agnes-the-ai-analyst/tests/test_keboola_extractor.py
ZdenekSrotyr 28430ced09
Keboola cutover: native parquet path + sync correctness + auto-discover protection (#190)
* fix: cutover regressions + parallel Keboola legacy fallback

Bundled fixes from a fresh-deploy run on a Keboola Storage backend with
the block-shared-snowflake-access feature flag — DuckDB Keboola
extension's per-table scan can't access bucket schemas, so the legacy
kbcstorage Storage-API client is the only working path.

CUTOVER REGRESSIONS

- agnes pull hash mismatch on every Keboola local-mode table —
  src/orchestrator.py:_update_sync_state stored md5(mtime+size)[:12]
  while the CLI compares against full 32-char content MD5. Now stores
  the same content MD5 the materialized SQL path already used.

- Trailing-slash sanitization in connectors/keboola/access.py and
  extractor.py — DuckDB Keboola extension's ATTACH fails when the URL
  ends in / (canonical form).

- src/profiler.py:TableInfo.description becomes optional — two call
  sites instantiated without it, crashing the profiler pass.

- scripts/ops/agnes-auto-upgrade.sh: chown on UID change — older images
  ran as root, current runs as agnes (uid 999). Reads target uid:gid
  from /etc/passwd inside the new image and chowns ${STATE_DIR},
  /data/extracts, /data/analytics when the digest moves.

- POST /api/sync/trigger is now singleton per process — two
  near-simultaneous trigger calls each forked an extractor subprocess,
  fought for extract.duckdb's file lock, starved uvicorn, flipped the
  container to unhealthy. Trigger now returns 409
  (sync_already_in_progress) when held; _run_sync acquires non-blocking.

PARALLEL LEGACY FALLBACK

- Process pool fan-out for the _extract_via_legacy queue (default 8
  workers, override via AGNES_KEBOOLA_PARALLELISM). Process pool, not
  thread pool, because connectors/keboola/client.py:export_table does
  os.chdir(temp_dir) — process-global, so threads raced and slice files
  landed in the wrong directory ("[Errno 2] No such file or directory:
  '<job_id>.csv_X_Y_Z.csv'").

- Extractor subprocess timeout 1800s -> 3600s (configurable via
  AGNES_EXTRACTOR_TIMEOUT_SEC). 28+ tables × multi-minute Keboola export
  jobs need the headroom on telemetry-class projects.

- Process group cleanup on timeout — Popen(start_new_session=True) puts
  the extractor in its own group. On timeout the parent SIGTERMs the
  group (10s grace) then SIGKILLs stragglers. Without this, the pool
  workers were reparented to PID 1 and continued holding open Keboola
  Storage export jobs. Inline extractor script also installs a SIGTERM
  -> sys.exit(143) handler so the with ProcessPoolExecutor(...) block
  __exit__ runs cleanly.

Tests: existing tests that patched subprocess.run updated to patch
subprocess.Popen with a _FakePopen stand-in (same exit-code-injection
contract). Two tests that exercised the parallel path forced
AGNES_KEBOOLA_PARALLELISM=1 to keep mocks alive (mocks don't ride into
ProcessPoolExecutor subprocesses).

Squashed onto current main (was 7 commits + multi-commit CHANGELOG +
agnes-auto-upgrade.sh conflicts; squash avoids per-commit conflict
resolution against main's flat-mount STATE_DIR refactor and 0.38.0
release cut).

* feat(keboola): Storage API direct extract path; drop extension data path

The DuckDB Keboola extension's COPY routes through Keboola QueryService,
which is unreliable on linked-bucket projects (extension v0.1.6 fixes
that case but isn't yet in the community CDN, and pre-fix any project
with the block-shared-snowflake-access feature flag couldn't see bucket
schemas at all). Move the extract path off the extension entirely and
talk to the Storage API directly via signed-URL download — works on any
project, regardless of extension state.

connectors/keboola/storage_api.py (NEW)
  Lightweight client built on requests.Session. Three endpoints:
  - POST /v2/storage/tables/{id}/export-async        (kicks off job)
  - GET  /v2/storage/jobs/{id}                        (poll until done)
  - GET  /v2/storage/files/{id}?federationToken=1     (signed URL detail)
  - GET  <signed_url>                                 (download bytes)
  Supports sliced exports (manifest + per-slice signed URLs) and gzipped
  payloads. ExportFilter dataclass mirrors the Keboola filter spec
  (whereFilters / columns / changedSince / limit) and handles JSON
  round-trip with the registry's source_query column. Token redaction
  in error messages. Bounded exponential backoff on job polling.
  No cloud-SDK dependency on the data path; thread-safe.

connectors/keboola/extractor.py
  - materialize_query() rewritten: takes bucket/source_table/source_query
    (JSON filter spec), exports via KeboolaStorageClient, converts CSV
    to parquet via DuckDB, atomic os.replace. Same return shape so
    sync.py downstream code stays uniform with the BQ branch.
  - _extract_via_legacy() also moved to Storage API direct (kept the
    name for caller compatibility with _legacy_worker / the parallel
    batch extractor). Per-call temp directories — no os.chdir, threads
    don't race.

app/api/sync.py
  _run_materialized_pass for source_type='keboola' rows now constructs a
  KeboolaStorageClient (replaces KeboolaAccess) and passes
  bucket/source_table/source_query to materialize_query. Reuses one
  client across rows for HTTP keep-alive. Sources keboola URL from env
  too (KEBOOLA_STACK_URL) when instance.yaml doesn't have stack_url
  configured.

cli/commands/admin.py
  discover-and-register defaults Keboola rows to query_mode='materialized'
  (NULL source_query = full table), matching the v26 migration's
  unification of the local/materialized split for Keboola. BigQuery and
  Jira keep their per-source defaults.

src/db.py
  Schema bump 25 → 26. Migration: UPDATE table_registry SET
  query_mode='materialized' WHERE source_type='keboola' AND
  query_mode='local'. NULL source_query on those rows means "full table
  export" — same effective behavior the local mode provided, but now
  via Storage API instead of the extension.

pyproject.toml
  kbcstorage dep stays (admin-side bucket/table list still uses the
  SDK in app/api/admin.py / connectors/keboola/client.py); only the
  data path is migrated off the SDK. Comment updated to reflect the
  new boundary.

tests
  - test_keboola_storage_api.py (NEW, 19 tests): ExportFilter parsing,
    HTTP client (token redaction, retry logic, polling), download_file
    (single, gzipped, sliced), end-to-end export_table_to_csv.
  - test_keboola_materialize.py rewritten: mocks KeboolaStorageClient
    instead of FakeAccess; same atomic-write + zero-rows + unsafe-id
    contracts.
  - test_sync_trigger_keboola_materialized.py: registry rows now carry
    bucket+source_table+JSON-shape source_query.

114+ Keboola-impacted tests green locally.

* test: schema version assertion bumped to 26 alongside the keboola query_mode migration

* fix(keboola): cutover hot-patches surfaced on agnes-dev

Five small fixes that were applied as in-container hot-patches during
agnes-dev cutover and need to be on the source-of-truth image so a fresh
upgrade does not undo them.

- app/api/sync.py: auto-discover gate considers the WHOLE registry (any
  source, any mode), not just rows where source matches and query_mode
  is local. After the v25→v26 keboola materialized migration an
  instance can have 30 materialized rows and zero local rows; the
  previous gate kept re-firing _discover_and_register_tables every
  scheduler tick, creating duplicate auto-discovered rows with the
  wrong bucket prefix every time.

- app/api/admin.py: _discover_and_register_tables reassembles the
  bucket as <stage>.<bucket-id> (e.g. in.c-finance) instead of
  dropping the stage prefix; default query_mode for keboola is now
  materialized (the v26 contract); validator allows NULL source_query
  for keboola materialized rows (full-table export via Storage API
  export-async, no SQL needed).

- cli/commands/admin.py: register-table mirrors the server validator
  (NULL source_query allowed for source_type=keboola); --bucket help
  text generalized to cover both BQ dataset and Keboola bucket id.

- connectors/keboola/extractor.py: max_line_size=64 MiB on
  read_csv_auto so embedded JSON / SQL cells (kbc_component_configuration
  in particular) do not trip the default 2 MiB ceiling.

- connectors/keboola/storage_api.py: GCP backend support — when the
  Storage API returns a manifest whose slice URLs are gs://
  references with a gcsCredentials block, rewrite to the JSON REST
  download endpoint and authenticate with the issued OAuth bearer
  token; redact tokens in any surfaced error string.

* test: align with new keboola materialized + auto-discover-gate contracts

- test_admin_keboola_materialized: rename
  test_register_keboola_materialized_rejects_missing_source_query →
  test_register_keboola_materialized_accepts_missing_source_query.
  v25→v26 introduced 'keboola materialized with NULL source_query
  means full-table export via Storage API export-async' as the
  default registration shape; the rejection case is no longer the
  contract.

- test_sync_filter: add list_all() to _StubRegistry. The auto-discover
  gate in _run_sync now keys off the WHOLE registry (not just local
  rows) so materialized-only Keboola instances do not re-trigger
  discovery on every tick.

* feat(keboola): native parquet export — skip CSV roundtrip

Storage API export-async accepts fileType={csv,parquet}. Switching the
materialized sync to parquet eliminates the CSV → DuckDB COPY → parquet
roundtrip that pinned a single uvicorn worker over 4 GiB on multi-GB
tables (read_csv with all_varchar + max_line_size=64MB has to
materialize the whole CSV in memory before COPY can stream out a
parquet). Snowflake UNLOAD on Keboola's side already produces typed,
self-contained parquet files; the extractor downloads them and renames
into place.

Two cases:

- **Single-file** export (small table): file_info.url points at one
  signed URL; download_file streams chunks straight to .parquet.tmp
  and we're done. No DuckDB.

- **Sliced** export (Snowflake UNLOAD respects MAX_FILE_SIZE — 16 MiB
  default — so anything larger arrives as N parquet slices): each
  slice is a complete parquet file with its own footer; naive concat
  would corrupt them. download_file_slices keeps the slices as
  separate files in a tempdir, then DuckDB COPY (SELECT * FROM
  read_parquet([slice0, slice1, ...])) merges them into one
  consolidated parquet. DuckDB streams row groups during this — peak
  memory bounded to one row group (~1 MiB) regardless of source size.

The legacy CSV path stays as the explicit opt-in via source_query=
'{"file_type":"csv"}' for projects whose backend can't UNLOAD
parquet (none known today; cheap escape hatch). Backward-compat alias
KeboolaStorageClient.export_table_to_csv kept.

Also fixes a latent bug in download_file's gzip detection: previous
heuristic flagged any unencrypted file as gzipped, which would have
corrupted parquet downloads at gunzip time. Name-suffix-only now.

* fix: tempdir leak cleanup, every 0m schedule, /sync/trigger body shapes

Three small self-contained fixes uncovered during agnes-dev cutover.

- connectors/keboola/extractor.py: tempfile.TemporaryDirectory now uses
  ignore_cleanup_errors=True so a worker death mid-write doesn't leave
  multi-GiB stale slice trees on the boot disk. (12 GiB seen after a
  disk-full crash where TemporaryDirectory's own cleanup also raised
  and got swallowed.)

- src/scheduler.py: is_valid_schedule accepts 'every 0m' (interval=0
  = always due). Force-resync of an errored row no longer requires
  waiting out the default 'every 1h' interval — admin can flip the
  schedule, trigger, then flip back.

- app/api/sync.py: POST /api/sync/trigger accepts both ['table_id']
  (legacy bare-array body) and {'tables': ['table_id']} (matches the
  response payload shape, more discoverable for clients building
  requests by hand). Malformed bodies return 422 with a structured
  detail; null/missing means 'sync everything' as before.

Tests cover: tempdir cleanup on raise (sliced parquet path),
is_valid_schedule + is_table_due 'every 0m' acceptance, and trigger
body parametrized matrix (8 valid shapes + 6 rejection cases).

* fix: targeted-trigger filter in materialized pass + auto-upgrade defer

Two operational gaps observed during agnes-dev cutover, in the same
sync-routing area.

- _run_materialized_pass now takes a 'tables' arg and skips rows not in
  the target set with reason='not_in_target'. POST /api/sync/trigger
  with a body of tables previously only scoped the legacy extractor
  subprocess — the materialized pass kept iterating every due
  materialized row, so an admin asking to re-sync kbc_job re-ran
  every other due materialized row alongside it. Match on registry id
  OR name (admins commonly pass either form). tables=None preserves
  the no-filter behavior.

- New GET /api/sync/status (public, no auth) returns {locked: bool}
  off _sync_lock.locked(). agnes-auto-upgrade.sh probes this before
  docker compose up -d and exits 0 with a 'deferred recreate' log
  line if a sync is in flight — the next 5-min cron tick retries.
  Pre-fix, an auto-upgrade triggered mid-sync would recreate the
  uvicorn worker and kill the in-flight extractor / Snowflake-UNLOAD
  download (observed when kbc_job's first 7-day retry got SIGKILLed).
  Connection failures in the probe fall through to the upgrade —
  being stuck on a wedged image is worse than interrupting a
  hypothetical sync.

* fix: auto-discover protects admin overrides + surfaces drift

Two real-world incidents on agnes-dev drove this:

1. kbc_job was registered manually with the correct
   (in.c-kbc_telemetry, kbc_job) coordinates. A naive auto-discover
   re-run would have inserted a SECOND kbc_job row at the slugified
   id 'in_c-keboola-storage_kbc_job' (where Keboola's discovery
   places it) — and that row's Storage API export-async 404s.

2. An earlier auto-discover bug stripped the stage prefix from
   bucket ids ('c-finance' instead of 'in.c-finance'), inserting
   137 rows whose syncs all failed.

Fix:

- _discover_and_register_tables now builds a plan first
  (_build_keboola_discovery_plan) classifying each discovered table
  into one of new / existing_match / existing_drift / invalid, then
  executes only the 'new' bucket. Drift rows are reported with both
  sides of the disagreement plus drift_kind:
  - same_id_diff_coords: registry has the same id but different
    bucket / source_table (admin migrated coords inline).
  - name_collision: discovery's slugified id differs from any
    registry id, but the discovered .name matches an existing row's
    .name (case-insensitive). Catches the kbc_job case.

- Bucket detection now prefers the API's authoritative bucket_id
  field (separate field on the Keboola tables.list response,
  normalised by KeboolaClient.discover_all_tables). Falls back to
  id-string parsing only when bucket_id is missing (older fallback
  path inside discover_all_tables).

- Endpoint POST /api/admin/discover-and-register?dry_run=true
  returns the plan without writing — would_register, drift,
  invalid lists. Lets an operator audit before merging discovery
  with a registry that has admin overrides.

Removed 'every 0m' from test_register_request_rejects_malformed_sync_schedule
— the runtime started accepting it in the previous commit (force-resync
override) and the validator follows suit.

* feat(keboola): AGNES_TEMP_DIR routes tempfiles off overlayfs /tmp

The container's /tmp lives on the boot disk's overlayfs (29 GiB on
agnes-dev, shared with /var). Snowflake UNLOAD of a wide table writes
slices into per-call /tmp tempdirs that fill multi-GiB / many-slice
exports long before the dedicated data disk fills. agnes-dev hit
100% boot-disk while the 20 GiB data disk had 15 GiB free.

connectors.keboola.storage_api.get_temp_root() reads AGNES_TEMP_DIR;
mkdirs the target on first use; unset / empty / unwritable falls
back to None (system tempdir, OSS-pre-fix behaviour). Both
materialize_query (parquet path) and _extract_via_legacy (CSV
fallback) and the sliced-CSV concat path in storage_api use the
helper now.

docker-compose.yml defaults AGNES_TEMP_DIR=/data/tmp on app, scheduler,
and extract services. The data volume is the dedicated disk in
production layouts and a plain docker volume in single-disk
dev/laptop setups — same blast radius as the previous /tmp default
on the latter, no regression.
2026-05-07 12:12:14 +02:00

580 lines
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Python

"""Tests for Keboola extractor."""
import os
from pathlib import Path
from unittest.mock import patch, MagicMock
import duckdb
import pytest
from tests.helpers.contract import validate_extract_contract
@pytest.fixture
def output_dir(tmp_path):
d = tmp_path / "extracts" / "keboola"
d.mkdir(parents=True)
return str(d)
@pytest.fixture
def sample_configs():
return [
{
"id": "in.c-crm.orders",
"name": "orders",
"source_type": "keboola",
"bucket": "in.c-crm",
"source_table": "orders",
"query_mode": "local",
"description": "Order data",
},
{
"id": "in.c-crm.customers",
"name": "customers",
"source_type": "keboola",
"bucket": "in.c-crm",
"source_table": "customers",
"query_mode": "local",
"description": "Customer data",
},
]
def _mock_attach(conn, url, token):
"""Mock that says extension is available and ATTACHes a fake kbc catalog."""
# Create in-memory DB as kbc so views referencing kbc."bucket"."table" can be created
conn.execute("ATTACH ':memory:' AS kbc")
return True
def _write_parquet(pq_path, data_sql="SELECT 1 AS id, 'test' AS name"):
"""Helper to write a parquet file with given SQL."""
local_conn = duckdb.connect()
local_conn.execute(f"COPY ({data_sql}) TO '{pq_path}' (FORMAT PARQUET)")
local_conn.close()
class TestKeboolaExtractor:
def test_creates_extract_duckdb(self, output_dir, sample_configs):
"""Test that run() creates extract.duckdb with correct structure."""
from connectors.keboola.extractor import run
def write_parquet(conn, tc, pq_path):
_write_parquet(pq_path)
with patch("connectors.keboola.extractor._try_attach_extension", side_effect=_mock_attach), \
patch("connectors.keboola.extractor._extract_via_extension", side_effect=write_parquet):
result = run(output_dir, sample_configs, "https://example.com", "test-token")
assert result["tables_extracted"] == 2
assert result["tables_failed"] == 0
# Verify extract.duckdb exists and has correct structure
db_path = Path(output_dir) / "extract.duckdb"
assert db_path.exists()
conn = duckdb.connect(str(db_path))
try:
# Check _meta table
meta = conn.execute("SELECT * FROM _meta ORDER BY table_name").fetchall()
assert len(meta) == 2
names = {row[0] for row in meta}
assert names == {"orders", "customers"}
# Check all are 'local' query_mode
modes = {row[5] for row in meta}
assert modes == {"local"}
finally:
conn.close()
validate_extract_contract(str(db_path))
def test_remote_tables_not_downloaded(self, output_dir):
"""Test that tables with query_mode='remote' are registered but not downloaded."""
from connectors.keboola.extractor import run
configs = [{
"name": "big_table",
"bucket": "in.c-events",
"source_table": "big_table",
"query_mode": "remote",
"description": "Too large to sync",
}]
def mock_attach_with_schema(conn, url, token):
"""Mock kbc with the expected bucket schema so remote views can be created."""
conn.execute("ATTACH ':memory:' AS kbc")
conn.execute('CREATE SCHEMA kbc."in.c-events"')
conn.execute('CREATE TABLE kbc."in.c-events"."big_table" (id VARCHAR)')
return True
with patch("connectors.keboola.extractor._try_attach_extension", side_effect=mock_attach_with_schema):
result = run(output_dir, configs, "https://example.com", "test-token")
assert result["tables_extracted"] == 1
conn = duckdb.connect(str(Path(output_dir) / "extract.duckdb"))
try:
meta = conn.execute("SELECT query_mode FROM _meta WHERE table_name='big_table'").fetchone()
assert meta[0] == "remote"
# _remote_attach table should exist with Keboola connection info
ra = conn.execute("SELECT alias, extension, url, token_env FROM _remote_attach").fetchone()
assert ra[0] == "kbc"
assert ra[1] == "keboola"
assert ra[2] == "https://example.com"
assert ra[3] == "KEBOOLA_STORAGE_TOKEN"
finally:
conn.close()
# No parquet file should exist
assert not (Path(output_dir) / "data" / "big_table.parquet").exists()
def test_handles_extraction_failure(self, output_dir, sample_configs, monkeypatch):
"""Test that a failed table doesn't stop other tables from extracting."""
from connectors.keboola.extractor import run
call_count = 0
def side_effect(conn, tc, pq_path):
nonlocal call_count
call_count += 1
if call_count == 1:
raise Exception("Network error")
# Second call succeeds
_write_parquet(pq_path, "SELECT 1 AS id")
# Mock the legacy fallback too — without it the real client
# attempts an HTTPS round-trip to the test URL and hangs ~minute.
# Force inline (PARALLELISM=1) so the mock survives — the parallel
# path would spawn a subprocess that doesn't see the patch.
monkeypatch.setenv("AGNES_KEBOOLA_PARALLELISM", "1")
def legacy_reraise(tc, pq_path, url, token):
raise Exception("Network error")
with patch("connectors.keboola.extractor._try_attach_extension", side_effect=_mock_attach), \
patch("connectors.keboola.extractor._extract_via_extension", side_effect=side_effect), \
patch("connectors.keboola.extractor._extract_via_legacy", side_effect=legacy_reraise):
result = run(output_dir, sample_configs, "https://example.com", "test-token")
assert result["tables_extracted"] == 1
assert result["tables_failed"] == 1
assert len(result["errors"]) == 1
def test_creates_data_directory(self, output_dir, sample_configs):
"""Test that data/ subdirectory is created."""
from connectors.keboola.extractor import run
def write_pq(conn, tc, pq_path):
_write_parquet(pq_path, "SELECT 1 AS id")
with patch("connectors.keboola.extractor._try_attach_extension", side_effect=_mock_attach), \
patch("connectors.keboola.extractor._extract_via_extension", side_effect=write_pq):
run(output_dir, sample_configs, "https://example.com", "test-token")
assert (Path(output_dir) / "data").is_dir()
assert (Path(output_dir) / "data" / "orders.parquet").exists()
def test_views_queryable(self, output_dir):
"""Test that views in extract.duckdb can be queried."""
from connectors.keboola.extractor import run
configs = [{"name": "test_table", "query_mode": "local", "description": "Test"}]
def write_pq(conn, tc, pq_path):
_write_parquet(pq_path, "SELECT 42 AS value, 'hello' AS msg")
with patch("connectors.keboola.extractor._try_attach_extension", side_effect=_mock_attach), \
patch("connectors.keboola.extractor._extract_via_extension", side_effect=write_pq):
run(output_dir, configs, "https://example.com", "test-token")
conn = duckdb.connect(str(Path(output_dir) / "extract.duckdb"))
try:
result = conn.execute("SELECT value, msg FROM test_table").fetchone()
assert result[0] == 42
assert result[1] == "hello"
finally:
conn.close()
def test_meta_table_schema(self, output_dir):
"""Test that _meta table has all required columns."""
from connectors.keboola.extractor import run
configs = [{"name": "t", "query_mode": "local", "description": "desc"}]
def write_pq(conn, tc, pq_path):
_write_parquet(pq_path, "SELECT 1 AS x")
with patch("connectors.keboola.extractor._try_attach_extension", side_effect=_mock_attach), \
patch("connectors.keboola.extractor._extract_via_extension", side_effect=write_pq):
run(output_dir, configs, "https://example.com", "test-token")
conn = duckdb.connect(str(Path(output_dir) / "extract.duckdb"))
try:
cols = conn.execute("SELECT column_name FROM information_schema.columns WHERE table_name='_meta' ORDER BY ordinal_position").fetchall()
col_names = [c[0] for c in cols]
assert col_names == ["table_name", "description", "rows", "size_bytes", "extracted_at", "query_mode"]
finally:
conn.close()
def test_legacy_fallback_when_extension_unavailable(self, output_dir):
"""Test that legacy client is used when extension attach fails."""
from connectors.keboola.extractor import run
configs = [{"name": "t", "id": "in.c-test.t", "query_mode": "local", "description": ""}]
def mock_legacy(tc, pq_path, url, token):
_write_parquet(pq_path, "SELECT 1 AS id")
# Extension not available
with patch("connectors.keboola.extractor._try_attach_extension", return_value=False), \
patch("connectors.keboola.extractor._extract_via_legacy", side_effect=mock_legacy):
result = run(output_dir, configs, "https://example.com", "test-token")
assert result["tables_extracted"] == 1
assert result["tables_failed"] == 0
# ---------------------------------------------------------------------------
# Connector failure mode tests
# ---------------------------------------------------------------------------
class TestKeboolaExtractorFailureModes:
"""Tests for Keboola extractor failure handling and resilience."""
def test_extractor_crash_does_not_corrupt_extract_duckdb(self, output_dir, sample_configs):
"""If the extractor crashes mid-extraction, the temp DB is not moved
into place, so the existing extract.duckdb (if any) is not corrupted.
The atomic write pattern (tmp + rename) protects against this."""
from connectors.keboola.extractor import run
# First, create a valid extract.duckdb
def write_pq(conn, tc, pq_path):
_write_parquet(pq_path, "SELECT 1 AS id")
with patch("connectors.keboola.extractor._try_attach_extension", side_effect=_mock_attach), patch("connectors.keboola.extractor._extract_via_extension", side_effect=write_pq):
run(output_dir, sample_configs[:1], "https://example.com", "test-token")
db_path = Path(output_dir) / "extract.duckdb"
assert db_path.exists()
# Verify it's valid
conn = duckdb.connect(str(db_path))
conn.execute("SELECT * FROM _meta").fetchall()
conn.close()
# Now simulate a crash during a second extraction — the extension
# attach raises an exception after the tmp file is created.
with patch("connectors.keboola.extractor._try_attach_extension", side_effect=RuntimeError("crash")):
try:
run(output_dir, sample_configs, "https://example.com", "test-token")
except Exception:
pass # The extractor catches internally and returns stats
# The extract.duckdb should still exist and be valid (atomic swap
# means the old file is untouched if the new one didn't complete)
assert db_path.exists()
def test_partial_data_write_incomplete_parquet(self, output_dir):
"""When a parquet file write fails mid-stream, the extractor records
the table as failed in stats but continues with other tables."""
from connectors.keboola.extractor import run
configs = [
{"name": "good_table", "query_mode": "local", "description": "OK"},
{"name": "bad_table", "query_mode": "local", "description": "Will fail"},
]
call_count = 0
def side_effect(conn, tc, pq_path):
nonlocal call_count
call_count += 1
if tc["name"] == "bad_table":
raise IOError("Disk full — partial write")
_write_parquet(pq_path, "SELECT 1 AS id")
with patch("connectors.keboola.extractor._try_attach_extension", side_effect=_mock_attach), patch("connectors.keboola.extractor._extract_via_extension", side_effect=side_effect):
result = run(output_dir, configs, "https://example.com", "test-token")
# One table succeeded, one failed
assert result["tables_extracted"] == 1
assert result["tables_failed"] == 1
assert len(result["errors"]) == 1
assert "bad_table" in result["errors"][0]["table"]
# The good table's parquet file exists
assert (Path(output_dir) / "data" / "good_table.parquet").exists()
# The bad table's parquet file should NOT exist (failed before write)
assert not (Path(output_dir) / "data" / "bad_table.parquet").exists()
def test_network_timeout_during_extraction(self, output_dir, monkeypatch):
"""Network timeout during extraction should return a meaningful error
in the stats, not crash the whole process."""
from connectors.keboola.extractor import run
import socket
configs = [
{"name": "timeout_table", "query_mode": "local", "description": "Will timeout"},
{"name": "ok_table", "query_mode": "local", "description": "OK"},
]
call_count = 0
def side_effect(conn, tc, pq_path):
nonlocal call_count
call_count += 1
if tc["name"] == "timeout_table":
raise socket.timeout("Connection timed out")
_write_parquet(pq_path, "SELECT 1 AS id")
# When extension scan fails, the per-table flow now retries via
# _extract_via_legacy. Mock it to re-raise the same socket.timeout
# so we observe the final error surface; the contract under test is
# "extension failure doesn't crash, error makes it into stats, other
# tables continue", not which path produced the message.
# Force PARALLELISM=1 so the mock survives — the parallel path uses
# ProcessPoolExecutor which spawns subprocesses that don't see the
# mock.
monkeypatch.setenv("AGNES_KEBOOLA_PARALLELISM", "1")
def legacy_reraise(tc, pq_path, url, token):
raise socket.timeout("Connection timed out")
with patch("connectors.keboola.extractor._try_attach_extension", side_effect=_mock_attach), \
patch("connectors.keboola.extractor._extract_via_extension", side_effect=side_effect), \
patch("connectors.keboola.extractor._extract_via_legacy", side_effect=legacy_reraise):
result = run(output_dir, configs, "https://example.com", "test-token")
assert result["tables_extracted"] == 1
assert result["tables_failed"] == 1
assert "timed out" in result["errors"][0]["error"].lower()
def test_extension_unavailable_fallback_to_client(self, output_dir):
"""When DuckDB Keboola extension fails to load, the extractor falls
back to the legacy HTTP client."""
from connectors.keboola.extractor import run
configs = [{"name": "t", "id": "in.c-test.t", "query_mode": "local",
"bucket": "in.c-test", "source_table": "t", "description": ""}]
def mock_legacy(tc, pq_path, url, token):
_write_parquet(pq_path, "SELECT 42 AS value")
with patch("connectors.keboola.extractor._try_attach_extension", return_value=False), patch("connectors.keboola.extractor._extract_via_legacy", side_effect=mock_legacy):
result = run(output_dir, configs, "https://example.com", "test-token")
assert result["tables_extracted"] == 1
assert result["tables_failed"] == 0
# Verify the data is queryable
conn = duckdb.connect(str(Path(output_dir) / "extract.duckdb"))
val = conn.execute("SELECT value FROM t").fetchone()
assert val[0] == 42
conn.close()
def test_extension_per_table_failure_falls_back_to_legacy(self, output_dir):
"""When ATTACH succeeds but the per-table extension scan fails (e.g.
Keboola QueryService schema/role mismatch — keboola/duckdb-extension#17),
the extractor retries that table via the legacy Storage-API client."""
from connectors.keboola.extractor import run
configs = [{"name": "t", "id": "in.c-test.t", "query_mode": "local",
"bucket": "in.c-test", "source_table": "t", "description": ""}]
def extension_scan_fails(conn, tc, pq_path):
raise RuntimeError(
"Keboola scan failed: Schema 'KBC_USE4_NNNN.\"in.c-test\"' "
"does not exist or not authorized."
)
def legacy_succeeds(tc, pq_path, url, token):
_write_parquet(pq_path, "SELECT 7 AS value")
with patch("connectors.keboola.extractor._try_attach_extension", side_effect=_mock_attach), \
patch("connectors.keboola.extractor._extract_via_extension", side_effect=extension_scan_fails), \
patch("connectors.keboola.extractor._extract_via_legacy", side_effect=legacy_succeeds):
result = run(output_dir, configs, "https://example.com", "test-token")
assert result["tables_extracted"] == 1
assert result["tables_failed"] == 0
# Verify the legacy-produced data is queryable
conn = duckdb.connect(str(Path(output_dir) / "extract.duckdb"))
val = conn.execute("SELECT value FROM t").fetchone()
assert val[0] == 7
conn.close()
def test_all_tables_fail_returns_full_failure_stats(self, output_dir, monkeypatch):
"""When every table fails, the extractor returns all failures in stats
without crashing."""
from connectors.keboola.extractor import run
configs = [
{"name": "t1", "query_mode": "local", "description": ""},
{"name": "t2", "query_mode": "local", "description": ""},
]
def always_fail(conn, tc, pq_path):
raise RuntimeError("Extraction failed")
# Mock legacy too — otherwise it would attempt a real HTTP call to
# the fake URL on each per-table fallback retry. Force inline mode
# (AGNES_KEBOOLA_PARALLELISM=1) so the mock survives — the parallel
# path uses ProcessPoolExecutor which spawns subprocesses that
# don't see the mock.
monkeypatch.setenv("AGNES_KEBOOLA_PARALLELISM", "1")
def legacy_also_fails(tc, pq_path, url, token):
raise RuntimeError("Extraction failed")
with patch("connectors.keboola.extractor._try_attach_extension", side_effect=_mock_attach), \
patch("connectors.keboola.extractor._extract_via_extension", side_effect=always_fail), \
patch("connectors.keboola.extractor._extract_via_legacy", side_effect=legacy_also_fails):
result = run(output_dir, configs, "https://example.com", "test-token")
assert result["tables_extracted"] == 0
assert result["tables_failed"] == 2
assert len(result["errors"]) == 2
def test_legacy_parallelism_one_runs_inline(self, output_dir, monkeypatch):
"""AGNES_KEBOOLA_PARALLELISM=1 keeps the legacy fallback inline —
no ProcessPoolExecutor, so unittest.mock patches survive. Useful
as a debugging escape hatch and the path used by tests below.
Why processes (not threads) for the parallel path: the legacy
client's `export_table` does `os.chdir(temp_dir)` to direct
kbcstorage's slice-file downloads into a per-call temp directory.
`os.chdir` is process-global, so two threads racing on it land
slice files in the wrong directory and the merge step fails with
`[Errno 2] No such file or directory`. Process workers each have
their own CWD and don't interfere."""
from connectors.keboola.extractor import run
configs = [
{"name": f"u{i}", "query_mode": "local", "description": "",
"bucket": "in.c-test", "source_table": f"u{i}"}
for i in range(3)
]
call_count = 0
def mock_legacy(tc, pq_path, url, token):
nonlocal call_count
call_count += 1
_write_parquet(pq_path, "SELECT 1 AS x")
def extension_always_fails(conn, tc, pq_path):
raise RuntimeError("Schema not authorized")
monkeypatch.setenv("AGNES_KEBOOLA_PARALLELISM", "1")
with patch("connectors.keboola.extractor._try_attach_extension", side_effect=_mock_attach), \
patch("connectors.keboola.extractor._extract_via_extension", side_effect=extension_always_fails), \
patch("connectors.keboola.extractor._extract_via_legacy", side_effect=mock_legacy):
result = run(output_dir, configs, "https://example.com", "test-token")
assert result["tables_extracted"] == 3
assert result["tables_failed"] == 0
assert call_count == 3, "all 3 tables should have called the patched legacy fn"
def test_legacy_uses_process_pool_when_parallel(self, output_dir, monkeypatch):
"""Structural check: when len(legacy_queue) > 1 and
AGNES_KEBOOLA_PARALLELISM > 1, the parallel path imports
`concurrent.futures.ProcessPoolExecutor` to drain the queue.
The mock can't ride into subprocesses (mocks aren't picklable),
so we patch ProcessPoolExecutor itself and verify it's invoked
with the expected worker count."""
from connectors.keboola.extractor import run
configs = [
{"name": f"t{i}", "query_mode": "local", "description": "",
"bucket": "in.c-test", "source_table": f"t{i}"}
for i in range(5)
]
def extension_always_fails(conn, tc, pq_path):
raise RuntimeError("Schema not authorized")
# Stand in for ProcessPoolExecutor — runs everything in-process
# so we can verify the call shape without dealing with pickling.
seen_max_workers = []
class _FakePool:
def __init__(self, max_workers):
seen_max_workers.append(max_workers)
def __enter__(self):
return self
def __exit__(self, *exc):
return False
def submit(self, fn, *args, **kwargs):
from concurrent.futures import Future
f: Future = Future()
try:
# Inline the legacy call so the parquet ends up on disk
# for the orchestrator's downstream stat + _meta logic.
f.set_result(fn(*args, **kwargs))
except Exception as e:
f.set_exception(e)
return f
def mock_legacy(tc, pq_path, url, token):
_write_parquet(pq_path, "SELECT 1 AS x")
monkeypatch.setenv("AGNES_KEBOOLA_PARALLELISM", "4")
with patch("connectors.keboola.extractor._try_attach_extension", side_effect=_mock_attach), \
patch("connectors.keboola.extractor._extract_via_extension", side_effect=extension_always_fails), \
patch("connectors.keboola.extractor._extract_via_legacy", side_effect=mock_legacy), \
patch("concurrent.futures.ProcessPoolExecutor", _FakePool):
result = run(output_dir, configs, "https://example.com", "test-token")
assert result["tables_extracted"] == 5
assert result["tables_failed"] == 0
assert seen_max_workers == [4], (
f"Expected ProcessPoolExecutor(max_workers=4); got {seen_max_workers}"
)
def test_unsafe_identifier_skipped_not_crashed(self, output_dir):
"""Tables with unsafe identifiers are skipped with an error in stats,
not causing a crash."""
from connectors.keboola.extractor import run
configs = [
{"name": "bad-name", "query_mode": "local", "description": "hyphen not allowed"},
{"name": "good_name", "query_mode": "local", "description": "OK"},
]
def write_pq(conn, tc, pq_path):
_write_parquet(pq_path, "SELECT 1 AS id")
with patch("connectors.keboola.extractor._try_attach_extension", side_effect=_mock_attach), \
patch("connectors.keboola.extractor._extract_via_extension", side_effect=write_pq):
result = run(output_dir, configs, "https://example.com", "test-token")
assert result["tables_extracted"] == 1
assert result["tables_failed"] == 1
assert result["errors"][0]["error"] == "unsafe identifier"
def test_compute_exit_code_full_success(self):
from connectors.keboola.extractor import compute_exit_code
stats = {"tables_failed": 0, "errors": []}
assert compute_exit_code(stats, 5) == 0
def test_compute_exit_code_partial_failure(self):
from connectors.keboola.extractor import compute_exit_code
stats = {"tables_failed": 2, "errors": [{}, {}]}
assert compute_exit_code(stats, 5) == 2
def test_compute_exit_code_full_failure(self):
from connectors.keboola.extractor import compute_exit_code
stats = {"tables_failed": 5, "errors": [{}] * 5}
assert compute_exit_code(stats, 5) == 1
def test_compute_exit_code_no_tables(self):
from connectors.keboola.extractor import compute_exit_code
stats = {"tables_failed": 0, "errors": []}
assert compute_exit_code(stats, 0) == 0