Partition()

This is the constructor method to create a partition in the specified collection.

Invocation

Partition(collection, name, description='', **kwargs)

Parameters

Parameter	Description	Type	Required
collection	Name of the collection	String	True
name	Name of the partition to create	String	True
description	Description of the collection	String	False

Return

A new partition object created with the specified name.

Properties

Property	Description	Type
name	Name of the partition	String
description	Description of the collection	String
is_empty	Boolean value to indicate if the partition is empty	Bool
num_entities	Number of entities in the partition	Integer

Example

from pymilvus import Partition
partition = Partition("book", "novel", "")

delete()

This method deletes entities from a specified partition.

Invocation

delete(expr, timeout=None, **kwargs)

Parameters

Parameter	Description	Type	Required
expr	Boolean expression that specifies the primary keys of the entities to delete	String	True
timeout	An optional duration of time in seconds to allow for the RPC. If it is set to None, the client keeps waiting until the server responds or error occurs.	Float	False

Return

A MutationResult object.

Properties

Property	Description	Type
delete_count	Number of the entities to delete	Integer

Raises

• RpcError: error if gRPC encounter an error.
• ParamError: error if the parameters are invalid.
• BaseException: error if the return result from server is not ok.

Example

import random
data = [
  [i for i in range(2000)],
  [i for i in range(10000, 12000)],
  [[random.random() for _ in range(2)] for _ in range(2000)],
]
from pymilvus import Partition
partition = Partition("book", "novel", "")
partition.insert(data)
expr = "book_id in [0,1]"
partition.delete(expr)

drop()

This method drops a partition and the data within.

Invocation

drop(timeout=None, **kwargs)

Parameters

Parameter	Description	Type	Required
timeout	An optional duration of time in seconds to allow for the RPC. If it is set to None, the client keeps waiting until the server responds or error occurs.	Float	False

Return

No return.

Raises

PartitionNotExistException: error if the partition does not exist.

Example

from pymilvus import Partition
partition = Partition("book", "novel", "")
partition.drop()

get_replicas()

This method checks the replica information.

Invocation

get_replicas()

Return

The information about replica groups and the corresponding query nodes and shard.

Raises

Example

from pymilvus import Partition
partition = Partition("book", "novel")
partition.load(replica_number=2)    # Load partition as 2 replicas
result = partition.get_replicas()
print(result)

insert()

This method inserts data into a specified partition.

Invocation

insert(data, timeout=None, **kwargs)

Parameters

Parameter	Description	Type	Required
data	Data to insert	list-like(list, tuple)	True
timeout	An optional duration of time in seconds to allow for the RPC. If it is set to None, the client keeps waiting until the server responds or error occurs.	Float	False

Return

A MutationResult object.

Properties

Property	Description	Type
insert_count	Number of the inserted entities	Integer
primary_keys	List of the primary keys of the inserted entities	list[String]

Raises

PartitionNotExistException: error if the partition does not exist.

Example

import random
data = [
  [i for i in range(2000)],
  [i for i in range(10000, 12000)],
  [[random.random() for _ in range(2)] for _ in range(2000)],
]
from pymilvus import Partition
partition = Partition("book", "novel", "")
partition.insert(data)

load()

This method loads the specified partition to memory (for search or query).

Invocation

load(timeout=None, **kwargs)

Parameters

Parameter	Description	Type	Required
replica_number	Number of the replica(s) to load	Integer	False
timeout	An optional duration of time in seconds to allow for the RPC. If it is set to None, the client keeps waiting until the server responds or error occurs.	Float	False
kwargs _async	Boolean value to indicate if to invoke asynchronously	Bool	False

Return

No return.

Raises

InvalidArgumentException: error if the argument is invalid.

Example

from pymilvus import Partition
partition = Partition("book", "novel", "")
partition.load()

query()

This method conducts a vector query in a specified partition.

Invocation

query(expr, output_fields=None, timeout=None, **kwargs)

Parameters

Parameter	Description	Type	Required
expr	Boolean expression to filter the data	String	True
output_fields	List of names of fields to output	list[String]	False
timeout	An optional duration of time in seconds to allow for the RPC. If it is set to None, the client keeps waiting until the server responds or error occurs.	Float	False
kwargs consistency_level guarantee_timestamp graceful_time travel_timestamp	Consistency level used in the search Milvus searches on the data view before this timestamp when it is provided. Otherwise, it searches the most updated data view. It can be only used in Customized level of consistency. PyMilvus will use current timestamp minus the graceful_time as the guarantee_timestamp for search. It can be only used in Bounded level of consistency. Timestamp that is used for Time Travel. Users can specify a timestamp in a search to get results based on a data view at a specified point in time.	String/Integer Integer Integer Integer	False

Return

A list that contains all results.

Raises

• RpcError: error if gRPC encounter an error.
• ParamError: error if the parameters are invalid.
• BaseException: error if the return result from server is not ok.

Example

from pymilvus import Partition
partition = Partition("novel")
res = collection.query(
  expr = "book_id in [2,4,6,8]", 
  output_fields = ["book_id", "book_intro"],
  consistency_level="Strong"
)
sorted_res = sorted(res, key=lambda k: k['book_id'])
sorted_res

release()

This method releases the specified partition from memory.

Invocation

release(timeout=None, **kwargs)

Parameters

Parameter	Description	Type	Required
timeout	An optional duration of time in seconds to allow for the RPC. If it is set to None, the client keeps waiting until the server responds or error occurs.	Float	False

Return

No return.

Raises

PartitionNotExistException: error if the partition does not exist.

Example

from pymilvus import Partition
partition = Partition("book", "novel", "")
partition.load()
partition.release()

search()

This method conducts a vector similarity search in a specified partition.

Invocation

search(data, anns_field, param, limit, expr=None, output_fields=None, timeout=None, round_decimal=-1, **kwargs)

Parameters

Parameter	Description	Type	Required
data	Data to search with	list[list[Float]]	True
anns_field	Name of the vector field to search on	String	True
param	Specific search parameter(s) of the index on the vector field	Dict	True
limit	Number of nearest records to return	Integer	True
expr	Boolean expression to filter the data	String	False
output_fields	List of names of fields to output	list[String]	False
timeout	An optional duration of time in seconds to allow for the RPC. If it is set to None, the client keeps waiting until the server responds or error occurs.	Float	False
round_decimal	Number of the decimal places of the returned distance	Integer	False
kwargs _async _callback consistency_level guarantee_timestamp graceful_time travel_timestamp	Boolean value to indicate if to invoke asynchronously Function that will be invoked after server responds successfully. It takes effect only if _async is set to True. Consistency level used in the search Milvus searches on the data view before this timestamp when it is provided. Otherwise, it searches the most updated data view. It can be only used in Customized level of consistency. PyMilvus will use current timestamp minus the graceful_time as the guarantee_timestamp for search. It can be only used in Bounded level of consistency. Timestamp that is used for Time Travel. Users can specify a timestamp in a search to get results based on a data view at a specified point in time.	Bool Function String/Integer Integer Integer Integer	False

Return

A SearchResult object, an iterable, 2d-array-like class whose first dimension is the number of vectors to query (nq), and the second dimension is the number of limit (topk).

Raises

• RpcError: error if gRPC encounter an error.
• ParamError: error if the parameters are invalid.
• BaseException: error if the return result from server is not ok.

Example

search_params = {"metric_type": "L2", "params": {"nprobe": 10}}
from pymilvus import Partition
partition = Partition("novel")
results = partition.search(
    data=[[0.1, 0.2]], 
    anns_field="book_intro", 
    param=search_params, 
    limit=10, 
    expr=None,
    consistency_level="Strong"
)
results[0].ids
results[0].distances