Connect the Python driver to your database
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This driver supports the vector and non-vector data types. DataStax recommends the Data API and clients for Serverless (Vector) databases. You can use the Data API to perform CQL operations on your table data in Serverless (Vector) databases. DataStax recommends drivers only for Serverless (Non-Vector) databases, existing applications that previously used a CQL-based driver, or if you need to use some CQL functions that aren’t supported by the Data API. For more information, see Connection methods comparison. |
Select one of the following methods for connecting the Python driver to your database.
Prerequisites
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Download your database’s Secure Connect Bundle (SCB).
Basic configuration
This configuration is recommended for basic use cases that are not proofs of concept or production use.
It initializes a session for connecting to your database using the cassandra-driver and sets up the connection with an SCB and authentication details sourced from environment variables.
import os
from cassandra.cluster import Cluster
from cassandra.auth import PlainTextAuthProvider
session = Cluster(
cloud={"secure_connect_bundle": os.environ["ASTRA_DB_SECURE_BUNDLE_PATH"]},
auth_provider=PlainTextAuthProvider("token", os.environ["ASTRA_DB_APPLICATION_TOKEN"]),
).connect()Production configuration
This configuration is for proofs of concept or production use. This code example includes additional configurations for connection timeout, request timeout, and protocol version.
import os
from cassandra.cluster import Cluster, ExecutionProfile, EXEC_PROFILE_DEFAULT, ProtocolVersion
from cassandra.auth import PlainTextAuthProvider
cloud_config= {
'secure_connect_bundle': os.environ["ASTRA_DB_SECURE_BUNDLE_PATH"],
'connect_timeout': 30
}
auth_provider=PlainTextAuthProvider("token", os.environ["ASTRA_DB_APPLICATION_TOKEN"])
profile = ExecutionProfile(request_timeout=30)
cluster = Cluster(
cloud=cloud_config,
auth_provider=auth_provider,
execution_profiles={EXEC_PROFILE_DEFAULT: profile},
protocol_version=ProtocolVersion.V4
)
session = cluster.connect()See the Python quickstart for details on how to install the package, connect to a Serverless (Vector) database, create a table and vector-compatible Storage-Attached Index (SAI), load data, and perform a similarity search.
