATEWAY_SOCKET env var
- Add close_system_db() function in src/db.py to cleanly close shared DB connection
- Add lifespan context manager in app/main.py to trigger shutdown on app exit
- Integrate lifespan into FastAPI app initialization
- All API tests pass (77/77)
DuckDB has used WAL by default since v0.8, so this pragma is not
valid DuckDB syntax. Removed obsolete try-except block that attempted
to enable WAL on system database initialization.
Adds _SAFE_IDENTIFIER regex guard before ATTACHing extract.duckdb files in the
read-only analytics connection, matching the same fix already applied in the
orchestrator. Adds test coverage for malicious directory names.
Add _atomic_swap_db helper that removes stale WAL files before and after
moving the temp DuckDB into place. Apply CHECKPOINT before close in both
orchestrator and Keboola extractor so DuckDB flushes WAL before the swap.
Expand blocked keywords to cover parquet_scan, read_csv_auto, query_table,
iceberg_scan, delta_scan, call, URL schemes (http/https/s3/gcs), and
additional file-scan functions. Set enable_external_access=false on the
non-read-only analytics connection path. Add three new tests covering
parquet_scan, read_csv_auto, and query_table blocking.
Adds _validate_identifier() with ^[a-zA-Z_][a-zA-Z0-9_]{0,63}$ regex and
applies it to source_name (directory names), table_name (_meta rows), and
alias/extension (_remote_attach rows) before any SQL interpolation.
Adds two tests covering SQL-injection directory names and malicious _meta entries.
_do_rebuild_source was creating a fresh temp DB with only one source,
then atomically replacing analytics.duckdb — wiping views from every
other source. Now it delegates to _do_rebuild so all extract dirs are
re-attached in a single pass.
Adds test_rebuild_source_preserves_other_sources to guard the regression.
BigQuery extension handles auth via GOOGLE_APPLICATION_CREDENTIALS env var,
so _remote_attach uses empty token_env. Orchestrator now supports both
token-based (Keboola) and env-based (BigQuery) authentication modes.
Extractors with remote tables now write a _remote_attach table into
extract.duckdb so the orchestrator can re-ATTACH external extensions
at query time. The mechanism is source-agnostic — any connector can use it.
- Keboola extractor writes _remote_attach + creates views on kbc.*
- Orchestrator reads _remote_attach, installs extension, reads token from env
- Graceful degradation: missing token → warning, local tables still work
Three-pronged fix for DuckDB lock conflicts:
1. WAL mode on system.duckdb — enables concurrent readers + writer
2. Sync trigger runs extractor as subprocess (not background task) —
separate process = separate DuckDB connections, no lock conflict
3. Both extractor and orchestrator write to .tmp then atomic rename —
avoids lock conflict with API reads on extract.duckdb/analytics.duckdb
Fixes#9 permanently.
Fixes#9 — background sync tasks could not access system.duckdb
because FastAPI held an exclusive lock. Now uses single shared
connection per DATA_DIR with cursor() for thread safety.
Schema v3: add is_public column to table_registry (default true).
src/rbac.py: can_access_table() checks admin bypass, public flag,
explicit permissions, wildcard bucket permissions.
API enforcement:
- manifest: filters tables by user access
- download: 403 if no access
- catalog: filters table list
- query: validates referenced tables against allowed list
New admin permissions API (/api/admin/permissions) for grant/revoke.
28 access control tests + 733 total tests passing.
New src/rbac.py: Role enum, hierarchy, get_user_role(), has_role(),
is_admin(), is_km_admin(), has_dataset_access(), set_user_role().
webapp/auth.py: admin_required + km_admin_required now use DuckDB
roles instead of Linux groups (pwd.getpwnam + sudo/data-ops check).
app/auth/dependencies.py: imports Role from src/rbac.py (single source).
11 RBAC tests passing.
- SyncSettingsRepository + DatasetPermissionRepository with RBAC
- Script deploy/run/undeploy API with import sandboxing
- User sync settings API with permission checks
- 4 CLI skills (connectors, security, notifications, corporate-memory)
- Kamal production + staging configs
- GitHub Actions CI + deploy workflows
- 91 total tests passing
Same issue as config.py - profiler's TableInfo and parser required
primary_key and sync_strategy, breaking auto-profile after sync
when daily_deal_traffic (remote-only) is in config.
Remote-only tables (query_mode="remote") like daily_deal_traffic
don't need primary_key or sync_strategy. The parser used hard
lookups (table_data["primary_key"]) causing KeyError and breaking
all data sync since 2026-03-21.
Changes:
- TableConfig: default primary_key="" and sync_strategy="none"
- Parser: use .get() with defaults instead of [] lookups
- Validator: add "none" as valid sync_strategy
Session testing revealed 3 issues with remote queries:
1. CLAUDE.md template recommended `cat <<HEREDOC | ssh ...` but
claude_settings.json had `cat` in deny list, causing 2-3 failed
attempts per query. Replaced with file-based approach: Write tool
creates JSON file, then `ssh ... < file` avoids the cat deny.
2. ssh/scp commands were not in the allow list, requiring manual
approval for every remote query. Added both to allow list.
3. DuckDB fetch_arrow_table() emitted DeprecationWarning on every
parquet export. Replaced with .arrow().read_all().
Also added instruction for proactive hybrid analysis when remote
tables are available (agent was only using local data until asked).
Agent was failing 3x on SSH commands due to backticks (BQ table names)
and single quotes (SQL string literals) getting mangled by nested shell
interpretation (local -> SSH -> bash -> Python).
New --stdin mode reads query spec as JSON from stdin via heredoc:
cat <<'QUERY' | ssh alias 'bash remote_query.sh --stdin'
{"register_bq": {"alias": "SELECT ... FROM \`table\` ..."}, "sql": "..."}
QUERY
Heredoc with <<'QUERY' (quoted) passes everything literally -- no
escaping needed for backticks, quotes, or parentheses.
Updated claude_md_template.txt to use --stdin as the primary method.
Analysts don't have WEBAPP_SECRET_KEY, so load_instance_config()
validation failed with noisy warnings. Now reads instance.yaml
directly with yaml.safe_load, skipping secret validation.
Add src/remote_query.py CLI module enabling the AI agent to run SQL
queries spanning local Parquet tables and remote BigQuery tables in a
single DuckDB session on the server. Two-phase protocol: BQ sub-queries
(--register-bq) fetch filtered/aggregated data, then DuckDB SQL (--sql)
joins everything.
Safety: COUNT(*) pre-check, memory estimation (2GB cap), row limits
(500K per BQ sub-query, 100K final result).
Changes:
- New src/remote_query.py with CLI, BQ registration, output formatting
- Add bq_entity_type field to TableConfig (view vs table routing)
- Extract create_local_views() from duckdb_manager.py for reuse
- Update claude_md_template.txt with remote query agent instructions
- Update example configs with remote_query section and docs
- 52 new tests (42 remote_query + 10 bq_entity_type), all passing
