rm perf.sh & refactor examples.

Signed-off-by: my-vegetable-has-exploded <[email protected]>

bindings/python/examples/psycopg_copy_dense.py

@@ -0,0 +1,57 @@
+import os
+
+import numpy as np
+import psycopg
+
+from pgvecto_rs.psycopg import register_vector
+
+URL = "postgresql://{username}:{password}@{host}:{port}/{db_name}".format(
+    port=os.getenv("DB_PORT", "5432"),
+    host=os.getenv("DB_HOST", "localhost"),
+    username=os.getenv("DB_USER", "postgres"),
+    password=os.getenv("DB_PASS", "mysecretpassword"),
+    db_name=os.getenv("DB_NAME", "postgres"),
+)
+
+# Connect to the DB and init things
+with psycopg.connect(URL) as conn:
+    conn.execute("CREATE EXTENSION IF NOT EXISTS vectors;")
+    register_vector(conn)
+    conn.execute("DROP TABLE IF EXISTS documents;")
+    conn.execute(
+        "CREATE TABLE documents (id SERIAL PRIMARY KEY, embedding vector(3) NOT NULL);",
+    )
+    conn.commit()
+    try:
+        embeddings = [
+            np.array([1, 2, 3]),
+            np.array([1.0, 2.0, 4.0]),
+            np.array([1, 3, 4]),
+        ]
+
+        with conn.cursor() as cursor, cursor.copy(
+            "COPY documents (embedding) FROM STDIN (FORMAT BINARY)"
+        ) as copy:
+            # write row by row
+            for e in embeddings:
+                copy.write_row([e])
+            copy.write_row([[1, 3, 5]])
+        conn.commit()
+
+        # Select the rows using binary format
+        cur = conn.execute(
+            "SELECT * FROM documents;",
+            binary=True,
+        )
+        for row in cur.fetchall():
+            print(row[0], ": ", row[1])
+
+        # output will be:
+        # 1 :  [1.0, 2.0, 3.0]
+        # 2 :  [1.0, 2.0, 4.0]
+        # 3 :  [1.0, 3.0, 4.0]
+        # 4 :  [1.0, 3.0, 5.0]
+    finally:
+        # Drop the table
+        conn.execute("DROP TABLE IF EXISTS documents;")
+        conn.commit()

bindings/python/examples/psycopg_copy_sparse.py

@@ -0,0 +1,52 @@
+import os
+
+import numpy as np
+import psycopg
+
+from pgvecto_rs.psycopg import register_vector
+from pgvecto_rs.types import SparseVector
+
+URL = "postgresql://{username}:{password}@{host}:{port}/{db_name}".format(
+    port=os.getenv("DB_PORT", "5432"),
+    host=os.getenv("DB_HOST", "localhost"),
+    username=os.getenv("DB_USER", "postgres"),
+    password=os.getenv("DB_PASS", "mysecretpassword"),
+    db_name=os.getenv("DB_NAME", "postgres"),
+)
+
+
+# Connect to the DB and init things
+with psycopg.connect(URL) as conn:
+    conn.execute("CREATE EXTENSION IF NOT EXISTS vectors;")
+    register_vector(conn)
+    conn.execute("DROP TABLE IF EXISTS documents;")
+    conn.execute(
+        "CREATE TABLE documents (id SERIAL PRIMARY KEY, embedding svector NOT NULL);",
+    )
+    conn.commit()
+    try:
+        with conn.cursor() as cursor, cursor.copy(
+            "COPY documents (embedding) FROM STDIN (FORMAT BINARY)"
+        ) as copy:
+            copy.write_row([SparseVector(3, [0, 2], [1.0, 3.0])])
+            copy.write_row([SparseVector(3, np.array([0, 1, 2]), [1.0, 2.0, 3.0])])
+            copy.write_row([SparseVector(3, np.array([1, 2]), np.array([2.0, 3.0]))])
+        conn.pgconn.flush()
+        conn.commit()
+
+        # Select the rows using binary format
+        cur = conn.execute(
+            "SELECT * FROM documents;",
+            binary=True,
+        )
+        for row in cur.fetchall():
+            print(row[0], ": ", row[1])
+
+        # output will be:
+        # 1 :  [1.0, 0.0, 3.0]
+        # 2 :  [1.0, 2.0, 3.0]
+        # 3 :  [0.0, 2.0, 3.0]
+    finally:
+        # Drop the table
+        conn.execute("DROP TABLE IF EXISTS documents;")
+        conn.commit()