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# -----------------------------------------------------------------------------
# Copyright (c) 2023, Oracle and/or its affiliates.
#
# This software is dual-licensed to you under the Universal Permissive License
# (UPL) 1.0 as shown at https://oss.oracle.com/licenses/upl and Apache License
# 2.0 as shown at http://www.apache.org/licenses/LICENSE-2.0. You may choose
# either license.
#
# If you elect to accept the software under the Apache License, Version 2.0,
# the following applies:
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# -----------------------------------------------------------------------------
# -----------------------------------------------------------------------------
# vector_numpy.py
#
# Demonstrates how to use the Oracle Database 23ai VECTOR data type with NumPy
# types.
# -----------------------------------------------------------------------------
import sys
import array
import numpy
import oracledb
import sample_env
# determine whether to use python-oracledb thin mode or thick mode
if not sample_env.get_is_thin():
oracledb.init_oracle_client(lib_dir=sample_env.get_oracle_client())
connection = oracledb.connect(
user=sample_env.get_main_user(),
password=sample_env.get_main_password(),
dsn=sample_env.get_connect_string(),
)
# this script only works with Oracle Database 23.4 or later
if sample_env.get_server_version() < (23, 4):
sys.exit("This example requires Oracle Database 23.4 or later.")
# this script works with thin mode, or with thick mode using Oracle Client 23.4
# or later
if not connection.thin and oracledb.clientversion()[:2] < (23, 4):
sys.exit(
"This example requires python-oracledb thin mode, or Oracle Client"
" 23.4 or later"
)
# Convert from NumPy ndarray types to array types when inserting vectors
def numpy_converter_in(value):
if value.dtype == numpy.float64:
dtype = "d"
elif value.dtype == numpy.float32:
dtype = "f"
else:
dtype = "b"
return array.array(dtype, value)
def input_type_handler(cursor, value, arraysize):
if isinstance(value, numpy.ndarray):
return cursor.var(
oracledb.DB_TYPE_VECTOR,
arraysize=arraysize,
inconverter=numpy_converter_in,
)
connection.inputtypehandler = input_type_handler
# Convert from array types to NumPy ndarray types when fetching vectors
def numpy_converter_out(value):
if value.typecode == "b":
dtype = numpy.int8
elif value.typecode == "f":
dtype = numpy.float32
else:
dtype = numpy.float64
return numpy.array(value, copy=False, dtype=dtype)
def output_type_handler(cursor, metadata):
if metadata.type_code is oracledb.DB_TYPE_VECTOR:
return cursor.var(
metadata.type_code,
arraysize=cursor.arraysize,
outconverter=numpy_converter_out,
)
connection.outputtypehandler = output_type_handler
with connection.cursor() as cursor:
# Insert
vector_data_32 = numpy.array([1.625, 1.5, 1.0])
vector_data_64 = numpy.array([11.25, 11.75, 11.5])
vector_data_8 = numpy.array([1, 2, 3])
cursor.execute(
"insert into SampleVectorTab (v32, v64, v8) values (:1, :2, :3)",
[vector_data_32, vector_data_64, vector_data_8],
)
# Query
cursor.execute("select * from SampleVectorTab")
# Each vector is represented as a numpy.ndarray type
for row in cursor:
print(row)