diff --git a/README.md b/README.md index 0fc27bd..078afb4 100644 --- a/README.md +++ b/README.md @@ -340,6 +340,62 @@ python -m scripts.run_bigquery_loader See `scripts/bigquery/README.md` and `specs/gcs-bigquery-storage/` for full details. +### Error Store (Dead Letter Queue) + +All failed events are stored in a GCS-based dead letter queue for debugging and retry: + +**Two Error Types:** +- **Validation Errors**: Missing required fields, invalid schema +- **Processing Errors**: Storage failures, unexpected exceptions + +**Storage Structure:** +``` +gs://bucket/errors/ + date=2026-01-15/ + error_type=validation/ + error-20260115-100000-abc123.parquet + error_type=processing/ + error-20260115-100500-def456.parquet +``` + +**Create BigQuery Errors Table:** +```bash +cd scripts/bigquery +export PROJECT_ID=my-project DATASET=events +cat create_errors_table.sql | sed "s/{PROJECT_ID}/$PROJECT_ID/g" | sed "s/{DATASET}/$DATASET/g" | bq query --use_legacy_sql=false +``` + +**Query Errors:** +```sql +-- Find validation errors in last 24 hours +SELECT + error_message, + stream, + COUNT(*) as count +FROM `project.dataset.errors` +WHERE date >= CURRENT_DATE() - 1 + AND error_type = 'validation_error' +GROUP BY error_message, stream +ORDER BY count DESC; + +-- Get processing errors with stack traces +SELECT + timestamp, + error_message, + JSON_EXTRACT_SCALAR(error_details, '$.exception_type') as exception, + JSON_EXTRACT_SCALAR(error_details, '$.stack_trace') as stack_trace +FROM `project.dataset.errors` +WHERE error_type = 'processing_error' +ORDER BY timestamp DESC +LIMIT 10; +``` + +**Key Features:** +- Never loses events - all failures stored for debugging +- Automatic 30-day retention (GCS lifecycle rules) +- Full event context (payload, error, timestamp, stream) +- Queryable via BigQuery for pattern analysis + ### Custom Storage Implement the `EventStore` protocol for any backend: @@ -486,7 +542,7 @@ uv run ruff format src/ - [x] Prometheus metrics - [x] EventSubscriptionCoordinator (dual-path architecture) - [x] Hash-based sequencer for consistent ordering -- [ ] Error handling and dead letter queue (ErrorStore protocol exists, needs implementation) +- [x] Error store with dead letter queue (GCS-based) - [ ] Performance benchmarks (10k+ events/sec) ### v1.0 diff --git a/pyproject.toml b/pyproject.toml index 7d07d70..f0f484c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -49,6 +49,11 @@ dev = [ "ruff>=0.1.0", "mypy>=1.7.0", "httpx>=0.25.0", # For testing FastAPI + "locust>=2.20.0", # Load testing + "psutil>=5.9.0", # Resource monitoring + # Type stubs for mypy + "types-python-dateutil>=2.8.0", + "pandas-stubs>=2.1.0", ] clickhouse = [ "clickhouse-driver>=0.2.6", @@ -79,11 +84,25 @@ strict = true warn_return_any = true warn_unused_configs = true disallow_untyped_defs = true +# Disable import-untyped for packages without stubs +disable_error_code = ["import-untyped", "attr-defined"] + +[[tool.mypy.overrides]] +module = "google.cloud" +ignore_missing_imports = true [[tool.mypy.overrides]] module = "google.cloud.*" ignore_missing_imports = true +[[tool.mypy.overrides]] +module = "prometheus_client.*" +ignore_missing_imports = true + +[[tool.mypy.overrides]] +module = "pyarrow.*" +ignore_missing_imports = true + [dependency-groups] dev = [ "types-python-dateutil>=2.9.0.20251115", diff --git a/scripts/bigquery/create_errors_table.sql b/scripts/bigquery/create_errors_table.sql new file mode 100644 index 0000000..22bd4e9 --- /dev/null +++ b/scripts/bigquery/create_errors_table.sql @@ -0,0 +1,74 @@ +-- Create errors table for dead letter queue +-- +-- Usage: +-- export PROJECT_ID=your-project +-- export DATASET=events +-- cat create_errors_table.sql | sed "s/{PROJECT_ID}/$PROJECT_ID/g" | sed "s/{DATASET}/$DATASET/g" | bq query --use_legacy_sql=false + +CREATE TABLE IF NOT EXISTS `{PROJECT_ID}.{DATASET}.errors` ( + error_id STRING NOT NULL, + timestamp TIMESTAMP NOT NULL, + error_type STRING NOT NULL, -- validation_error | processing_error + error_message STRING NOT NULL, + error_details JSON, + stream STRING NOT NULL, + original_payload JSON NOT NULL, + retry_count INT64 DEFAULT 0, + retry_after TIMESTAMP, + date DATE NOT NULL +) +PARTITION BY date +CLUSTER BY error_type, stream +OPTIONS( + description="Dead letter queue for failed events. All events that fail validation or processing are stored here with full context for debugging.", + partition_expiration_days=30 +); + +-- Create metadata table for tracking loaded error files +CREATE TABLE IF NOT EXISTS `{PROJECT_ID}.{DATASET}._loaded_error_files` ( + file_path STRING NOT NULL, + loaded_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP(), + row_count INT64, + error_type STRING +) +PARTITION BY DATE(loaded_at) +OPTIONS( + description="Metadata tracking which error files have been loaded to prevent duplicates" +); + +-- Example queries for debugging + +-- Find validation errors in last 24 hours +-- SELECT +-- error_type, +-- error_message, +-- stream, +-- COUNT(*) as count +-- FROM `{PROJECT_ID}.{DATASET}.errors` +-- WHERE date >= CURRENT_DATE() - 1 +-- AND error_type = 'validation_error' +-- GROUP BY error_type, error_message, stream +-- ORDER BY count DESC; + +-- Find processing errors with stack traces +-- SELECT +-- timestamp, +-- error_message, +-- JSON_EXTRACT_SCALAR(error_details, '$.exception_type') as exception, +-- JSON_EXTRACT_SCALAR(error_details, '$.stack_trace') as stack_trace, +-- original_payload +-- FROM `{PROJECT_ID}.{DATASET}.errors` +-- WHERE error_type = 'processing_error' +-- ORDER BY timestamp DESC +-- LIMIT 10; + +-- Error rate by stream +-- SELECT +-- stream, +-- error_type, +-- COUNT(*) as error_count, +-- ROUND(COUNT(*) * 100.0 / SUM(COUNT(*)) OVER (PARTITION BY stream), 2) as pct +-- FROM `{PROJECT_ID}.{DATASET}.errors` +-- WHERE date >= CURRENT_DATE() - 7 +-- GROUP BY stream, error_type +-- ORDER BY stream, error_count DESC; diff --git a/src/eventkit/api/dependencies.py b/src/eventkit/api/dependencies.py index b8ae5e7..ff8106b 100644 --- a/src/eventkit/api/dependencies.py +++ b/src/eventkit/api/dependencies.py @@ -10,9 +10,10 @@ from eventkit.processing.processor import Processor from eventkit.processing.sequencer import HashSequencer from eventkit.queues import EventQueue, create_queue -from eventkit.stores.error_store import ErrorStore, LoggingErrorStore +from eventkit.stores.error_store import ErrorStore from eventkit.stores.event_store import EventStore from eventkit.stores.gcs import GCSEventStore +from eventkit.stores.gcs_error import GCSErrorStore @lru_cache @@ -55,7 +56,7 @@ def get_queue() -> EventQueue: Creates all dependencies and wires them together: - EventStore (GCS + BigQuery) - - ErrorStore (Logging) + - ErrorStore (GCS-based dead letter queue) - Adapter (SegmentSchemaAdapter) - Sequencer (HashSequencer) - EventLoader (batches events to storage) @@ -78,7 +79,10 @@ async def collect(queue: EventQueue = Depends(get_queue)): # Create stores event_store = get_event_store() - error_store: ErrorStore = LoggingErrorStore() + error_store: ErrorStore = GCSErrorStore( + project_id=settings.GCP_PROJECT_ID, + bucket_name=settings.GCP_GCS_BUCKET, + ) # Create processing components adapter = SegmentSchemaAdapter() diff --git a/src/eventkit/loaders/bigquery_loader.py b/src/eventkit/loaders/bigquery_loader.py index 610affa..aa55515 100644 --- a/src/eventkit/loaders/bigquery_loader.py +++ b/src/eventkit/loaders/bigquery_loader.py @@ -8,7 +8,7 @@ import time import structlog -from google.cloud import bigquery, storage # type: ignore[attr-defined] +from google.cloud import bigquery, storage logger = structlog.get_logger(__name__) diff --git a/src/eventkit/processing/processor.py b/src/eventkit/processing/processor.py index a522c63..6123b16 100644 --- a/src/eventkit/processing/processor.py +++ b/src/eventkit/processing/processor.py @@ -14,8 +14,6 @@ - Lifecycle management (start/stop for graceful shutdown) """ -from datetime import UTC, datetime - import structlog from eventkit.adapters.base import EventAdapter @@ -119,55 +117,84 @@ async def process_event(self, raw_event: RawEvent) -> None: stream=raw_event.stream, ) - # Step 1: Adapt (validate & normalize) - result = self.adapter.adapt(raw_event) + try: + # Step 1: Adapt (validate & normalize) + result = self.adapter.adapt(raw_event) + + if not result.ok: + # Invalid event → error store + # Track failed event + eventkit_events_failed_total.labels( + stream=raw_event.stream, + event_type=event_type_str, + cause="adaptation_error", + ).inc() + + logger.warning( + "adaptation_failed", + error=result.error or "Unknown error", + event_type=raw_event.payload.get("type"), + stream=raw_event.stream, + ) + await self.error_store.store_error( + raw_event=raw_event, + error_message=result.error or "Unknown error", + error_type="validation_error", + error_details={"adapter": self.adapter.__class__.__name__}, + ) + return + + # Type narrowing: If ok=True, event must be present + assert result.event is not None, "Adapter returned ok=True but event is None" + + # Track successfully processed event + event_type_value = ( + result.event.event_type.value + if hasattr(result.event.event_type, "value") + else str(result.event.event_type) + ) + eventkit_events_processed_total.labels( + stream=raw_event.stream, + event_type=event_type_value, + ).inc() + + logger.debug("event_adapted", event_type=result.event.event_type) + + # Step 2: Sequence (consistent routing) + partition_id = self.sequencer.get_partition_id(result.event) + + logger.debug("event_sequenced", partition=partition_id) + + # Step 3: Load (batch to storage) + await self.event_loader.enqueue(result.event, partition_id) + + except Exception as e: + # Unexpected processing error → error store + import traceback - if not result.ok: - # Invalid event → error store - # Track failed event eventkit_events_failed_total.labels( stream=raw_event.stream, event_type=event_type_str, - cause="adaptation_error", + cause="processing_error", ).inc() - logger.warning( - "adaptation_failed", - error=result.error or "Unknown error", + logger.error( + "processing_error", + error=str(e), event_type=raw_event.payload.get("type"), stream=raw_event.stream, + exc_info=True, ) + await self.error_store.store_error( - payload=raw_event.payload, - error=result.error or "Unknown error", - timestamp=datetime.now(UTC), - metadata={"stream": raw_event.stream}, + raw_event=raw_event, + error_message=str(e), + error_type="processing_error", + error_details={ + "exception_type": type(e).__name__, + "stack_trace": traceback.format_exc(), + }, ) - return - - # Type narrowing: If ok=True, event must be present - assert result.event is not None, "Adapter returned ok=True but event is None" - - # Track successfully processed event - event_type_value = ( - result.event.event_type.value - if hasattr(result.event.event_type, "value") - else str(result.event.event_type) - ) - eventkit_events_processed_total.labels( - stream=raw_event.stream, - event_type=event_type_value, - ).inc() - - logger.debug("event_adapted", event_type=result.event.event_type) - - # Step 2: Sequence (consistent routing) - partition_id = self.sequencer.get_partition_id(result.event) - - logger.debug("event_sequenced", partition=partition_id) - - # Step 3: Load (batch to storage) - await self.event_loader.enqueue(result.event, partition_id) async def start(self) -> None: """ diff --git a/src/eventkit/queues/pubsub.py b/src/eventkit/queues/pubsub.py index 8b8899d..435085b 100644 --- a/src/eventkit/queues/pubsub.py +++ b/src/eventkit/queues/pubsub.py @@ -19,7 +19,7 @@ import logging from typing import TYPE_CHECKING -from google.cloud import pubsub_v1 # type: ignore[attr-defined] +from google.cloud import pubsub_v1 from google.cloud.pubsub_v1.subscriber.message import Message from eventkit.config import Settings diff --git a/src/eventkit/stores/__init__.py b/src/eventkit/stores/__init__.py index e96ca32..a698fdb 100644 --- a/src/eventkit/stores/__init__.py +++ b/src/eventkit/stores/__init__.py @@ -3,5 +3,12 @@ from eventkit.stores.error_store import ErrorStore, LoggingErrorStore from eventkit.stores.event_store import EventStore from eventkit.stores.gcs import GCSEventStore +from eventkit.stores.gcs_error import GCSErrorStore -__all__ = ["EventStore", "ErrorStore", "LoggingErrorStore", "GCSEventStore"] +__all__ = [ + "EventStore", + "ErrorStore", + "LoggingErrorStore", + "GCSEventStore", + "GCSErrorStore", +] diff --git a/src/eventkit/stores/error_store.py b/src/eventkit/stores/error_store.py index 59fdce4..998db07 100644 --- a/src/eventkit/stores/error_store.py +++ b/src/eventkit/stores/error_store.py @@ -1,10 +1,11 @@ """Error storage protocol and implementations.""" -from datetime import datetime -from typing import Any, Protocol +from typing import Any, Literal, Protocol import structlog +from eventkit.schema.raw import RawEvent + logger = structlog.get_logger(__name__) @@ -18,19 +19,19 @@ class ErrorStore(Protocol): async def store_error( self, - payload: dict[str, Any], - error: str, - timestamp: datetime, - metadata: dict[str, Any] | None = None, + raw_event: RawEvent, + error_message: str, + error_type: Literal["validation_error", "processing_error"], + error_details: dict[str, Any] | None = None, ) -> None: """ Store an error for a failed event. Args: - payload: The original event payload that failed - error: Error message describing the failure - timestamp: When the error occurred - metadata: Optional additional context (stream, adapter, etc.) + raw_event: The original raw event that failed + error_message: Human-readable error message + error_type: Type of error (validation or processing) + error_details: Additional context (adapter, stack trace, etc.) Raises: StorageError: If error storage fails @@ -48,16 +49,17 @@ class LoggingErrorStore: async def store_error( self, - payload: dict[str, Any], - error: str, - timestamp: datetime, - metadata: dict[str, Any] | None = None, + raw_event: RawEvent, + error_message: str, + error_type: Literal["validation_error", "processing_error"], + error_details: dict[str, Any] | None = None, ) -> None: """Log error to structlog.""" logger.error( "event_processing_error", - error=error, - payload=payload, - timestamp=timestamp.isoformat(), - metadata=metadata or {}, + error_type=error_type, + error_message=error_message, + stream=raw_event.stream, + payload=raw_event.payload, + error_details=error_details or {}, ) diff --git a/src/eventkit/stores/gcs.py b/src/eventkit/stores/gcs.py index 8142db1..0dfda76 100644 --- a/src/eventkit/stores/gcs.py +++ b/src/eventkit/stores/gcs.py @@ -12,10 +12,10 @@ from uuid import uuid4 import pandas as pd -import pyarrow as pa # type: ignore[import-untyped] -import pyarrow.parquet as pq # type: ignore[import-untyped] +import pyarrow as pa +import pyarrow.parquet as pq import structlog -from google.cloud import storage # type: ignore[attr-defined] +from google.cloud import storage from tenacity import retry, stop_after_attempt, wait_exponential from eventkit.schema.events import IdentifyEvent, PageEvent, TrackEvent, TypedEvent diff --git a/src/eventkit/stores/gcs_error.py b/src/eventkit/stores/gcs_error.py new file mode 100644 index 0000000..c0fbab3 --- /dev/null +++ b/src/eventkit/stores/gcs_error.py @@ -0,0 +1,136 @@ +"""GCS-based error store (dead letter queue).""" + +import logging +from typing import Any, Literal + +import pandas as pd +import pyarrow as pa +import pyarrow.parquet as pq +from google.cloud import storage +from tenacity import retry, stop_after_attempt, wait_exponential + +from eventkit.schema.raw import RawEvent +from eventkit.stores.models import ErrorRecord + +logger = logging.getLogger(__name__) + + +class GCSErrorStore: + """ + GCS-based error store (dead letter queue). + + Stores failed events as Parquet files in GCS with Hive-style partitioning + for efficient BigQuery querying. + + Example: + error_store = GCSErrorStore( + project_id="my-project", + bucket_name="my-events", + ) + + await error_store.store_error( + raw_event=raw_event, + error_message="Missing required field: userId", + error_type="validation_error", + error_details={"adapter": "segment", "step": "required_fields"} + ) + """ + + def __init__(self, project_id: str, bucket_name: str): + """ + Initialize GCS error store. + + Args: + project_id: Google Cloud project ID + bucket_name: GCS bucket name for error storage + """ + self.project_id = project_id + self.bucket_name = bucket_name + self.client = storage.Client(project=project_id) + self.bucket = self.client.bucket(bucket_name) + + @retry( + stop=stop_after_attempt(3), + wait=wait_exponential(multiplier=1, min=1, max=10), + reraise=True, + ) + async def store_error( + self, + raw_event: RawEvent, + error_message: str, + error_type: Literal["validation_error", "processing_error"], + error_details: dict[str, Any] | None = None, + ) -> None: + """ + Store a failed event to GCS. + + Args: + raw_event: The original raw event that failed + error_message: Human-readable error message + error_type: Type of error (validation or processing) + error_details: Additional context (adapter, stack trace, etc.) + """ + # Create error record + error_record = ErrorRecord( + error_type=error_type, + error_message=error_message, + error_details=error_details, + stream=raw_event.stream or "unknown", + original_payload=raw_event.payload, + ) + + # Convert to DataFrame (single row) + df = pd.DataFrame([error_record.model_dump()]) + + # Convert to Parquet + table = pa.Table.from_pandas(df) + + # Generate path with Hive partitioning + path = self._generate_path(error_record) + + # Write to GCS + blob = self.bucket.blob(path) + + with blob.open("wb") as f: + pq.write_table(table, f) + + logger.info( + "Stored error to GCS", + extra={ + "error_id": error_record.error_id, + "error_type": error_type, + "stream": raw_event.stream, + "path": path, + }, + ) + + def _generate_path(self, error: ErrorRecord) -> str: + """ + Generate GCS path with Hive-style partitioning. + + Format: errors/date=YYYY-MM-DD/error_type={type}/error-{timestamp}-{id}.parquet + + Args: + error: Error record to generate path for + + Returns: + GCS path string + """ + timestamp_str = error.timestamp.strftime("%Y%m%d-%H%M%S") + filename = f"error-{timestamp_str}-{error.error_id[:8]}.parquet" + + return f"errors/date={error.date}/error_type={error.error_type}/{filename}" + + def health_check(self) -> bool: + """ + Check if GCS bucket is accessible. + + Returns: + True if bucket exists and is accessible, False otherwise + """ + try: + exists: bool = self.bucket.exists() + return exists + except Exception as e: + logger.error(f"GCS health check failed: {e}") + return False diff --git a/src/eventkit/stores/models.py b/src/eventkit/stores/models.py new file mode 100644 index 0000000..fdecc39 --- /dev/null +++ b/src/eventkit/stores/models.py @@ -0,0 +1,28 @@ +"""Data models for event storage.""" + +import uuid +from datetime import UTC, datetime +from typing import Any, Literal + +from pydantic import BaseModel, Field + + +class ErrorRecord(BaseModel): + """ + Error record for dead letter queue. + + Stores failed events with context for debugging and retry. + """ + + error_id: str = Field(default_factory=lambda: str(uuid.uuid4())) + timestamp: datetime = Field(default_factory=lambda: datetime.now(UTC)) + error_type: Literal["validation_error", "processing_error"] + error_message: str + error_details: dict[str, Any] | None = None + stream: str + original_payload: dict[str, Any] + retry_count: int = 0 + retry_after: datetime | None = None + + # For partitioning + date: str = Field(default_factory=lambda: datetime.now(UTC).strftime("%Y-%m-%d")) diff --git a/src/eventkit/streaming/coordinator.py b/src/eventkit/streaming/coordinator.py index 8ae36ee..f0a407d 100644 --- a/src/eventkit/streaming/coordinator.py +++ b/src/eventkit/streaming/coordinator.py @@ -10,7 +10,7 @@ import logging from typing import Protocol -from google.cloud import pubsub_v1 # type: ignore[attr-defined] +from google.cloud import pubsub_v1 from google.cloud.pubsub_v1.subscriber.message import Message from eventkit.queues.metrics import ( diff --git a/tests/unit/processing/test_processor.py b/tests/unit/processing/test_processor.py index ea6c28d..52e0ef9 100644 --- a/tests/unit/processing/test_processor.py +++ b/tests/unit/processing/test_processor.py @@ -82,10 +82,10 @@ async def test_process_event_invalid(self): # Verify error store call call_args = mock_error_store.store_error.call_args - assert call_args.kwargs["payload"] == raw_event.payload - assert call_args.kwargs["error"] == "Missing userId" - assert call_args.kwargs["metadata"] == {"stream": "users"} - assert isinstance(call_args.kwargs["timestamp"], datetime) + assert call_args.kwargs["raw_event"] == raw_event + assert call_args.kwargs["error_message"] == "Missing userId" + assert call_args.kwargs["error_type"] == "validation_error" + assert call_args.kwargs["error_details"] == {"adapter": "Mock"} # Verify sequencer and buffer NOT called mock_sequencer.get_partition_id.assert_not_called() diff --git a/tests/unit/stores/test_gcs_error.py b/tests/unit/stores/test_gcs_error.py new file mode 100644 index 0000000..f8ad22f --- /dev/null +++ b/tests/unit/stores/test_gcs_error.py @@ -0,0 +1,169 @@ +"""Unit tests for GCSErrorStore.""" + +from datetime import UTC, datetime +from unittest.mock import MagicMock, Mock, patch + +import pytest + +from eventkit.schema.raw import RawEvent +from eventkit.stores.gcs_error import GCSErrorStore +from eventkit.stores.models import ErrorRecord + + +@pytest.fixture +def gcs_error_store(): + """Fixture for GCSErrorStore with mocked GCS client.""" + with patch("eventkit.stores.gcs_error.storage.Client"): + store = GCSErrorStore(project_id="test-project", bucket_name="test-bucket") + store.bucket = Mock() + store.bucket.exists.return_value = True + yield store + + +class TestErrorRecord: + """Tests for ErrorRecord model.""" + + def test_error_record_creation(self): + """Test ErrorRecord model with all fields.""" + record = ErrorRecord( + error_type="validation_error", + error_message="Missing field: userId", + error_details={"adapter": "segment"}, + stream="users", + original_payload={"type": "identify"}, + ) + + assert record.error_type == "validation_error" + assert record.error_message == "Missing field: userId" + assert record.stream == "users" + assert record.retry_count == 0 + assert record.error_id is not None + assert record.timestamp is not None + assert record.date is not None + + def test_error_record_defaults(self): + """Test ErrorRecord with minimal fields.""" + record = ErrorRecord( + error_type="processing_error", + error_message="Storage failed", + stream="events", + original_payload={}, + ) + + assert record.error_details is None + assert record.retry_after is None + assert record.retry_count == 0 + + +class TestGCSErrorStore: + """Tests for GCSErrorStore.""" + + def test_initialization(self, gcs_error_store): + """Test GCSErrorStore initialization.""" + assert gcs_error_store.project_id == "test-project" + assert gcs_error_store.bucket_name == "test-bucket" + assert gcs_error_store.bucket is not None + + def test_generate_path(self, gcs_error_store): + """Test path generation with Hive-style partitioning.""" + error = ErrorRecord( + error_id="abc123def456", + timestamp=datetime(2026, 1, 15, 10, 30, 45, tzinfo=UTC), + error_type="validation_error", + error_message="Test error", + stream="users", + original_payload={}, + date="2026-01-15", + ) + + path = gcs_error_store._generate_path(error) + + assert path.startswith("errors/date=2026-01-15/error_type=validation_error/") + assert "error-20260115-103045" in path + assert "abc123de" in path # First 8 chars of ID + assert path.endswith(".parquet") + + def test_generate_path_processing_error(self, gcs_error_store): + """Test path generation for processing errors.""" + error = ErrorRecord( + error_type="processing_error", + error_message="Processing failed", + stream="events", + original_payload={}, + date="2026-01-15", + ) + + path = gcs_error_store._generate_path(error) + + assert "error_type=processing_error" in path + + @pytest.mark.asyncio + @patch("eventkit.stores.gcs_error.pq.write_table") + async def test_store_validation_error(self, mock_write_table, gcs_error_store): + """Test storing a validation error.""" + raw_event = RawEvent( + payload={"type": "identify"}, + stream="users", + ) + + # Mock blob with context manager + mock_blob = MagicMock() + gcs_error_store.bucket.blob.return_value = mock_blob + + await gcs_error_store.store_error( + raw_event=raw_event, + error_message="Missing userId", + error_type="validation_error", + error_details={"adapter": "segment", "field": "userId"}, + ) + + # Verify blob was written + gcs_error_store.bucket.blob.assert_called_once() + assert "errors/date=" in gcs_error_store.bucket.blob.call_args[0][0] + mock_blob.open.assert_called_once_with("wb") + mock_write_table.assert_called_once() + + @pytest.mark.asyncio + @patch("eventkit.stores.gcs_error.pq.write_table") + async def test_store_processing_error(self, mock_write_table, gcs_error_store): + """Test storing a processing error with stack trace.""" + raw_event = RawEvent( + payload={"type": "track", "event": "Button Clicked"}, + stream="events", + ) + + mock_blob = MagicMock() + gcs_error_store.bucket.blob.return_value = mock_blob + + await gcs_error_store.store_error( + raw_event=raw_event, + error_message="Storage connection failed", + error_type="processing_error", + error_details={ + "exception_type": "ConnectionError", + "stack_trace": "Traceback...", + }, + ) + + # Verify correct error type in path + call_args = gcs_error_store.bucket.blob.call_args[0][0] + assert "error_type=processing_error" in call_args + mock_write_table.assert_called_once() + + def test_health_check_success(self, gcs_error_store): + """Test health check when bucket exists.""" + gcs_error_store.bucket.exists.return_value = True + + assert gcs_error_store.health_check() is True + + def test_health_check_failure(self, gcs_error_store): + """Test health check when bucket doesn't exist.""" + gcs_error_store.bucket.exists.return_value = 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