irisvector example

Author: daimor

README.md

@@ -74,6 +74,60 @@ docker run -d --name iris \
  intersystemsdc/iris-community:preview
 ```
 
+Examples
+===
+
+IRISVector
+---
+
+```python
+from sqlalchemy import Column, MetaData, Table, select
+from sqlalchemy.sql.sqltypes import Integer, UUID
+from sqlalchemy_iris import IRISVector
+from sqlalchemy import create_engine
+from sqlalchemy.orm import DeclarativeBase
+import uuid
+
+DATABASE_URL = "iris://_SYSTEM:SYS@localhost:1972/USER"
+engine = create_engine(DATABASE_URL, echo=False)
+
+# Create a table metadata
+metadata = MetaData()
+
+
+class Base(DeclarativeBase):
+    pass
+
+
+def main():
+    demo_table = Table(
+        "demo_table",
+        metadata,
+        Column("id", Integer, primary_key=True, autoincrement=True),
+        Column("uuid", UUID),
+        Column("embedding", IRISVector(item_type=float, max_items=3)),
+    )
+
+    demo_table.drop(engine, checkfirst=True)
+    demo_table.create(engine, checkfirst=True)
+    with engine.connect() as conn:
+        conn.execute(
+            demo_table.insert(),
+            [
+                {"uuid": uuid.uuid4(), "embedding": [1, 2, 3]},
+                {"uuid": uuid.uuid4(), "embedding": [2, 3, 4]},
+            ],
+        )
+        conn.commit()
+        result = conn.execute(
+            demo_table.select()
+        ).fetchall()
+        print("result", result)
+
+
+main()
+```
+
 _Port 1972 is used for binary communication (this driver, xDBC and so on), and 52773 is for web (Management Portal, IRIS based web-applications and API's)._
 
 The System Management Portal is available by URL: `http://localhost:52773/csp/sys/UtilHome.csp`

test.py

@@ -0,0 +1,41 @@
+from sqlalchemy import Column, MetaData, Table, select
+from sqlalchemy.sql.sqltypes import Integer, UUID
+from sqlalchemy_iris import IRISVector
+from sqlalchemy import create_engine
+from sqlalchemy.orm import DeclarativeBase
+import uuid
+
+DATABASE_URL = "iris://_SYSTEM:SYS@localhost:1972/USER"
+engine = create_engine(DATABASE_URL, echo=False)
+
+# Create a table metadata
+metadata = MetaData()
+
+
+def main():
+    demo_table = Table(
+        "demo_table",
+        metadata,
+        Column("id", Integer, primary_key=True, autoincrement=True),
+        Column("uuid", UUID),
+        Column("embedding", IRISVector(item_type=float, max_items=3)),
+    )
+
+    demo_table.drop(engine, checkfirst=True)
+    demo_table.create(engine, checkfirst=True)
+    with engine.connect() as conn:
+        conn.execute(
+            demo_table.insert(),
+            [
+                {"uuid": uuid.uuid4(), "embedding": [1, 2, 3]},
+                {"uuid": uuid.uuid4(), "embedding": [2, 3, 4]},
+            ],
+        )
+        conn.commit()
+        result = conn.execute(
+            demo_table.select()
+        ).fetchall()
+        print("result", result)
+
+
+main()