qlty_columnSummary
Analyze table columns to generate summary statistics for data quality assessment in Teradata databases.
Instructions
Get the column summary statistics for a table.
Arguments: database_name - name of the database table_name - table name to analyze
Returns: ResponseType: formatted response with query results + metadata
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| database_name | Yes | ||
| table_name | Yes |
Implementation Reference
- The handler function that implements the core logic of the qlty_columnSummary tool. It connects to Teradata, runs TD_ColumnSummary on the table, converts results to JSON, adds metadata, and returns a formatted response.
def handle_qlty_columnSummary(conn: TeradataConnection, database_name: str | None, table_name: str, *args, **kwargs): """ Get the column summary statistics for a table. Arguments: database_name - name of the database table_name - table name to analyze Returns: ResponseType: formatted response with query results + metadata """ logger.debug(f"Tool: handle_qlty_columnSummary: Args: table_name: {database_name}.{table_name}") if database_name is not None: table_name = f"{database_name}.{table_name}" with conn.cursor() as cur: rows = cur.execute(f"select * from TD_ColumnSummary ( on {table_name} as InputTable using TargetColumns ('[:]')) as dt") data = rows_to_json(cur.description, rows.fetchall()) metadata = { "tool_name": "qlty_columnSummary", "database_name": database_name, "table_name": table_name, "rows": len(data) } logger.debug(f"Tool: handle_qlty_columnSummary: Metadata: {metadata}") return create_response(data, metadata)