157 resolve vertex name edge name collision for tigergraph

README.md

@@ -143,7 +143,7 @@ caster.ingest(
 
 ```python
 from graflo.db.postgres import PostgresConnection
-from graflo.db.postgres.heuristics import infer_schema_from_postgres
+from graflo.db.inferencer import infer_schema_from_postgres
 from graflo.db.connection.onto import PostgresConfig
 from graflo import Caster
 from graflo.onto import DBFlavor

docs/examples/example-5.md

@@ -262,7 +262,8 @@ Automatically generate a graflo Schema from your PostgreSQL database. This is th
 5. **Creates Resources**: Resource definitions are generated for each table with appropriate actors (VertexActor for vertex tables, EdgeActor for edge tables). Foreign keys are mapped to vertex matching keys.
 
 ```python
-from graflo.db.postgres import infer_schema_from_postgres
+
+from graflo.db.inferencer import infer_schema_from_postgres
 from graflo.onto import DBFlavor
 from graflo.db.connection.onto import ArangoConfig, Neo4jConfig, TigergraphConfig, FalkordbConfig
 from graflo.db import DBType
@@ -283,7 +284,7 @@ db_flavor = (
 schema = infer_schema_from_postgres(
     postgres_conn,
     schema_name="public",  # PostgreSQL schema name
-    db_flavor=db_flavor     # Target graph database flavor
+    db_flavor=db_flavor  # Target graph database flavor
 )
 ```
 
@@ -327,7 +328,8 @@ logger.info(f"Inferred schema saved to {schema_output_file}")
 Create `Patterns` that map PostgreSQL tables to resources:
 
 ```python
-from graflo.db.postgres import create_patterns_from_postgres
+
+from graflo.db.inferencer import create_patterns_from_postgres
 
 # Create patterns from PostgreSQL tables
 patterns = create_patterns_from_postgres(
@@ -402,9 +404,8 @@ from graflo.onto import DBFlavor
 from graflo.db import DBType
 from graflo.db.postgres import (
     PostgresConnection,
-    create_patterns_from_postgres,
-    infer_schema_from_postgres,
 )
+from graflo.db.inferencer import infer_schema_from_postgres, create_patterns_from_postgres
 from graflo.db.connection.onto import ArangoConfig, PostgresConfig
 
 logger = logging.getLogger(__name__)
@@ -419,6 +420,7 @@ postgres_conn = PostgresConnection(postgres_conf)
 # Step 3: Connect to target graph database
 # You can try different databases by uncommenting the desired config:
 from graflo.db.connection.onto import ArangoConfig, Neo4jConfig, TigergraphConfig, FalkordbConfig
+
 target_config = ArangoConfig.from_docker_env()  # or Neo4jConfig, TigergraphConfig, FalkordbConfig
 
 # Step 4: Infer Schema from PostgreSQL database structure

docs/getting_started/quickstart.md

@@ -108,7 +108,8 @@ The `ingest()` method takes:
 You can ingest data directly from PostgreSQL tables. First, infer the schema from your PostgreSQL database:
 
 ```python
-from graflo.db.postgres import PostgresConnection, infer_schema_from_postgres, create_patterns_from_postgres
+from graflo.db.postgres import PostgresConnection
+from graflo.db.inferencer import infer_schema_from_postgres, create_patterns_from_postgres
 from graflo.db.connection.onto import PostgresConfig
 
 # Connect to PostgreSQL

examples/5-ingest-postgres/generated-schema.yaml

@@ -1,8 +1,53 @@
+edge_config:
+    edges:
+    -   relation: follows
+        source: users
+        target: users
+        weights:
+            direct:
+            -   name: created_at
+                type: DATETIME
+    -   relation: purchases
+        source: users
+        target: products
+        weights:
+            direct:
+            -   name: purchase_date
+                type: DATETIME
+            -   name: quantity
+                type: INT
+            -   name: total_amount
+                type: FLOAT
 general:
-    name: public
+    name: accounting
+resources:
+-   apply:
+    -   vertex: products
+    resource_name: products
+-   apply:
+    -   vertex: users
+    resource_name: users
+-   apply:
+    -   map:
+            follower_id: id
+        target_vertex: users
+    -   map:
+            followed_id: id
+        target_vertex: users
+    resource_name: follows
+-   apply:
+    -   map:
+            user_id: id
+        target_vertex: users
+    -   map:
+            product_id: id
+        target_vertex: products
+    resource_name: purchases
+transforms: {}
 vertex_config:
+    db_flavor: tigergraph
     vertices:
-    -   name: products
+    -   dbname: products
         fields:
         -   name: id
             type: INT
@@ -17,8 +62,8 @@ vertex_config:
         indexes:
         -   fields:
             -   id
-        dbname: products
-    -   name: users
+        name: products
+    -   dbname: users
         fields:
         -   name: id
             type: INT
@@ -31,48 +76,4 @@ vertex_config:
         indexes:
         -   fields:
             -   id
-        dbname: users
-edge_config:
-    edges:
-    -   source: users
-        target: users
-        weights:
-            direct:
-            -   name: created_at
-                type: DATETIME
-        relation: follows
-    -   source: users
-        target: products
-        weights:
-            direct:
-            -   name: purchase_date
-                type: DATETIME
-            -   name: quantity
-                type: INT
-            -   name: total_amount
-                type: FLOAT
-        relation: purchases
-resources:
--   resource_name: products
-    apply:
-    -   vertex: products
--   resource_name: users
-    apply:
-    -   vertex: users
--   resource_name: follows
-    apply:
-    -   target_vertex: users
-        map:
-            follower_id: id
-    -   target_vertex: users
-        map:
-            followed_id: id
--   resource_name: purchases
-    apply:
-    -   target_vertex: users
-        map:
-            user_id: id
-    -   target_vertex: products
-        map:
-            product_id: id
-transforms: {}
+        name: users

examples/5-ingest-postgres/ingest.py

@@ -13,15 +13,17 @@
 
 import logging
 from pathlib import Path
-import yaml
+from suthing import FileHandle
 
 from graflo.onto import DBFlavor
 from graflo.db import DBType
 from graflo import Caster
 from graflo.db.postgres import (
     PostgresConnection,
-    create_patterns_from_postgres,
+)
+from graflo.db.inferencer import (
     infer_schema_from_postgres,
+    create_patterns_from_postgres,
 )
 from graflo.db.postgres.util import load_schema_from_sql_file
 from graflo.db.connection.onto import PostgresConfig, TigergraphConfig
@@ -103,15 +105,13 @@
         postgres_conn, schema_name="public", db_flavor=db_flavor
     )
 
+
+schema.general.name = "accounting"
 # Step 3.5: Dump inferred schema to YAML file
 schema_output_file = Path(__file__).parent / "generated-schema.yaml"
 
 # Convert schema to dict (enums are automatically converted to strings by BaseDataclass.to_dict())
-schema_dict = schema.to_dict()
-
-# Write to YAML file
-with open(schema_output_file, "w") as f:
-    yaml.safe_dump(schema_dict, f, default_flow_style=False, sort_keys=False)
+FileHandle.dump(schema.to_dict(), schema_output_file)
 
 logger.info(f"Inferred schema saved to {schema_output_file}")
 

graflo/db/__init__.py

@@ -32,12 +32,16 @@
 from .neo4j.conn import Neo4jConnection
 from .postgres.conn import PostgresConnection
 from .tigergraph.conn import TigerGraphConnection
+from .inferencer import infer_schema_from_postgres, create_patterns_from_postgres
+
 
 __all__ = [
     "Connection",
     "ConnectionType",
+    "create_patterns_from_postgres",
     "DBType",
     "DBConfig",
+    "infer_schema_from_postgres",
     "ConnectionManager",
     "ArangoConnection",
     "FalkordbConnection",