The get_vector_bucket interface is used to query the metadata of a vector bucket. This article describes how to retrieve vector bucket configuration information through the get_vector_bucket interface of the TOS Vectors Python SDK.

Notes

You need to fill in the region and access domain in the sample code according to your actual situation. For details, see Region and Access Domain (Endpoint).

To prevent key leakage, the sample code reads the Access Key ID and Secret Access Key from environment variables. Therefore, before using the SDK, configure long-term access credentials. For details, see Configure Long-Term Access Credentials.

The TOS Vectors Python SDK supports using temporary access credentials and also allows configuring timeout mechanisms, retry policies, and other settings. You can adjust these flexibly based on business needs to enhance application security. For details, see Common Configuration Scenarios.

Permissions required

The primary account has all permissions by default, but IAM users have no permissions by default. If you need to perform the get_vector_bucket operation using a sub-account, the primary account must grant the following permissions to the sub-account through IAM policies and bucket policies:

tosvectors:GetVectorBucket

Code example

Query information of the specified vector bucket

# Query information for a specified vector bucket​
import os​
import tos​
​
# Retrieve AK and SK information from environment variables.​
ak = os.getenv('TOS_ACCESS_KEY')​
sk = os.getenv('TOS_SECRET_KEY')​
# Fill in your endpoint and your region with the endpoint corresponding to the bucket's region. # For example, for China (Beijing), set your endpoint to https://tosvectors-cn-beijing.volces.com and your region to cn-beijing.​
endpoint = 'Provide your endpoint'​
region = 'Provide your region'​
vector_bucket_name = 'Provide your bucket name'​
​
# Retrieve Account ID from Environment Variables​
account_id = os.getenv('TOS_ACCOUNT_ID')​
​
try:​
    # Create a VectorClient object; all vector operations are handled through VectorClient​
    client = tos.VectorClient(ak, sk, endpoint, region)​
    ​
    # Query detailed information for a specified vector bucket​
    # You need to provide the vector bucket name and account ID​
    result = client.get_vector_bucket(vector_bucket_name, account_id)​
    ​
    # Print the message indicating successful query​
    print('Query vector bucket information successfully')​
    print('Request ID: {}'.format(result.request_id))​
    print('Status codes: {}'.format(result.status_code))​
    ​
    # Print detailed information about vector storage buckets​
    if result.vector_bucket:​
        print('\n Vector bucket details:')​
        print('Vector bucket name: {}'.format(result.vector_bucket.vector_bucket_name))​
        print('Vector bucket TRN: {}'.format(result.vector_bucket.vector_bucket_trn))​
        print('Creation time: {}'.format(result.vector_bucket.creation_time))​
    ​
except tos.exceptions.TosClientError as e:​
    # The operation failed and a client exception was caught. This is usually due to invalid request parameters or a network exception.​
    print('fail with client error, message:{}, cause: {}'.format(e.message, e.cause))​
except tos.exceptions.TosServerError as e:​
    # The operation failed and a server exception occurred. See the response for the error details.​
    print('fail with server error, code: {}'.format(e.code))​
    # Use the request ID for troubleshooting purposes. We strongly recommend including the request ID in the logs.​
    print('error with request id: {}'.format(e.request_id))​
    print('error with message: {}'.format(e.message))​
    print('error with http code: {}'.format(e.status_code))​
    print('error with ec: {}'.format(e.ec))​
    print('error with request url: {}'.format(e.request_url))​
except Exception as e:​
    print('fail with unknown error: {}'.format(e))​