agnes-the-ai-analyst/connectors/keboola/extractor.py
ZdenekSrotyr 4751094e1c
fix(keboola): per-table fallback to legacy Storage-API client (#183)
* fix(keboola): per-table fallback to legacy Storage-API client

The DuckDB Keboola extension's per-table COPY fails with
`Schema '..."in.c-..."' does not exist or not authorized` on
projects whose Snowflake backend doesn't expose bucket schemas
to the storage-token-derived QueryService role
(keboola/duckdb-extension#17). ATTACH itself succeeds, so the
existing extension-level fallback in `_try_attach_extension`
never triggers — the table is just marked failed.

- Promote `kbcstorage>=0.9.0` from optional to core dep so the
  legacy client import in `_extract_via_legacy` doesn't crash
  default installs with `ModuleNotFoundError`.
- Wrap `_extract_via_extension` in a per-table try/except so a
  scan failure retries via `_extract_via_legacy` instead of
  recording `tables_failed` and moving on.

Slower than the extension path, but produces correct parquets
on affected projects while the upstream extension fix lands.

* test(keboola): cover per-table extension→legacy fallback

Two existing tests mocked _extract_via_extension to throw and asserted
the original message survived in result["errors"]. With per-table
fallback, the new flow retries via _extract_via_legacy — which on the
mock URLs would throw a different (404 / DNS-fail) error, replacing the
asserted message.

- Mock _extract_via_legacy alongside _extract_via_extension in
  test_network_timeout_during_extraction +
  test_partial_failure_continues +
  test_all_tables_fail_returns_full_failure_stats so the assertion
  observes the final propagated error from the fallback chain.
- Add test_extension_per_table_failure_falls_back_to_legacy that
  exercises the new behavior directly: extension scan fails with the
  QueryService schema-not-authorized message
  (keboola/duckdb-extension#17), legacy succeeds, parquet ends up
  queryable.
2026-05-05 15:47:44 +02:00

428 lines
17 KiB
Python

"""Keboola extractor — produces extract.duckdb + data/*.parquet using DuckDB Keboola extension."""
import logging
import os
from datetime import datetime, timezone
from pathlib import Path
from typing import List, Dict, Any
import duckdb
from src.identifier_validation import (
is_safe_quoted_identifier,
validate_identifier,
validate_quoted_identifier,
)
logger = logging.getLogger(__name__)
def materialize_query(
table_id: str,
sql: str,
*,
keboola_access, # KeboolaAccess (avoid circular import)
output_dir: Path,
) -> dict:
"""Materialize an admin-registered SELECT against the Keboola Storage
API extension into a parquet file.
Parallel of `connectors/bigquery/extractor.py:materialize_query`.
Cost guardrail: the Keboola extension has no analog of BQ dry-run;
Storage API cost is download-shaped (per-byte egress + Storage API
job). Phase B ships without a guardrail and logs the byte count;
a future PR can add a configurable `max_bytes_per_keboola_materialize`
gate similar to BQ's `max_bytes_per_materialize`.
"""
import re
import hashlib
# Defense: table_id is interpolated into the parquet filename.
# Reject anything that's not a safe identifier.
if not re.fullmatch(r"[A-Za-z_][A-Za-z0-9_]*", table_id):
raise ValueError(f"unsafe table_id for materialize: {table_id!r}")
parquet_path = Path(output_dir) / f"{table_id}.parquet"
tmp_path = Path(output_dir) / f"{table_id}.parquet.tmp"
if tmp_path.exists():
tmp_path.unlink()
safe_tmp_lit = str(tmp_path).replace("'", "''")
# Atomic write — mirror BQ's pattern at connectors/bigquery/extractor.py:370.
# COPY into a `.parquet.tmp`, hash + size from the tmp file, only swap to
# the final path on success. A mid-COPY failure (network, disk full,
# extension crash) leaves no partial parquet at the canonical path that
# the orchestrator rebuild would pick up. Devin finding 2026-05-01:
# BUG_pr-review-job-3fbd31c9_0003.
with keboola_access.duckdb_session() as conn:
try:
conn.execute(f"COPY ({sql}) TO '{safe_tmp_lit}' (FORMAT PARQUET)")
row_count = conn.execute(
f"SELECT COUNT(*) FROM read_parquet('{safe_tmp_lit}')"
).fetchone()[0]
except Exception:
if tmp_path.exists():
tmp_path.unlink()
raise
# Streaming MD5 — never read the entire parquet into memory. Keboola
# materialized results can reach multi-GB sizes (admin-aggregated
# subsets); hashing in 8 KiB chunks keeps memory bounded. Mirror of BQ's
# streaming hash at connectors/bigquery/extractor.py:438. Devin finding
# 2026-05-01: BUG_pr-review-job-3fbd31c9_0002.
h = hashlib.md5()
with open(tmp_path, "rb") as f:
for chunk in iter(lambda: f.read(8192), b""):
h.update(chunk)
md5 = h.hexdigest()
size = tmp_path.stat().st_size
os.replace(tmp_path, parquet_path)
if row_count == 0:
logger.warning(
"Materialized Keboola query for %s wrote 0 rows — verify the "
"SQL filters and that the source bucket has data.",
table_id,
)
return {
"table_id": table_id,
"path": str(parquet_path),
"rows": row_count,
"bytes": size,
"md5": md5,
}
def _create_meta_table(conn: duckdb.DuckDBPyConnection) -> None:
"""Create the _meta table required by the extract.duckdb contract."""
conn.execute("DROP TABLE IF EXISTS _meta")
conn.execute("""CREATE TABLE _meta (
table_name VARCHAR NOT NULL,
description VARCHAR,
rows BIGINT,
size_bytes BIGINT,
extracted_at TIMESTAMP,
query_mode VARCHAR DEFAULT 'local'
)""")
def _create_remote_attach_table(conn: duckdb.DuckDBPyConnection, keboola_url: str) -> None:
"""Write _remote_attach so orchestrator can re-ATTACH the Keboola extension."""
conn.execute("DROP TABLE IF EXISTS _remote_attach")
conn.execute("""CREATE TABLE _remote_attach (
alias VARCHAR,
extension VARCHAR,
url VARCHAR,
token_env VARCHAR
)""")
conn.execute(
"INSERT INTO _remote_attach VALUES (?, ?, ?, ?)",
["kbc", "keboola", keboola_url, "KEBOOLA_STORAGE_TOKEN"],
)
def _try_attach_extension(conn: duckdb.DuckDBPyConnection, keboola_url: str, keboola_token: str) -> bool:
"""Try to install and attach the Keboola DuckDB extension. Returns True on success."""
try:
conn.execute("INSTALL keboola FROM community; LOAD keboola;")
escaped_token = keboola_token.replace("'", "''")
conn.execute(f"ATTACH '{keboola_url}' AS kbc (TYPE keboola, TOKEN '{escaped_token}')")
logger.info("Using DuckDB Keboola extension")
return True
except Exception as e:
logger.warning("Keboola extension unavailable (%s), falling back to legacy client", e)
return False
def run(output_dir: str, table_configs: List[Dict[str, Any]], keboola_url: str, keboola_token: str) -> Dict[str, Any]:
"""Extract tables from Keboola into output_dir using DuckDB extension.
Args:
output_dir: Path to write extract.duckdb + data/
table_configs: List of table config dicts from table_registry
keboola_url: Keboola stack URL
keboola_token: Keboola Storage API token
Returns:
Dict with extraction stats: {tables_extracted: int, tables_failed: int, errors: list}
"""
output_path = Path(output_dir)
data_dir = output_path / "data"
data_dir.mkdir(parents=True, exist_ok=True)
# Write to temp file then rename — avoids lock conflict with orchestrator
# which may hold a read lock on the existing extract.duckdb
db_path = output_path / "extract.duckdb"
tmp_db_path = output_path / "extract.duckdb.tmp"
if tmp_db_path.exists():
tmp_db_path.unlink()
conn = duckdb.connect(str(tmp_db_path))
stats = {"tables_extracted": 0, "tables_failed": 0, "errors": []}
now = datetime.now(timezone.utc)
try:
# Try DuckDB Keboola extension
use_extension = _try_attach_extension(conn, keboola_url, keboola_token)
_create_meta_table(conn)
has_remote = any(tc.get("query_mode") == "remote" for tc in table_configs)
if has_remote and use_extension:
_create_remote_attach_table(conn, keboola_url)
for tc in table_configs:
table_name = tc["name"]
query_mode = tc.get("query_mode", "local")
# Materialized rows are written by the sync trigger pass via
# `materialize_query()` — they live as parquets in
# /data/extracts/keboola/data/, picked up by the orchestrator's
# standard local-parquet discovery. Don't extract here (would
# double-write data via the source bucket reference and confuse
# sync_state bookkeeping). Mirror of the BQ extractor's skip at
# connectors/bigquery/extractor.py:190.
if query_mode == "materialized":
logger.info(
"Skipping legacy extract for %s — query_mode='materialized', "
"handled by _run_materialized_pass instead",
tc.get("id") or tc.get("name"),
)
continue
# #81 Group D — refuse rows whose identifiers don't pass the
# whitelist. The registry is admin-controlled but anyone with
# write access can otherwise inject SQL via the CREATE VIEW /
# COPY / SELECT interpolation below. Skip-and-continue rather
# than crashing the whole extraction; valid rows still process.
#
# `table_name` is the DuckDB view name in the master
# analytics DB. The orchestrator uses the STRICT validator
# (`^[a-zA-Z_][a-zA-Z0-9_]{0,63}$`) when re-creating views,
# so any name with `-` or `.` would pass extraction here
# but be silently dropped at orchestrator-rebuild time.
# Use the strict validator here too so the failure is
# caught early and visible in tables_failed.
if not validate_identifier(table_name, "Keboola table_name"):
stats["tables_failed"] += 1
stats["errors"].append({"table": table_name, "error": "unsafe identifier"})
continue
if query_mode == "remote":
# Create view pointing to kbc extension (requires re-ATTACH at query time)
bucket = tc.get("bucket", "")
source_table = tc.get("source_table", table_name)
if not (
validate_quoted_identifier(bucket, "Keboola bucket")
and validate_quoted_identifier(source_table, "Keboola source_table")
):
stats["tables_failed"] += 1
stats["errors"].append({"table": table_name, "error": "unsafe bucket/source_table"})
continue
if use_extension and bucket:
conn.execute(
f'CREATE OR REPLACE VIEW "{table_name}" AS SELECT * FROM kbc."{bucket}"."{source_table}"'
)
conn.execute(
"INSERT INTO _meta VALUES (?, ?, 0, 0, ?, 'remote')",
[table_name, tc.get("description", ""), now],
)
stats["tables_extracted"] += 1
continue
try:
pq_path = str(data_dir / f"{table_name}.parquet")
if use_extension:
try:
_extract_via_extension(conn, tc, pq_path)
except Exception as ext_err:
# ATTACH succeeded but the per-table COPY failed —
# most commonly a Keboola QueryService permission error
# (`Schema '..."in.c-..."' does not exist or not
# authorized`, see keboola/duckdb-extension#17). The
# legacy Storage-API client doesn't go through
# QueryService at all, so retry there.
logger.warning(
"Keboola extension scan failed for %s (%s); retrying via legacy Storage-API client",
table_name, ext_err,
)
_extract_via_legacy(tc, pq_path, keboola_url, keboola_token)
else:
_extract_via_legacy(tc, pq_path, keboola_url, keboola_token)
# Get row count and file size. pq_path is built from the
# validated table_name above, but escape the parquet path
# literal for defense-in-depth.
safe_pq_lit = pq_path.replace("'", "''")
rows = conn.execute(f"SELECT count(*) FROM read_parquet('{safe_pq_lit}')").fetchone()[0]
size = os.path.getsize(pq_path)
# Create view and register in _meta
conn.execute(f"CREATE OR REPLACE VIEW \"{table_name}\" AS SELECT * FROM read_parquet('{safe_pq_lit}')")
conn.execute(
"INSERT INTO _meta VALUES (?, ?, ?, ?, ?, 'local')",
[table_name, tc.get("description", ""), rows, size, now],
)
stats["tables_extracted"] += 1
logger.info("Extracted %s: %d rows, %d bytes", table_name, rows, size)
except Exception as e:
logger.error("Failed to extract %s: %s", table_name, e)
stats["tables_failed"] += 1
stats["errors"].append({"table": table_name, "error": str(e)})
# Detach Keboola if extension was used
if use_extension:
try:
conn.execute("DETACH kbc")
except Exception:
pass
finally:
conn.execute("CHECKPOINT")
conn.close()
# Atomic replace: swap temp DB into place, cleaning up any WAL files
import shutil
old_wal = Path(str(db_path) + ".wal")
if old_wal.exists():
old_wal.unlink()
if tmp_db_path.exists():
shutil.move(str(tmp_db_path), str(db_path))
tmp_wal = Path(str(tmp_db_path) + ".wal")
if tmp_wal.exists():
tmp_wal.unlink()
return stats
def _extract_via_extension(conn: duckdb.DuckDBPyConnection, tc: Dict[str, Any], pq_path: str) -> None:
"""Extract a table using the DuckDB Keboola extension."""
bucket = tc.get("bucket", "")
source_table = tc.get("source_table", tc["name"])
# #81 Group D — defense-in-depth. The caller already validates these;
# refuse here too in case a future caller forgets. Use the relaxed
# quoted-identifier check that accepts Keboola's `in.c-foo` form.
if not (is_safe_quoted_identifier(bucket) and is_safe_quoted_identifier(source_table)):
raise ValueError(f"unsafe bucket/source_table: {bucket!r}/{source_table!r}")
safe_pq_lit = pq_path.replace("'", "''")
conn.execute(f'COPY (SELECT * FROM kbc."{bucket}"."{source_table}") TO \'{safe_pq_lit}\' (FORMAT PARQUET)')
def _extract_via_legacy(tc: Dict[str, Any], pq_path: str, keboola_url: str, keboola_token: str) -> None:
"""Fallback: extract using legacy Keboola client (kbcstorage SDK)."""
from connectors.keboola.client import KeboolaClient
client = KeboolaClient(token=keboola_token, url=keboola_url)
# Export to CSV temp file, then convert to parquet via DuckDB
import tempfile
with tempfile.NamedTemporaryFile(suffix=".csv", delete=False) as tmp:
csv_path = tmp.name
try:
# Construct full Keboola table ID: bucket.source_table (e.g., in.c-finance.circle)
bucket = tc.get("bucket", "")
source_table = tc.get("source_table", tc["name"])
table_id = f"{bucket}.{source_table}" if bucket else tc.get("id", tc["name"])
client.export_table(table_id, Path(csv_path))
# Convert CSV to Parquet using DuckDB — all_varchar avoids type inference errors
# (e.g. columns with mostly numeric values but some strings like "Non-Manager")
conv_conn = duckdb.connect()
conv_conn.execute(
f"COPY (SELECT * FROM read_csv('{csv_path}', all_varchar=true)) TO '{pq_path}' (FORMAT PARQUET)"
)
conv_conn.close()
finally:
if os.path.exists(csv_path):
os.unlink(csv_path)
def compute_exit_code(stats: Dict[str, Any], total: int) -> int:
"""Map an extraction `stats` dict to a process exit code.
Issue #81 Group B: distinguish full success from partial failure so
the sync API and CLI consumers can alert on partial vs. full failure
rather than treating any non-zero as one bucket.
- ``0`` — every table succeeded (or no tables registered).
- ``1`` — every table failed (full failure).
- ``2`` — at least one succeeded and at least one failed (partial).
`total` is the count of tables the extractor was asked to process.
`stats["tables_failed"]` is the count it actually failed.
"""
failed = stats.get("tables_failed", 0)
if total == 0:
return 0
if failed == 0:
return 0
if failed >= total:
return 1
return 2
if __name__ == "__main__":
"""Standalone: reads config from env + table_registry, runs extraction.
Used by sync trigger subprocess. Reads KEBOOLA_STORAGE_TOKEN and
KEBOOLA_STACK_URL from environment, table list from DuckDB registry.
"""
from app.logging_config import setup_logging
setup_logging(__name__)
# Read Keboola credentials — env first, then instance.yaml fallback
url = os.environ.get("KEBOOLA_STACK_URL", "")
token = os.environ.get("KEBOOLA_STORAGE_TOKEN", "")
if not url or not token:
try:
from config.loader import load_instance_config
config = load_instance_config()
kbc_config = config.get("keboola", {})
url = url or kbc_config.get("url", "")
token_env = kbc_config.get("token_env", "KEBOOLA_STORAGE_TOKEN")
token = token or os.environ.get(token_env, "")
except Exception:
pass
if not url or not token:
logger.error("Missing KEBOOLA_STACK_URL or KEBOOLA_STORAGE_TOKEN")
exit(1)
# Read table list from registry
from src.db import get_system_db
from src.repositories.table_registry import TableRegistryRepository
sys_conn = get_system_db()
try:
repo = TableRegistryRepository(sys_conn)
tables = repo.list_by_source("keboola")
finally:
sys_conn.close()
if not tables:
logger.warning("No Keboola tables registered in table_registry")
exit(0)
logger.info("Extracting %d tables from %s", len(tables), url)
data_dir = Path(os.environ.get("DATA_DIR", "./data"))
result = run(str(data_dir / "extracts" / "keboola"), tables, url, token)
logger.info("Extraction complete: %s", result)
code = compute_exit_code(result, len(tables))
if code == 2:
logger.error("Partial failure: %d of %d tables failed", result.get("tables_failed", 0), len(tables))
elif code == 1:
logger.error("All %d tables failed", len(tables))
exit(code)