Insert documents into a collection by using the SDK for Python - Vector Retrieval Service

This topic describes how to insert documents into a collection by using the SDK for Python.

Note

If the ID of a document to be inserted already exists, the existing document is not overwritten, and the insert operation is invalid for the document.

Prerequisites

A cluster is created. For more information, see Create a cluster.
An API key is obtained. For more information, see Manage API keys.
The SDK of the latest version is installed. For more information, see Install DashVector SDK.

API definition

Python

Collection.insert(
    docs: Union[Doc, List[Doc], Tuple, List[Tuple]],
    partition: Optional[str] = None,
    async_req: False
) -> DashVectorResponse

Example

Note

You need to replace YOUR_API_KEY with your API key and YOUR_CLUSTER_ENDPOINT with the endpoint of your cluster in the sample code for the code to run properly.
You need to create a collection named quickstart in advance. For more information, see the "Example" section of the Create a collection topic.

Python

import dashvector
from dashvector import Doc
import numpy as np

client = dashvector.Client(
    api_key='YOUR_API_KEY',
    endpoint='YOUR_CLUSTER_ENDPOINT'
)
collection = client.get(name='quickstart')

Insert a document

Python

# Insert a document by using a Doc object.
ret = collection.insert(
    Doc(
        id='1',
        vector=[0.1, 0.2, 0.3, 0.4]
    )
)
# Check whether the insert method is successfully called.
assert ret

# Simplified version: Use a tuple to insert a document.
ret = collection.insert(
    ('2', [0.1, 0.1, 0.1, 0.1])               # (id, vector)
)

Insert a document with fields

Python

# Insert a document and specify the values of related fields.
ret = collection.insert(
    Doc(
        id='3',
        vector=np.random.rand(4),
        fields={
            # Specify the values of fields that are predefined during collection creation.
            'name': 'zhangsan', 'weight':70.0, 'age':30, 
            # Specify schema-free fields and values.
            'anykey1': 'str-value', 'anykey2': 1,
            'anykey3': True, 'anykey4': 3.1415926
        }
    )
)

# Insert a document and specify the values of related fields.
ret = collection.insert(
    ('4', np.random.rand(4), {'foo': 'bar'})  # (id, vector, fields)
)

Insert multiple documents at a time

Python

# Use Doc objects to insert 10 documents at a time.
ret = collection.insert(
    [
        Doc(id=str(i+5), vector=np.random.rand(4)) for i in range(10)
    ]
)

# Simplified version: Use tuples to insert three documents.
ret = collection.insert(
    [
        ('15', [0.2,0.7,0.8,1.3], {'age': 20}),
        ('16', [0.3,0.6,0.9,1.2], {'age': 30}),
        ('17', [0.4,0.5,1.0,1.1], {'age': 40})
    ]                                         # List[(id, vector, fields)]
)

# Check whether the batch insert method is successfully called.
assert ret

Asynchronously insert documents

Python

# Asynchronously insert 10 documents at a time.
ret_funture = collection.insert(
    [
        Doc(id=str(i+18), vector=np.random.rand(4), fields={'name': 'foo' + str(i)}) for i in range(10)
    ],
    async_req=True
)
# Wait for the asynchronous insertion result.
ret = ret_funture.get()

Insert a document containing a sparse vector

Python

ret = collection.insert(
    Doc(
        id='28',
        vector=[0.1, 0.2, 0.3, 0.4],
        sparse_vector={1:0.4, 10000:0.6, 222222:0.8}
    )
)

Request parameters

Parameter	Type	Default value	Description
docs	Union[Doc, List[Doc], Tuple, List[Tuple]]	-	The one or more documents to be inserted.
partition	Optional[str]	None	Optional. The name of the partition.
async_req	bool	False	Optional. Specifies whether to enable the asynchronous mode.

Note

If the type of the docs parameter is Tuple, the elements in the tuple must be in the order of (id, vector) or (id, vector, fields). In this case, the tuple is equivalent to a Doc object.
Each field in a Doc object can be set to a user-defined key-value pair. In a key-value pair, the key must be of the str type, and the value can be of the str, int, bool, or float type.
1. If a key is predefined during collection creation, the value must be of the predefined type.
2. If the key is not predefined during collection creation, the value can be of the str, int, bool, or float type.
For more information about predefining fields, see Schema-free.

Response parameters

Note

A DashVectorResponse object is returned, which contains the operation result, as described in the following table.

Parameter	Type	Description	Example
code	int	The returned status code. For more information, see Status codes.	0
message	str	The returned message.	success
request_id	str	The unique ID of the request.	19215409-ea66-4db9-8764-26ce2eb5bb99