Update 2026-05-13 16:43:53

dataclaw-api/app/connectors/parquet.py

@@ -0,0 +1,58 @@
+import duckdb
+import pandas as pd
+from typing import List, Dict, Any
+import os
+
+class ParquetConnector:
+    def __init__(self, file_path: str):
+        self.file_path = file_path
+        if not os.path.exists(self.file_path):
+             raise FileNotFoundError(f"Parquet file not found: {self.file_path}")
+
+    def execute_query(self, query: str) -> List[Dict[str, Any]]:
+        conn = duckdb.connect(":memory:")
+        # Register the parquet file as a view or table
+        # We can use read_parquet directly in query, or register it.
+        # Let's register it as 'parquet_table' for simplicity in generated SQL, 
+        # or we can ask LLM to use the filename.
+        # A better approach for generic SQL is to register it as a table name derived from filename or just 'data'.
+        table_name = os.path.splitext(os.path.basename(self.file_path))[0]
+        conn.execute(f"CREATE OR REPLACE VIEW {table_name} AS SELECT * FROM read_parquet('{self.file_path}')")
+        
+        # If the query doesn't use the table name, we might have issues. 
+        # But usually we provide schema with table name to LLM.
+        try:
+            # DuckDB returns a dataframe, we convert to dict
+            df = conn.execute(query).df()
+            return df.to_dict(orient="records")
+        except Exception as e:
+            print(f"Parquet Query Error: {e}")
+            raise e
+        finally:
+            conn.close()
+
+    def get_schema(self) -> Dict[str, List[Dict[str, str]]]:
+        conn = duckdb.connect(":memory:")
+        table_name = os.path.splitext(os.path.basename(self.file_path))[0]
+        conn.execute(f"CREATE OR REPLACE VIEW {table_name} AS SELECT * FROM read_parquet('{self.file_path}')")
+        
+        try:
+            # Get columns
+            columns = conn.execute(f"DESCRIBE {table_name}").fetchall()
+            schema = {table_name: [{"name": col[0], "type": col[1]} for col in columns]}
+            return schema
+        except Exception as e:
+            print(f"Error getting schema: {e}")
+            return {}
+        finally:
+            conn.close()
+
+    def test_connection(self) -> bool:
+        try:
+            conn = duckdb.connect(":memory:")
+            conn.execute(f"SELECT * FROM read_parquet('{self.file_path}') LIMIT 1")
+            conn.close()
+            return True
+        except Exception as e:
+            print(f"Parquet Connection Error: {e}")
+            return False