Low-level Python client
The OpenSearch low-level Python client (opensearch-py) provides wrapper methods for the OpenSearch REST API so that you can interact with your cluster more naturally in Python. Rather than sending raw HTTP requests to a given URL, you can create an OpenSearch client for your cluster and call the client’s built-in functions. For the client’s complete API documentation and additional examples, see the opensearch-py API documentation.
This getting started guide illustrates how to connect to OpenSearch, index documents, and run queries. For the client source code, see the opensearch-py repo.
Setup
To add the client to your project, install it using pip:
pip install opensearch-py
After installing the client, you can import it like any other module:
from opensearchpy import OpenSearch
Connecting to OpenSearch
To connect to the default OpenSearch host, create a client object with SSL enabled if you are using the Security plugin. You can use the default credentials for testing purposes:
host = 'localhost'
port = 9200
auth = ('admin', 'admin') # For testing only. Don't store credentials in code.
ca_certs_path = '/full/path/to/root-ca.pem' # Provide a CA bundle if you use intermediate CAs with your root CA.
# Create the client with SSL/TLS enabled, but hostname verification disabled.
client = OpenSearch(
hosts = [{'host': host, 'port': port}],
http_compress = True, # enables gzip compression for request bodies
http_auth = auth,
use_ssl = True,
verify_certs = True,
ssl_assert_hostname = False,
ssl_show_warn = False,
ca_certs = ca_certs_path
)
If you have your own client certificates, specify them in the client_cert_path and client_key_path parameters:
host = 'localhost'
port = 9200
auth = ('admin', 'admin') # For testing only. Don't store credentials in code.
ca_certs_path = '/full/path/to/root-ca.pem' # Provide a CA bundle if you use intermediate CAs with your root CA.
# Optional client certificates if you don't want to use HTTP basic authentication.
client_cert_path = '/full/path/to/client.pem'
client_key_path = '/full/path/to/client-key.pem'
# Create the client with SSL/TLS enabled, but hostname verification disabled.
client = OpenSearch(
hosts = [{'host': host, 'port': port}],
http_compress = True, # enables gzip compression for request bodies
http_auth = auth,
client_cert = client_cert_path,
client_key = client_key_path,
use_ssl = True,
verify_certs = True,
ssl_assert_hostname = False,
ssl_show_warn = False,
ca_certs = ca_certs_path
)
If you are not using the Security plugin, create a client object with SSL disabled:
host = 'localhost'
port = 9200
# Create the client with SSL/TLS and hostname verification disabled.
client = OpenSearch(
hosts = [{'host': host, 'port': port}],
http_compress = True, # enables gzip compression for request bodies
use_ssl = False,
verify_certs = False,
ssl_assert_hostname = False,
ssl_show_warn = False
)
Connecting to Amazon OpenSearch Service
The following example illustrates connecting to Amazon OpenSearch Service:
from opensearchpy import OpenSearch, RequestsHttpConnection, AWSV4SignerAuth
import boto3
host = '' # cluster endpoint, for example: my-test-domain.us-east-1.es.amazonaws.com
region = 'us-west-2'
service = 'es'
credentials = boto3.Session().get_credentials()
auth = AWSV4SignerAuth(credentials, region, service)
client = OpenSearch(
hosts = [{'host': host, 'port': 443}],
http_auth = auth,
use_ssl = True,
verify_certs = True,
connection_class = RequestsHttpConnection,
pool_maxsize = 20
)
Connecting to Amazon OpenSearch Serverless
The following example illustrates connecting to Amazon OpenSearch Serverless Service:
from opensearchpy import OpenSearch, RequestsHttpConnection, AWSV4SignerAuth
import boto3
host = '' # cluster endpoint, for example: my-test-domain.us-east-1.aoss.amazonaws.com
region = 'us-west-2'
service = 'aoss'
credentials = boto3.Session().get_credentials()
auth = AWSV4SignerAuth(credentials, region, service)
client = OpenSearch(
hosts = [{'host': host, 'port': 443}],
http_auth = auth,
use_ssl = True,
verify_certs = True,
connection_class = RequestsHttpConnection,
pool_maxsize = 20
)
Creating an index
To create an OpenSearch index, use the client.indices.create() method. You can use the following code to construct a JSON object with custom settings:
index_name = 'python-test-index'
index_body = {
'settings': {
'index': {
'number_of_shards': 4
}
}
}
response = client.indices.create(index_name, body=index_body)
Indexing a document
You can index a document using the client.index() method:
document = {
'title': 'Moneyball',
'director': 'Bennett Miller',
'year': '2011'
}
response = client.index(
index = 'python-test-index',
body = document,
id = '1',
refresh = True
)
Performing bulk operations
You can perform several operations at the same time by using the bulk() method of the client. The operations may be of the same type or of different types. Note that the operations must be separated by a \n and the entire string must be a single line:
movies = '{ "index" : { "_index" : "my-dsl-index", "_id" : "2" } } \n { "title" : "Interstellar", "director" : "Christopher Nolan", "year" : "2014"} \n { "create" : { "_index" : "my-dsl-index", "_id" : "3" } } \n { "title" : "Star Trek Beyond", "director" : "Justin Lin", "year" : "2015"} \n { "update" : {"_id" : "3", "_index" : "my-dsl-index" } } \n { "doc" : {"year" : "2016"} }'
client.bulk(movies)
Searching for documents
The easiest way to search for documents is to construct a query string. The following code uses a multi-match query to search for “miller” in the title and director fields. It boosts the documents that have “miller” in the title field:
q = 'miller'
query = {
'size': 5,
'query': {
'multi_match': {
'query': q,
'fields': ['title^2', 'director']
}
}
}
response = client.search(
body = query,
index = 'python-test-index'
)
Deleting a document
You can delete a document using the client.delete() method:
response = client.delete(
index = 'python-test-index',
id = '1'
)
Deleting an index
You can delete an index using the client.indices.delete() method:
response = client.indices.delete(
index = 'python-test-index'
)
Sample program
The following sample program creates a client, adds an index with non-default settings, inserts a document, performs bulk operations, searches for the document, deletes the document, and then deletes the index:
from opensearchpy import OpenSearch
host = 'localhost'
port = 9200
auth = ('admin', 'admin') # For testing only. Don't store credentials in code.
ca_certs_path = '/full/path/to/root-ca.pem' # Provide a CA bundle if you use intermediate CAs with your root CA.
# Optional client certificates if you don't want to use HTTP basic authentication.
# client_cert_path = '/full/path/to/client.pem'
# client_key_path = '/full/path/to/client-key.pem'
# Create the client with SSL/TLS enabled, but hostname verification disabled.
client = OpenSearch(
hosts = [{'host': host, 'port': port}],
http_compress = True, # enables gzip compression for request bodies
http_auth = auth,
# client_cert = client_cert_path,
# client_key = client_key_path,
use_ssl = True,
verify_certs = True,
ssl_assert_hostname = False,
ssl_show_warn = False,
ca_certs = ca_certs_path
)
# Create an index with non-default settings.
index_name = 'python-test-index'
index_body = {
'settings': {
'index': {
'number_of_shards': 4
}
}
}
response = client.indices.create(index_name, body=index_body)
print('\nCreating index:')
print(response)
# Add a document to the index.
document = {
'title': 'Moneyball',
'director': 'Bennett Miller',
'year': '2011'
}
id = '1'
response = client.index(
index = index_name,
body = document,
id = id,
refresh = True
)
print('\nAdding document:')
print(response)
# Perform bulk operations
movies = '{ "index" : { "_index" : "my-dsl-index", "_id" : "2" } } \n { "title" : "Interstellar", "director" : "Christopher Nolan", "year" : "2014"} \n { "create" : { "_index" : "my-dsl-index", "_id" : "3" } } \n { "title" : "Star Trek Beyond", "director" : "Justin Lin", "year" : "2015"} \n { "update" : {"_id" : "3", "_index" : "my-dsl-index" } } \n { "doc" : {"year" : "2016"} }'
client.bulk(movies)
# Search for the document.
q = 'miller'
query = {
'size': 5,
'query': {
'multi_match': {
'query': q,
'fields': ['title^2', 'director']
}
}
}
response = client.search(
body = query,
index = index_name
)
print('\nSearch results:')
print(response)
# Delete the document.
response = client.delete(
index = index_name,
id = id
)
print('\nDeleting document:')
print(response)
# Delete the index.
response = client.indices.delete(
index = index_name
)
print('\nDeleting index:')
print(response)