f0979f997a
E2E testing showed admin POSTs of materialized BQ rows whose source_query uses BigQuery-native backtick identifiers (`prj.ds.t`) silently no-op'd at the next sync tick — the materialize path runs the SQL through the DuckDB BQ extension's COPY which uses DuckDB's parser; backticks aren't recognized and the query either parse-errors or matches zero rows. No parquet lands at the canonical path and no error reaches an operator-visible surface. Two-part fix: 1. RegisterTableRequest's _check_mode_query_coherence model_validator now rejects any source_query containing a backtick with a 422 + actionable message pointing at the DuckDB equivalent (bq."dataset"."table"). Same check is applied in update_table on the merged record so PATCHes that flip a stored source_query to backtick form are also caught. Covers BQ AND Keboola materialized rows since both connectors funnel source_query through DuckDB's COPY. 2. _run_materialized_pass now persists per-row failures via the new SyncStateRepository.set_error / clear_error methods (existing sync_state.error / status columns — no schema migration). GET /api/admin/registry enriches each row with `last_sync_error` from a single batched SELECT against sync_state, so the admin UI / da admin status can show "this table failed last sync because: X" instead of operators having to trawl scheduler logs. Recovered rows have the error cleared automatically — update_sync's success path resets status='ok' / error=NULL on the upsert. The materialized-path test fixture's _materialized_payload helper is updated to use DuckDB-flavor SQL (the prior backtick example pre-dated the fix). 6 new tests cover register/update rejection on BQ + Keboola, the sync_state error persistence, and the registry response surface.
705 lines
31 KiB
Python
705 lines
31 KiB
Python
"""Sync endpoints — manifest, trigger, sync-settings, table-subscriptions."""
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import hashlib
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import logging
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import os
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import subprocess
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import traceback
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from datetime import datetime, timezone
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from pathlib import Path
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from typing import Optional, List
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from fastapi import APIRouter, Depends, HTTPException, BackgroundTasks
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from pydantic import BaseModel
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import duckdb
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from app.auth.access import require_admin
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from app.auth.dependencies import get_current_user, _get_db
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from app.utils import get_data_dir as _get_data_dir
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from src.repositories.sync_state import SyncStateRepository
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from src.repositories.sync_settings import SyncSettingsRepository
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from src.repositories.table_registry import TableRegistryRepository
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from src.rbac import can_access_table
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from src.scheduler import filter_due_tables
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/api/sync", tags=["sync"])
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def _file_hash(path: Path) -> str:
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if not path.exists():
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return ""
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h = hashlib.md5()
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with open(path, "rb") as f:
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for chunk in iter(lambda: f.read(8192), b""):
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h.update(chunk)
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return h.hexdigest()
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def _materialize_table(
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*,
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table_id: str,
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sql: str,
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bq,
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output_dir: str,
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max_bytes: Optional[int],
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) -> dict:
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"""Thin wrapper around `connectors.bigquery.extractor.materialize_query`
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so the trigger pass can be unit-tested by patching this seam without
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touching the real BqAccess factory or the duckdb import."""
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from connectors.bigquery.extractor import materialize_query
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return materialize_query(
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table_id=table_id, sql=sql, bq=bq,
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output_dir=output_dir, max_bytes=max_bytes,
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)
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def _run_materialized_pass(conn: duckdb.DuckDBPyConnection, bq) -> dict:
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"""Walk `table_registry` for `query_mode='materialized'` rows and run any
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that are due, dispatching by ``source_type`` to the correct connector's
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materialize_query. Honors per-table `sync_schedule` via `is_table_due()`,
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computes the file hash inline, and updates `sync_state` so the manifest
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can serve the row to `da sync` without re-hashing on every request.
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BigQuery rows go through BqAccess + bigquery_query() (jobs API),
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optionally cost-guarded by ``max_bytes_per_materialize``.
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Keboola rows go through KeboolaAccess + ATTACH-and-COPY, no
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guardrail (extension has no dry-run primitive).
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Returns:
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``{"materialized": [ids], "skipped": [ids], "errors": [{table, error}]}``
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Errors are aggregated per row — one budget-blown table doesn't stop a
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healthy sibling. ``MaterializeBudgetError`` is caught and rendered with
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its structured fields so operator alerting can pick out the cap-vs-actual
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bytes from the log line.
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"""
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from src.scheduler import is_table_due
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from app.instance_config import get_value
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from connectors.bigquery.extractor import MaterializeBudgetError
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bq_output_dir = str(Path(_get_data_dir()) / "extracts" / "bigquery")
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kb_output_dir = Path(_get_data_dir()) / "extracts" / "keboola" / "data"
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# Sentinel: max_bytes <= 0 (or None) disables the guardrail. `get_value()`
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# treats YAML `null` as "missing" → returns the default; operators must use
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# the explicit `0` sentinel to disable. See config/instance.yaml.example.
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# YAML accepts floats too (e.g. `10737418240.0`), and operators may
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# write `1e10` for readability; coerce to int and tolerate non-numeric
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# entries by falling through to the disable path with a warning.
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raw_max = get_value(
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"data_source", "bigquery", "max_bytes_per_materialize",
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default=10 * 2**30,
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)
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try:
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n = int(raw_max) if raw_max is not None else 0
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except (TypeError, ValueError):
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logger.warning(
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"data_source.bigquery.max_bytes_per_materialize is not numeric "
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"(%r); cost guardrail disabled. Set an integer or 0 to disable.",
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raw_max,
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)
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n = 0
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bq_max_bytes = n if n > 0 else None
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registry = TableRegistryRepository(conn)
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state = SyncStateRepository(conn)
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summary = {"materialized": [], "skipped": [], "errors": []}
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keboola_access = None # lazy-init on first Keboola row
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for row in registry.list_all():
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if row.get("query_mode") != "materialized":
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continue
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# Convention across connectors: sync_state.table_id and the parquet
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# filename are keyed by `table_registry.name` (matches Keboola's
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# `_meta.table_name`) so the manifest's `registry_by_name` lookup
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# at `_build_manifest_for_user` resolves cleanly. Without this,
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# admins who register `name="Orders_90d"` (id slugified to
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# `orders_90d`) would see `query_mode` default to `"local"` in the
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# manifest because the lookup misses on `id`.
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ref_name = row["name"]
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last = state.get_last_sync(ref_name)
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last_iso = last.isoformat() if last else None
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schedule = row.get("sync_schedule") or "every 1h"
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if not is_table_due(schedule, last_iso):
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summary["skipped"].append(ref_name)
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continue
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source_type = row.get("source_type") or "bigquery" # legacy default
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# Dispatch by source_type. BQ rows keep using `_materialize_table`
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# (the existing test seam); Keboola rows use the new Keboola
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# materialize_query via a lazily-initialized KeboolaAccess.
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try:
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if source_type == "bigquery":
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stats = _materialize_table(
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table_id=ref_name,
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sql=row["source_query"],
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bq=bq,
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output_dir=bq_output_dir,
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max_bytes=bq_max_bytes,
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)
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elif source_type == "keboola":
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if keboola_access is None:
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from connectors.keboola.access import KeboolaAccess
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keboola_url = get_value(
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"data_source", "keboola", "stack_url", default=""
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) or ""
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token_env = get_value(
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"data_source", "keboola", "token_env",
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default="KEBOOLA_STORAGE_TOKEN",
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) or "KEBOOLA_STORAGE_TOKEN"
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keboola_token = os.environ.get(token_env, "")
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if not (keboola_url and keboola_token):
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summary["errors"].append({
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"table": ref_name,
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"error": (
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"Keboola URL/token not configured for "
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"materialized path (data_source.keboola.stack_url "
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f"+ env {token_env})"
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),
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})
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continue
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keboola_access = KeboolaAccess(
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url=keboola_url, token=keboola_token,
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)
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kb_output_dir.mkdir(parents=True, exist_ok=True)
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from connectors.keboola.extractor import (
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materialize_query as kb_materialize_query,
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)
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kb_stats = kb_materialize_query(
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table_id=ref_name,
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sql=row["source_query"],
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keboola_access=keboola_access,
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output_dir=kb_output_dir,
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)
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# Normalize Keboola materialize_query output to the shape the
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# BQ branch uses for downstream sync_state updates. KB returns
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# {table_id, path, rows, bytes, md5}; map to
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# {rows, size_bytes, hash}.
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stats = {
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"rows": kb_stats["rows"],
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"size_bytes": kb_stats["bytes"],
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"hash": kb_stats["md5"],
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"query_mode": "materialized",
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}
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else:
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summary["errors"].append({
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"table": ref_name,
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"error": (
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f"materialized path not supported for "
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f"source_type={source_type!r}"
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),
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})
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continue
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except MaterializeBudgetError as e:
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logger.warning(
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"Materialize cap exceeded for %s: %s bytes > %s bytes",
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e.table_id, f"{e.current:,}", f"{e.limit:,}",
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)
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summary["errors"].append({
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"table": ref_name,
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"error": str(e),
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"current": e.current,
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"limit": e.limit,
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})
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# Persist the failure so `GET /api/admin/registry` can surface
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# `last_sync_error` to the admin UI / `da admin status`.
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# Without this, scheduler stderr was the only place the cap
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# failure showed up and operators had no API path to it.
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state.set_error(ref_name, str(e))
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continue
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except Exception as e:
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logger.exception("Materialize failed for %s", ref_name)
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summary["errors"].append({"table": ref_name, "error": str(e)})
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state.set_error(ref_name, str(e))
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continue
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# `materialize_query` returns the parquet's MD5 inline — hashing
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# there means we don't re-read a multi-GB file on the request
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# thread. Fallback to `_file_hash(parquet_path)` if for some
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# reason the stats dict didn't carry it (defensive).
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parquet_hash = stats.get("hash")
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if not parquet_hash:
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output_dir_for_hash = (
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bq_output_dir if source_type == "bigquery" else str(kb_output_dir.parent)
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)
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parquet_path = Path(output_dir_for_hash) / "data" / f"{ref_name}.parquet"
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parquet_hash = _file_hash(parquet_path)
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# `update_sync` resets `status='ok'` / `error=NULL` on the upsert
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# path (its argument defaults), so a row that previously errored
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# has the failure cleared by this call. No separate clear_error
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# needed here — the test invariant is that a successful materialize
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# leaves status='ok' and error='', which `update_sync` already
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# establishes.
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state.update_sync(
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table_id=ref_name,
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rows=stats["rows"],
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file_size_bytes=stats["size_bytes"],
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hash=parquet_hash,
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)
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summary["materialized"].append(ref_name)
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return summary
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def _run_sync(tables: Optional[List[str]] = None):
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"""Run extractor as subprocess + orchestrator rebuild.
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Reads table configs from DuckDB (in main process which has the shared
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connection), passes them as JSON via stdin to the extractor subprocess.
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This avoids DuckDB lock conflicts — subprocess never opens system.duckdb.
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"""
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import json as _json
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import sys
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try:
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from app.instance_config import get_data_source_type, get_value
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from src.db import get_system_db
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source_type = get_data_source_type()
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data_dir = _get_data_dir()
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# Read table configs in main process (has shared DuckDB connection)
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sys_conn = get_system_db()
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# Track whether the REGISTRY (not the post-filter list) was empty.
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# Auto-discovery must only fire on a truly empty registry; if the
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# filter returned [] because nothing was due, re-discovering would
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# bypass the schedule entirely on Keboola instances. (Devin BUG_0001
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# on ebb8cc9.)
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registry_has_tables = False
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try:
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repo = TableRegistryRepository(sys_conn)
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if tables:
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# Manual operator override — bypass schedule filter entirely
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# so an admin saying "sync these specific tables now" wins.
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all_configs = [repo.get(t) for t in tables]
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table_configs = [c for c in all_configs if c is not None]
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registry_has_tables = bool(table_configs)
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else:
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table_configs = repo.list_local(source_type) if source_type else repo.list_local()
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registry_has_tables = bool(table_configs)
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# Without this filter, every scheduler tick would re-sync
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# every table regardless of its sync_schedule cadence,
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# making the field a no-op at trigger time. Tables with
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# no schedule pass through unchanged (opt-in feature).
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state_repo = SyncStateRepository(sys_conn)
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table_configs = filter_due_tables(table_configs, state_repo)
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finally:
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sys_conn.close()
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if not table_configs:
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# Auto-discover tables on first sync when registry is empty.
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# `not registry_has_tables` is the load-bearing guard — without
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# it, "filter excluded everything" looks identical to "registry
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# empty" and we'd re-discover + re-sync every tick regardless of
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# sync_schedule.
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if not registry_has_tables and source_type == "keboola" and os.environ.get("KEBOOLA_STORAGE_TOKEN"):
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logger.info("No tables registered — running auto-discovery from Keboola")
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try:
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from app.api.admin import _discover_and_register_tables
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auto_conn = get_system_db()
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try:
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result = _discover_and_register_tables(auto_conn, "auto-discovery")
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logger.info("Auto-discovered %d tables, skipped %d", result["registered"], result["skipped"])
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finally:
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auto_conn.close()
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# Re-read table configs after auto-registration
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sys_conn2 = get_system_db()
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try:
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table_configs = TableRegistryRepository(sys_conn2).list_local(source_type)
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finally:
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sys_conn2.close()
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except Exception as e:
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logger.warning("Auto-discovery failed: %s", e)
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# CRITICAL: don't early-return when local-mode tables are empty.
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# `list_local("bigquery")` is always empty on BQ-only deployments
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# (BQ rows are always remote or materialized, never local), so an
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# early return would prevent the materialized pass AND the
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# orchestrator rebuild from ever firing on a BQ-only instance.
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# Devin BUG_0002 on PR #148 commit 2fa44f2. Just flag whether the
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# Keboola subprocess + custom-connectors should run; everything
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# below (materialized pass, orchestrator rebuild, profiler) runs
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# unconditionally so a registry with materialized rows but no
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# local rows still publishes them.
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run_extractor_subprocess = bool(table_configs)
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if not run_extractor_subprocess:
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logger.info(
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"No local-mode tables to sync for source_type=%s — "
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"skipping extractor subprocess; materialized pass + "
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"orchestrator rebuild still run.",
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source_type,
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)
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env = {**os.environ}
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import sys as _sys
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if run_extractor_subprocess:
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# Serialize configs — strip non-serializable fields
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serializable = []
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for tc in table_configs:
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serializable.append({k: (v.isoformat() if hasattr(v, 'isoformat') else v)
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for k, v in tc.items() if v is not None})
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# Run extractor subprocess with table configs via stdin
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# Subprocess does NOT open system.duckdb — no lock conflict
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cmd = [sys.executable, "-c", """
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import json, sys, os, logging
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from pathlib import Path
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# Subprocess inherits no logging config — without basicConfig, Python's
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# lastResort handler only surfaces WARNING+ to stderr and INFO-level
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# extraction progress from connectors.keboola.extractor.run() is silently
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# dropped. capture_output=True in the parent then swallows the rest.
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# Devin BUG_0002 on PR #136 review.
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logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s")
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configs = json.load(sys.stdin)
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url = os.environ.get("KEBOOLA_STACK_URL", "")
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token = os.environ.get("KEBOOLA_STORAGE_TOKEN", "")
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if not url or not token:
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print("ERROR: Missing KEBOOLA_STACK_URL or KEBOOLA_STORAGE_TOKEN", file=sys.stderr)
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sys.exit(1)
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from connectors.keboola.extractor import run, compute_exit_code
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data_dir = Path(os.environ.get("DATA_DIR", "./data"))
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result = run(str(data_dir / "extracts" / "keboola"), configs, url, token)
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print(json.dumps(result))
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# Issue #81 Group B: surface partial-failure as exit 2 so the API
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# caller can distinguish "every table failed" from "9/10 succeeded".
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sys.exit(compute_exit_code(result, len(configs)))
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"""]
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print(f"[SYNC] Starting extractor subprocess for {len(table_configs)} tables", file=_sys.stderr, flush=True)
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try:
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result = subprocess.run(
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cmd, input=_json.dumps(serializable), capture_output=True, text=True,
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timeout=1800, env=env,
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cwd=str(Path(__file__).parent.parent.parent),
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)
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except subprocess.TimeoutExpired:
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# Catch the timeout LOCALLY so the materialized BQ pass and
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# orchestrator rebuild below still fire. Pre-fix the timeout
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# propagated to the outer except handler and skipped the rest
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# of `_run_sync` — on a dual-source deployment a slow Keboola
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# extractor would silently block all materialized parquets +
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# master-view rebuild until the next trigger. Devin BUG_0001
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# on PR #148 commit 2219255. Mirrors the per-custom-connector
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# timeout pattern below (line ~347).
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print(
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"[SYNC] Extractor timed out after 1800s — continuing to "
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"materialized pass + orchestrator rebuild",
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file=_sys.stderr, flush=True,
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)
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result = None
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if result is not None:
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if result.stdout:
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print(f"[SYNC] Extractor stdout: {result.stdout.strip()[-500:]}", file=_sys.stderr, flush=True)
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if result.stderr:
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print(f"[SYNC] Extractor stderr: {result.stderr[-500:]}", file=_sys.stderr, flush=True)
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# Issue #81 Group B: three exit codes. 0 = full success,
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# 1 = full failure, 2 = partial. Partial is a data-quality
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# alert, not a crash — the orchestrator's per-table _meta
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# machinery already captured which tables succeeded; we just
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# need to log loudly so operator alerting can pick it up.
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if result.returncode == 0:
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print(f"[SYNC] Extractor OK", file=_sys.stderr, flush=True)
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elif result.returncode == 2:
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print(
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f"[SYNC] Extractor PARTIAL FAILURE (exit 2) — some tables "
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f"succeeded, some failed; see stderr for per-table errors. "
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f"Successful tables will still be published by the orchestrator.",
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file=_sys.stderr, flush=True,
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)
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else:
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print(f"[SYNC] Extractor FAILED (exit {result.returncode})", file=_sys.stderr, flush=True)
|
|
|
|
# Run custom connectors (Tier A: local mount) — only when there
|
|
# were local-mode tables to drive the extractor. Custom connectors
|
|
# currently piggyback on the same env as the Keboola extractor.
|
|
connectors_dir = Path(os.environ.get("CONNECTORS_DIR", str(Path(__file__).parent.parent.parent / "connectors" / "custom")))
|
|
if connectors_dir.exists():
|
|
for connector_dir in sorted(connectors_dir.iterdir()):
|
|
if not connector_dir.is_dir():
|
|
continue
|
|
extractor = connector_dir / "extractor.py"
|
|
if not extractor.exists():
|
|
continue
|
|
logger.info("Running custom connector: %s", connector_dir.name)
|
|
try:
|
|
custom_result = subprocess.run(
|
|
[sys.executable, str(extractor)],
|
|
env=env, capture_output=True, text=True, timeout=600,
|
|
cwd=str(Path(__file__).parent.parent.parent),
|
|
)
|
|
if custom_result.returncode != 0:
|
|
logger.error("Custom connector %s failed: %s", connector_dir.name, custom_result.stderr[-500:])
|
|
else:
|
|
logger.info("Custom connector %s completed", connector_dir.name)
|
|
except subprocess.TimeoutExpired:
|
|
logger.error("Custom connector %s timed out", connector_dir.name)
|
|
|
|
# Materialized SQL pass — runs admin-registered SQL through the
|
|
# source's DuckDB extension (BQ via BqAccess, Keboola via
|
|
# KeboolaAccess) and writes parquet for due rows. _run_materialized_pass
|
|
# itself dispatches by source_type, so we always run it regardless of
|
|
# which (or both) source types have a `project` / `stack_url` set —
|
|
# Keboola-only instances would otherwise silently skip Keboola
|
|
# materialized rows just because no BQ project is configured (Devin
|
|
# finding 2026-05-01: BUG_pr-review-job-3fbd31c9_0001). The BQ
|
|
# branch inside _run_materialized_pass uses a per-row try/except so
|
|
# the sentinel BqAccess (not_configured) raises a typed error that
|
|
# gets recorded against that row only — no cascade.
|
|
try:
|
|
from connectors.bigquery.access import get_bq_access
|
|
from src.db import get_system_db as _get_system_db
|
|
bq_access = get_bq_access() # sentinel if no BQ project; OK
|
|
mat_conn = _get_system_db()
|
|
try:
|
|
mat_summary = _run_materialized_pass(mat_conn, bq_access)
|
|
finally:
|
|
mat_conn.close()
|
|
print(
|
|
f"[SYNC] Materialized SQL: {len(mat_summary['materialized'])} ok, "
|
|
f"{len(mat_summary['skipped'])} skipped, "
|
|
f"{len(mat_summary['errors'])} errors",
|
|
file=_sys.stderr, flush=True,
|
|
)
|
|
for err in mat_summary["errors"]:
|
|
print(
|
|
f"[SYNC] {err['table']}: {err['error']}",
|
|
file=_sys.stderr, flush=True,
|
|
)
|
|
except Exception as e:
|
|
print(
|
|
f"[SYNC] Materialized SQL pass FAILED: {e}",
|
|
file=_sys.stderr, flush=True,
|
|
)
|
|
traceback.print_exc()
|
|
|
|
# Rebuild master views (reads extract.duckdb files, no write conflict)
|
|
from src.orchestrator import SyncOrchestrator
|
|
orch = SyncOrchestrator()
|
|
views = orch.rebuild()
|
|
print(f"[SYNC] Orchestrator rebuild: {{{', '.join(f'{k}: {len(v)}' for k, v in views.items())}}}", file=_sys.stderr, flush=True)
|
|
|
|
# Auto-profile synced tables (best-effort, don't fail sync on profile error)
|
|
try:
|
|
from src.profiler import profile_table, TableInfo
|
|
from src.repositories.profiles import ProfileRepository
|
|
|
|
data_dir = Path(os.environ.get("DATA_DIR", "./data"))
|
|
extracts_dir = data_dir / "extracts"
|
|
|
|
sys_conn = get_system_db()
|
|
try:
|
|
profile_repo = ProfileRepository(sys_conn)
|
|
profiled = 0
|
|
for source_name, table_names in views.items():
|
|
for table_name in table_names[:10]: # Limit per sync
|
|
pq_path = extracts_dir / source_name / "data" / f"{table_name}.parquet"
|
|
if not pq_path.exists():
|
|
continue
|
|
try:
|
|
table_info = TableInfo(name=table_name, table_id=table_name)
|
|
profile = profile_table(table_info, pq_path, [], {}, {})
|
|
profile_repo.save(table_name, profile)
|
|
profiled += 1
|
|
except Exception as pe:
|
|
print(f"[SYNC] Profile {table_name}: {pe}", file=_sys.stderr, flush=True)
|
|
print(f"[SYNC] Profiled {profiled} tables", file=_sys.stderr, flush=True)
|
|
finally:
|
|
sys_conn.close()
|
|
except Exception as e:
|
|
print(f"[SYNC] Profiler skipped: {e}", file=_sys.stderr, flush=True)
|
|
|
|
except subprocess.TimeoutExpired:
|
|
print("[SYNC] Extractor timed out after 1800s", file=_sys.stderr, flush=True)
|
|
except Exception as e:
|
|
print(f"[SYNC] FAILED: {e}", file=_sys.stderr, flush=True)
|
|
traceback.print_exc()
|
|
|
|
|
|
# ---- Manifest ----
|
|
|
|
def _build_manifest_for_user(conn, user: dict) -> dict:
|
|
"""Build manifest dict filtered by user's accessible tables.
|
|
|
|
Joins ``sync_state`` with ``table_registry`` so each table entry exposes
|
|
``query_mode`` and ``source_type``. The CLI uses these to decide whether
|
|
to download a parquet (local) or skip it (remote, e.g. BigQuery views).
|
|
|
|
Defensive defaults: if a sync_state row has no matching registry entry
|
|
(race / manual deletion), fall back to ``query_mode='local'`` and
|
|
``source_type=''`` so the manifest still serializes cleanly.
|
|
"""
|
|
sync_repo = SyncStateRepository(conn)
|
|
table_repo = TableRegistryRepository(conn)
|
|
all_states = sync_repo.get_all_states()
|
|
# `sync_state.table_id` is sourced from `_meta.table_name` which equals
|
|
# `table_registry.name`, NOT `table_registry.id`. Auto-discovered Keboola
|
|
# tables and manually-registered ones with mixed-case/spaced names produce
|
|
# id != name; an id-keyed lookup would miss them and silently default to
|
|
# `query_mode=local`, causing the CLI to try downloading remote tables.
|
|
registry_by_name = {t["name"]: t for t in table_repo.list_all()}
|
|
|
|
# Filter by user's accessible tables. `can_access_table` has its own
|
|
# admin shortcut (Admin group → True). Lookup translates name→id first
|
|
# because `s["table_id"]` is sourced from `_meta.table_name` = registry
|
|
# `name` while `can_access_table` keys on registry `id`; when id != name
|
|
# an id-keyed call would miss.
|
|
def _id_for(state):
|
|
reg = registry_by_name.get(state["table_id"])
|
|
return reg["id"] if reg else state["table_id"]
|
|
all_states = [s for s in all_states if can_access_table(user, _id_for(s), conn)]
|
|
|
|
data_dir = _get_data_dir()
|
|
tables = {}
|
|
for state in all_states:
|
|
table_id = state["table_id"]
|
|
reg = registry_by_name.get(table_id, {})
|
|
tables[table_id] = {
|
|
"hash": state.get("hash", ""),
|
|
"updated": state.get("last_sync").isoformat() if state.get("last_sync") else None,
|
|
"size_bytes": state.get("file_size_bytes", 0),
|
|
"rows": state.get("rows", 0),
|
|
"query_mode": reg.get("query_mode") or "local",
|
|
"source_type": reg.get("source_type") or "",
|
|
}
|
|
|
|
# Asset hashes
|
|
docs_dir = data_dir / "docs"
|
|
assets = {}
|
|
for asset_name, asset_path in [
|
|
("docs", docs_dir),
|
|
("profiles", data_dir / "src_data" / "metadata" / "profiles.json"),
|
|
]:
|
|
if asset_path.exists():
|
|
if asset_path.is_file():
|
|
assets[asset_name] = {"hash": _file_hash(asset_path)}
|
|
else:
|
|
newest = max(
|
|
(f.stat().st_mtime for f in asset_path.rglob("*") if f.is_file()),
|
|
default=0,
|
|
)
|
|
assets[asset_name] = {"hash": str(int(newest))}
|
|
|
|
return {
|
|
"tables": tables,
|
|
"assets": assets,
|
|
"server_time": datetime.now(timezone.utc).isoformat(),
|
|
}
|
|
|
|
|
|
@router.get("/manifest")
|
|
async def sync_manifest(
|
|
user: dict = Depends(get_current_user),
|
|
conn: duckdb.DuckDBPyConnection = Depends(_get_db),
|
|
):
|
|
"""Return hash-based manifest of all synced data, filtered per user."""
|
|
return _build_manifest_for_user(conn, user)
|
|
|
|
|
|
# ---- Trigger ----
|
|
|
|
@router.post("/trigger")
|
|
async def trigger_sync(
|
|
background_tasks: BackgroundTasks,
|
|
tables: Optional[List[str]] = None,
|
|
user: dict = Depends(require_admin),
|
|
):
|
|
"""Trigger data sync from configured source. Admin only. Runs in background."""
|
|
background_tasks.add_task(_run_sync, tables)
|
|
return {
|
|
"status": "triggered",
|
|
"tables": tables or "all",
|
|
"message": "Data sync started in background. Check /api/health for progress.",
|
|
}
|
|
|
|
|
|
# ---- Sync Settings (dataset subscriptions) ----
|
|
|
|
class SyncSettingsUpdate(BaseModel):
|
|
datasets: dict # {dataset_name: bool}
|
|
|
|
|
|
@router.get("/settings")
|
|
async def get_sync_settings(
|
|
user: dict = Depends(get_current_user),
|
|
conn: duckdb.DuckDBPyConnection = Depends(_get_db),
|
|
):
|
|
"""Get user's dataset sync settings."""
|
|
repo = SyncSettingsRepository(conn)
|
|
settings = repo.get_user_settings(user["id"])
|
|
enabled = repo.get_enabled_datasets(user["id"])
|
|
return {
|
|
"user_id": user["id"],
|
|
"settings": settings,
|
|
"enabled_datasets": enabled,
|
|
}
|
|
|
|
|
|
@router.post("/settings")
|
|
async def update_sync_settings(
|
|
request: SyncSettingsUpdate,
|
|
user: dict = Depends(get_current_user),
|
|
conn: duckdb.DuckDBPyConnection = Depends(_get_db),
|
|
):
|
|
"""Update user's dataset sync settings.
|
|
|
|
A dataset can only be enabled when the user has access (via
|
|
``resource_grants(group, "table", dataset)`` or Admin membership). The
|
|
user_sync_settings layer is per-user preference, not authorization —
|
|
the gate stops users from enabling sync on tables they cannot read.
|
|
"""
|
|
from app.auth.access import can_access
|
|
from app.resource_types import ResourceType
|
|
|
|
settings_repo = SyncSettingsRepository(conn)
|
|
results = {}
|
|
for dataset, enabled in request.datasets.items():
|
|
if not can_access(user["id"], ResourceType.TABLE.value, dataset, conn):
|
|
results[dataset] = {"error": "no permission"}
|
|
continue
|
|
settings_repo.set_dataset_enabled(user["id"], dataset, enabled)
|
|
results[dataset] = {"enabled": enabled}
|
|
|
|
return {"updated": results}
|
|
|
|
|
|
# ---- Table Subscriptions ----
|
|
|
|
class TableSubscriptionUpdate(BaseModel):
|
|
table_mode: str = "all" # "all" or "explicit"
|
|
tables: dict = {} # {table_name: bool}
|
|
|
|
|
|
@router.get("/table-subscriptions")
|
|
async def get_table_subscriptions(
|
|
user: dict = Depends(get_current_user),
|
|
conn: duckdb.DuckDBPyConnection = Depends(_get_db),
|
|
):
|
|
"""Get user's per-table subscription settings."""
|
|
repo = SyncSettingsRepository(conn)
|
|
settings = repo.get_user_settings(user["id"])
|
|
return {"user_id": user["id"], "subscriptions": settings}
|
|
|
|
|
|
@router.post("/table-subscriptions")
|
|
async def update_table_subscriptions(
|
|
request: TableSubscriptionUpdate,
|
|
user: dict = Depends(get_current_user),
|
|
conn: duckdb.DuckDBPyConnection = Depends(_get_db),
|
|
):
|
|
"""Update per-table subscription preferences."""
|
|
repo = SyncSettingsRepository(conn)
|
|
for table_name, enabled in request.tables.items():
|
|
repo.set_dataset_enabled(user["id"], table_name, enabled)
|
|
return {"table_mode": request.table_mode, "updated": len(request.tables)}
|