Chris Coutinho
578de4d7d6
- Add Prometheus metrics for HTTP, MCP tools, Nextcloud API, OAuth, vector sync, and DB operations - Add OpenTelemetry distributed tracing with OTLP export - Add structured JSON logging with trace context correlation - Add ObservabilityMiddleware for automatic HTTP instrumentation - Add app_name attribute to all client classes for per-app metrics - Add configuration for metrics, tracing, and logging via environment variables - Add documentation in docs/observability.md - Fix graceful degradation when tracing is disabled (default state) - Fix uvicorn logging configuration to use observability formatters 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
128 lines
4.5 KiB
Python
128 lines
4.5 KiB
Python
"""Client for Nextcloud Tables app operations."""
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import logging
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from typing import Any, Dict, List, Optional
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from .base import BaseNextcloudClient
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logger = logging.getLogger(__name__)
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class TablesClient(BaseNextcloudClient):
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"""Client for Nextcloud Tables app operations."""
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app_name = "tables"
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async def list_tables(self) -> List[Dict[str, Any]]:
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"""List all tables available to the user."""
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response = await self._make_request(
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"GET",
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"/ocs/v2.php/apps/tables/api/2/tables",
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headers={"OCS-APIRequest": "true", "Accept": "application/json"},
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)
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result = response.json()
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return result["ocs"]["data"]
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async def get_table_schema(self, table_id: int) -> Dict[str, Any]:
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"""Get the schema/structure of a specific table including columns and views."""
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# Using v1 API as v2 schema endpoint had issues during testing
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response = await self._make_request(
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"GET", f"/index.php/apps/tables/api/1/tables/{table_id}/scheme"
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)
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return response.json()
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async def get_table_rows(
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self, table_id: int, limit: Optional[int] = None, offset: Optional[int] = None
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) -> List[Dict[str, Any]]:
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"""Read rows from a table with optional pagination."""
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params = {}
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if limit is not None:
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params["limit"] = limit
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if offset is not None:
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params["offset"] = offset
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response = await self._make_request(
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"GET", f"/index.php/apps/tables/api/1/tables/{table_id}/rows", params=params
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)
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return response.json()
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async def create_row(self, table_id: int, data: Dict[str, Any]) -> Dict[str, Any]:
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"""Insert a new row into a table.
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Args:
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table_id: ID of the table to insert into
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data: Dictionary mapping column IDs to values, e.g. {1: "text", 2: 42}
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"""
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# Transform data to API format: {"data": {"1": "text", "2": 42}}
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api_data = {str(k): v for k, v in data.items()}
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response = await self._make_request(
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"POST",
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f"/ocs/v2.php/apps/tables/api/2/tables/{table_id}/rows",
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headers={"OCS-APIRequest": "true", "Accept": "application/json"},
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json={"data": api_data},
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)
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result = response.json()
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return result["ocs"]["data"]
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async def update_row(self, row_id: int, data: Dict[str, Any]) -> Dict[str, Any]:
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"""Update an existing row in a table.
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Args:
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row_id: ID of the row to update
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data: Dictionary mapping column IDs to new values, e.g. {1: "new text", 2: 99}
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"""
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# Transform data to API format for v1 endpoint
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api_data = {str(k): v for k, v in data.items()}
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response = await self._make_request(
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"PUT",
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f"/index.php/apps/tables/api/1/rows/{row_id}",
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json={"data": api_data},
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)
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return response.json()
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async def delete_row(self, row_id: int) -> Dict[str, Any]:
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"""Delete a row from a table."""
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response = await self._make_request(
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"DELETE", f"/index.php/apps/tables/api/1/rows/{row_id}"
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)
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return response.json()
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def transform_row_data(
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self, rows: List[Dict[str, Any]], columns: List[Dict[str, Any]]
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) -> List[Dict[str, Any]]:
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"""Transform raw row data into more readable format using column names.
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Args:
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rows: Raw row data from the API
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columns: Column definitions from table schema
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Returns:
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List of rows with column names as keys instead of column IDs
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"""
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# Create mapping from column ID to column title
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column_map = {col["id"]: col["title"] for col in columns}
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transformed_rows = []
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for row in rows:
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transformed_row = {
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"id": row["id"],
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"tableId": row["tableId"],
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"createdBy": row["createdBy"],
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"createdAt": row["createdAt"],
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"lastEditBy": row["lastEditBy"],
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"lastEditAt": row["lastEditAt"],
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"data": {},
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}
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# Transform data array to column_name: value mapping
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for item in row["data"]:
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column_id = item["columnId"]
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column_name = column_map.get(column_id, f"column_{column_id}")
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transformed_row["data"][column_name] = item["value"]
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transformed_rows.append(transformed_row)
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return transformed_rows
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