API reference¶

Constructor¶

Methods¶

APIs¶

class milvus.Milvus(host=None, port=None, handler='GRPC', pool='SingletonThread', **kwargs)¶

compact(collection_name, timeout=None, **kwargs)¶

Compacts segments in a collection. This function is recommended after deleting vectors.

Parameters

collection_name (str) -- Name of the collections to compact.

count_entities(collection_name, timeout=30)¶

Returns the number of vectors in a collection.

Parameters

collection_name (str) -- target table name.

Returns

Status: indicate if operation is successful

res: int, table row count

create_collection(param, timeout=30)¶

Creates a collection.

Parameters

• param (dict) --

  Information needed to create a collection.

  `param={'collection_name': 'name',

  'dimension': 16, 'index_file_size': 1024 (default)， 'metric_type': Metric_type.L2 (default) }`

• timeout (double) -- Timeout in seconds.

Returns

Whether the operation is successful.

Return type

Status

create_index(collection_name, index_type=None, params=None, timeout=None, **kwargs)¶

Creates index for a collection.

Parameters

• collection_name (str) -- Collection used to create index.

• index -- index params

• timeout (int) --

  grpc request timeout.

  if timeout = -1, method invoke a synchronous call, waiting util grpc response else method invoke a asynchronous call, timeout work here

Returns

Whether the operation is successful.

create_partition(collection_name, partition_tag, timeout=30)¶

create a partition for a collection.

Parameters

• collection_name (str) -- Name of the collection.

• partition_name (str) -- Name of the partition.

• partition_tag (str) -- Name of the partition tag.

• timeout (int) -- time waiting for response.

Returns

Status: Whether the operation is successful.

delete_entity_by_id(collection_name, id_array, timeout=None)¶

Deletes vectors in a collection by vector ID.

Parameters

• collection_name (str) -- Name of the collection.

• id_array (list[int]) -- list of vector id

Returns

Status: Whether the operation is successful.

drop_collection(collection_name, timeout=30)¶

Deletes a collection by name.

Parameters

collection_name (str) -- Name of the collection being deleted

Returns

Status, indicate if operation is successful

Return type

Status

drop_index(collection_name, timeout=30)¶

Removes an index.

Parameters

collection_name (str) -- target collection name.

Returns

Status: Whether the operation is successful.

：:rtype: Status

drop_partition(collection_name, partition_tag, timeout=30)¶

Deletes a partition in a collection.

Parameters

• collection_name (str) -- Collection name.

• partition_tag (str) -- Partition name.

• timeout (int) -- time waiting for response.

Returns

Status: Whether the operation is successful.

flush(collection_name_array=None, timeout=None, **kwargs)¶

Flushes vector data in one collection or multiple collections to disk.

Parameters

collection_name -- Name of one or multiple collections to flush.

get_collection_info(collection_name, timeout=30)¶

Returns information of a collection.

Parameters

collection_name (str) -- Name of the collection to describe.

Returns

(Status, table_schema) Status: indicate if query is successful table_schema: return when operation is successful

Return type

(Status, TableSchema)

get_collection_stats(collection_name, timeout=30)¶

Returns collection statistics information

Returns

Status: indicate if this operation is successful

statistics: statistics information

Return type

(Status, dict)

get_entity_by_id(collection_name, ids, timeout=None)¶

Returns raw vectors according to ids.

Parameters

• collection_name (str) -- Name of the collection

• ids (list) -- list of vector id

Returns

Status: indicate if invoke is successful

has_collection(collection_name, timeout=30)¶

Checks whether a collection exists.

Parameters

• collection_name (str) -- Name of the collection to check.

• timeout (int) -- Timeout in seconds.

Returns

Status: indicate whether the operation is successful. bool if given collection_name exists

has_partition(collection_name, partition_tag)¶

Check if specified partition exists.

Parameters

• collection_name (str) -- target table name.

• partition_tag (str) -- partition tag.

Returns

Status: Whether the operation is successful. exists: If specified partition exists

insert(collection_name, records, ids=None, partition_tag=None, params=None, timeout=None, **kwargs)¶

Insert vectors to a collection.

Parameters

• ids (list[int]) -- list of id

• collection_name (str) -- Name of the collection to insert vectors to.

• records -- List of vectors to insert.

• partition_tag (str or None. If partition_tag is None, vectors will be inserted to the collection rather than partitions.) -- Tag of a partition.

Returns

Status: Whether vectors are inserted successfully. ids: IDs of the inserted vectors.

Return type

(Status, list(int))

list_collections(timeout=30)¶

Returns collection list.

Returns

Status: indicate if this operation is successful

collections: list of collection names, return when operation

is successful

Return type

(Status, list[str])

list_partitions(collection_name, timeout=30)¶

Show all partitions in a collection.

Parameters

• collection_name (str) -- target table name.

• timeout (int) -- time waiting for response.

Returns

Status: Whether the operation is successful. partition_list:

load_collection(collection_name, partition_tags=None, timeout=None)¶

Loads a collection for caching.

Parameters

collection_name (str) -- collection to load

Returns

Status: indicate if invoke is successful

search(collection_name, top_k, query_records, partition_tags=None, params=None, timeout=None, **kwargs)¶

Search vectors in a collection.

Parameters

• collection_name (str) -- Name of the collection.

• top_k (int) -- number of vertors which is most similar with query vectors

• nprobe (int) -- cell number of probe

• query_records (list[list[float32]]) -- vectors to query

• partition_tags (list) -- tags to search

:return

Status: Whether the operation is successful. result: query result

Return type

(Status, TopKQueryResult)

search_in_segment(collection_name, file_ids, query_records, top_k, params=None, timeout=None, **kwargs)¶

Searches for vectors in specific segments of a collection.

The Milvus server stores vector data into multiple files. Searching for vectors in specific files is a method used in Mishards. Obtain more detail about Mishards, see <a href="https://github.com/milvus-io/milvus/tree/master/shards">

Parameters

• collection_name (str) -- table name been queried

• file_ids (list[str] or list[int]) -- Specified files id array

• query_records (list[list[float]]) -- all vectors going to be queried

• query_ranges --

  Optional ranges for conditional search.

  If not specified, search in the whole table

• top_k (int) -- how many similar vectors will be searched

Returns

Status: indicate if query is successful results: query result

Return type

(Status, TopKQueryResult)