done with ruff checks
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parent
51dfac359d
commit
1ba9e1df31
3 changed files with 95 additions and 67 deletions
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@ -16,7 +16,9 @@ from cognee.modules.engine.models import TableRow, TableType, ColumnValue
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logger = logging.getLogger(__name__)
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async def migrate_relational_database(graph_db, schema, migrate_column_data=True,schema_only=False):
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async def migrate_relational_database(
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graph_db, schema, migrate_column_data=True, schema_only=False
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):
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"""
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Migrates data from a relational database into a graph database.
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@ -33,15 +35,15 @@ async def migrate_relational_database(graph_db, schema, migrate_column_data=True
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# Create a mapping of node_id to node objects for referencing in edge creation
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node_mapping = {}
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edge_mapping = []
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if schema_only:
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database_config = get_migration_config().to_dict()
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database_config = get_migration_config().to_dict()
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# Calling the ingest_database_schema function to return DataPoint subclasses
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result = await ingest_database_schema(
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database_config=database_config,
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schema_name="migrated_schema",
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max_sample_rows=5,
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node_set=["database_schema", "schema_tables", "relationships"]
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node_set=["database_schema", "schema_tables", "relationships"],
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)
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database_schema = result["database_schema"]
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schema_tables = result["schema_tables"]
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@ -51,57 +53,64 @@ async def migrate_relational_database(graph_db, schema, migrate_column_data=True
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for table in schema_tables:
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table_node_id = table.id
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# Add TableSchema Datapoint as a node.
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node_mapping[table_node_id]=table
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edge_mapping.append((
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table_node_id,
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database_node_id,
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"is_part_of",
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dict(
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source_node_id=table_node_id,
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target_node_id=database_node_id,
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relationship_name="is_part_of",
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),
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))
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for rel in schema_relationships:
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source_table_id = uuid5(NAMESPACE_OID,name=rel.source_table)
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target_table_id = uuid5(NAMESPACE_OID,name=rel.target_table)
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relationship_id = rel.id
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# Add RelationshipTable DataPoint as a node.
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node_mapping[relationship_id]=rel
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edge_mapping.append((
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source_table_id,
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relationship_id,
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"has_relationship",
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dict(
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source_node_id=source_table_id,
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target_node_id=relationship_id,
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relationship_name=rel.relationship_type,
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),
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))
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edge_mapping.append((
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relationship_id,
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target_table_id,
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"has_relationship",
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dict(
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source_node_id=relationship_id,
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target_node_id=target_table_id,
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relationship_name=rel.relationship_type,
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node_mapping[table_node_id] = table
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edge_mapping.append(
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(
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table_node_id,
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database_node_id,
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"is_part_of",
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dict(
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source_node_id=table_node_id,
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target_node_id=database_node_id,
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relationship_name="is_part_of",
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),
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)
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))
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edge_mapping.append((
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source_table_id,
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target_table_id,
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rel.relationship_type,
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dict(
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source_node_id=source_table_id,
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target_node_id=target_table_id,
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relationship_name=rel.relationship_type,
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),
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))
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)
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for rel in schema_relationships:
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source_table_id = uuid5(NAMESPACE_OID, name=rel.source_table)
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target_table_id = uuid5(NAMESPACE_OID, name=rel.target_table)
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relationship_id = rel.id
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# Add RelationshipTable DataPoint as a node.
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node_mapping[relationship_id] = rel
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edge_mapping.append(
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(
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source_table_id,
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relationship_id,
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"has_relationship",
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dict(
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source_node_id=source_table_id,
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target_node_id=relationship_id,
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relationship_name=rel.relationship_type,
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),
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)
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)
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edge_mapping.append(
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(
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relationship_id,
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target_table_id,
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"has_relationship",
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dict(
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source_node_id=relationship_id,
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target_node_id=target_table_id,
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relationship_name=rel.relationship_type,
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),
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)
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)
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edge_mapping.append(
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(
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source_table_id,
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target_table_id,
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rel.relationship_type,
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dict(
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source_node_id=source_table_id,
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target_node_id=target_table_id,
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relationship_name=rel.relationship_type,
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),
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)
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)
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else:
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async with engine.engine.begin() as cursor:
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# First, create table type nodes for all tables
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@ -1,27 +1,32 @@
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from typing import List, Dict
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from uuid import uuid5, NAMESPACE_OID
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from cognee.infrastructure.engine.models.DataPoint import DataPoint
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from cognee.infrastructure.databases.relational.get_migration_relational_engine import get_migration_relational_engine
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from cognee.infrastructure.databases.relational.get_migration_relational_engine import (
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get_migration_relational_engine,
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)
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from sqlalchemy import text
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from cognee.tasks.schema.models import DatabaseSchema, SchemaTable, SchemaRelationship
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from cognee.infrastructure.databases.relational.create_relational_engine import create_relational_engine
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from cognee.infrastructure.databases.relational.create_relational_engine import (
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create_relational_engine,
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)
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from datetime import datetime
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async def ingest_database_schema(
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database_config: Dict,
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schema_name: str = "default",
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max_sample_rows: int = 5,
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node_set: List[str] = ["database_schema"]
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node_set: List[str] = ["database_schema"],
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) -> Dict[str, List[DataPoint] | DataPoint]:
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"""
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Ingest database schema with sample data into dedicated nodeset
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Args:
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database_config: Database connection configuration
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schema_name: Name identifier for this schema
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max_sample_rows: Maximum sample rows per table
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node_set: Target nodeset (default: ["database_schema"])
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Returns:
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List of created DataPoint objects
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"""
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@ -42,8 +47,13 @@ async def ingest_database_schema(
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async with engine.engine.begin() as cursor:
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for table_name, details in schema.items():
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rows_result = await cursor.execute(text(f"SELECT * FROM {table_name} LIMIT {max_sample_rows}"))
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rows = [dict(zip([col["name"] for col in details["columns"]], row)) for row in rows_result.fetchall()]
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rows_result = await cursor.execute(
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text(f"SELECT * FROM {table_name} LIMIT {max_sample_rows}")
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)
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rows = [
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dict(zip([col["name"] for col in details["columns"]], row))
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for row in rows_result.fetchall()
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]
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count_result = await cursor.execute(text(f"SELECT COUNT(*) FROM {table_name};"))
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row_count_estimate = count_result.scalar()
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@ -56,7 +66,7 @@ async def ingest_database_schema(
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foreign_keys=details.get("foreign_keys", []),
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sample_rows=rows,
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row_count_estimate=row_count_estimate,
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description=f""
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description=f"Schema table for '{table_name}' with {len(details['columns'])} columns and approx. {row_count_estimate} rows.",
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)
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schema_tables.append(schema_table)
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tables[table_name] = details
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@ -64,13 +74,16 @@ async def ingest_database_schema(
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for fk in details.get("foreign_keys", []):
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relationship = SchemaRelationship(
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id=uuid5(NAMESPACE_OID, name=f"{fk['column']}:{table_name}:{fk['ref_column']}:{fk['ref_table']}"),
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id=uuid5(
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NAMESPACE_OID,
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name=f"{fk['column']}:{table_name}:{fk['ref_column']}:{fk['ref_table']}",
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),
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source_table=table_name,
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target_table=fk["ref_table"],
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relationship_type="foreign_key",
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source_column=fk["column"],
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target_column=fk["ref_column"],
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description=f""
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description=f"Foreign key relationship: {table_name}.{fk['column']} → {fk['ref_table']}.{fk['ref_column']}",
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)
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schema_relationships.append(relationship)
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@ -81,11 +94,11 @@ async def ingest_database_schema(
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tables=tables,
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sample_data=sample_data,
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extraction_timestamp=datetime.utcnow(),
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description=f""
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description=f"Database schema '{schema_name}' containing {len(schema_tables)} tables and {len(schema_relationships)} relationships.",
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)
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return {
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"database_schema": database_schema,
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"schema_tables": schema_tables,
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"relationships": schema_relationships
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"relationships": schema_relationships,
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}
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@ -2,8 +2,10 @@ from cognee.infrastructure.engine.models.DataPoint import DataPoint
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from typing import List, Dict, Optional
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from datetime import datetime
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class DatabaseSchema(DataPoint):
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"""Represents a complete database schema with sample data"""
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schema_name: str
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database_type: str # sqlite, postgres, etc.
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tables: Dict[str, Dict] # Reuse existing schema format from SqlAlchemyAdapter
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@ -12,8 +14,10 @@ class DatabaseSchema(DataPoint):
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description: str
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metadata: dict = {"index_fields": ["schema_name", "database_type"]}
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class SchemaTable(DataPoint):
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"""Represents an individual table schema with relationships"""
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table_name: str
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schema_name: str
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columns: List[Dict] # Column definitions with types
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@ -24,12 +28,14 @@ class SchemaTable(DataPoint):
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description: str
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metadata: dict = {"index_fields": ["table_name", "schema_name"]}
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class SchemaRelationship(DataPoint):
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"""Represents relationships between tables"""
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source_table: str
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target_table: str
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relationship_type: str # "foreign_key", "one_to_many", etc.
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source_column: str
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target_column: str
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description: str
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metadata: dict = {"index_fields": ["source_table", "target_table"]}
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metadata: dict = {"index_fields": ["source_table", "target_table"]}
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