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API Reference

connect

Connects to the Infinity server and gets an Infinity object.

infinity_obj = infinity.connect(REMOTE_HOST)

Details

This method connect to the Infinity server and return a infinity object.

Parameters

  • REMOTE_HOST = NetworkAddress("127.0.0.1", 9080)

Returns

  • success: An Infinity object.
  • failure: Exception

infinity_obj.disconnect

Disconnects from the Infinity server.

infinity_obj.disconnect()

Details

This method disconnects the current Infinity object from the server.

It is automatically called when an Infinity object is destructed.

Returns

  • success:
    • response success is True
  • failure: Exception

infinity_obj.create_database

Creates a database.

infinity_obj.create_database("my_database")

Details

This method creates a database by name.

Parameters

  • db_name : str

Returns

  • success:
    • response success is True
  • failure: Exception

infinity_obj.drop_database

Drops a database.

infinity_obj.drop_database("my_database")

Details

This method drops a database by name.

Parameters

  • db_name : str Name of the database to drop.

Returns

  • success:
    • response success is True
  • failure: Exception

infinity_obj.list_databases

Lists all databases.

infinity_obj.list_databases()

Details

This method lists all databases.

Returns

  • success:
    • response success is True.
    • response db_names list[str]
  • failure: Exception

infinity_obj.get_database

Gets a database object.

db_obj=infinity_obj.get_database("default")

Details

This method retrieves a database object by name.

Parameters

  • db_name : str The name of the database to retrieve.

Returns

  • success:
    • A database object.
  • failure: Exception

db_obj.create_table

Creates a table.

db_obj.create_table("test_create_varchar_table",
	                  {"c1": "varchar, primary key", "c2": "float"}, None)

db_obj.create_table("test_create_embedding_table", 
										{"c1": "vector,128,float"}, None)

Details

numeric or varchar

  • columns_definition : dict
    • key: column name: str
    • value: <datatype>,<constraint>,<constraint> :str

embedding

  • columns_definition : dict
    • key: column name: str
    • value: vector,<dimension>,<element_type> :str

Parameters

  • table_name : str
  • columns_definition : dict[str, str]
  • options : None

Returns

  • success:
    • response success is True
  • failure: Exception

db_obj.drop_table

Drops a table.

db_obj.drop_table("test_create_varchar_table", if_exists=True)

Details

Drops a table by name.

Parameters

  • table_name : str The name of the table to drop.
  • if_exists : bool

Returns

  • success:
    • response success is True
  • failure: Exception

db_obj.get_table

Gets a table object.

table_obj = db_obj.get_table("test_create_varchar_table")

Details

This method retrieves a table object by name.

Parameters

  • table_name : str The name of the intended table.

Returns

  • success:
    • A table object
  • failure: Exception

db_obj.list_tables

Lists all tables.

db_obj.list_tables()

Details

This method lists all tables in the database.

Returns

  • success:
    • response success is True
    • response table_names list[str]
  • failure: Exception

table_obj.create_index

Creates an index by IndexInfo list.

db_obj.create_table("test_index_ivfflat", {
            "c1": "vector,1024,float"}, None)
db_obj.get_table("test_index_ivfflat")
table_obj.create_index("my_index",
                       [index.IndexInfo("c1",index.IndexType.IVFFlat,
	                      [		
													index.InitParameter("centroids_count", "128"),
	                        index.InitParameter("metric", "l2")
												])], None)
db_obj.create_table(
            "test_index_hnsw", {"c1": "vector,1024,float"}, None)

db_obj.get_table("test_index_hnsw")
table_obj.create_index("my_index",
                       [index.IndexInfo("c1",index.IndexType.Hnsw,
                       [
                          index.InitParameter("M", "16"),
                          index.InitParameter("ef_construction", "50"),
                          index.InitParameter("ef", "50"),
                          index.InitParameter("metric", "l2")
                        ])], None)
db_obj.create_table(
            "test_index_fulltext", {"doctitle": "varchar", "docdate": "varchar", "body": "varchar"}, None)

db_obj.get_table("test_index_fulltext")
table_obj.create_index("my_index",
                             [index.IndexInfo("body",
							                                index.IndexType.IRSFullText,
	                                            [index.InitParameter("ANALYZER", "segmentation")]),
                              index.IndexInfo("doctitle",
                                              index.IndexType.IRSFullText,
                                              []),
                              index.IndexInfo("docdate",
                                              index.IndexType.IRSFullText,
                                              []),
                              ], None)

Details

This method uses indexInfo to create an index.

  • IndexInfo
    • column_name : str Name of the column. Required.
    • index_type : Enum. The index type. Includes:
      • IVFFlat
      • HnswLVQ
      • ``Hnsw`
      • IRSFullText
    • index_param_list : list[InitParameter]
      • param_name : str
      • param_value : str
      • example
        • InitParameter("M", "16")
        • InitParameter("ef_construction", "50")
        • InitParameter("ef", "50")
        • InitParameter("metric", "l2")
        • InitParameter("centroids_count", "128")

Parameters

  • index_name : str
  • index_infos : list[IndexInfo]
  • options : None

Returns

  • success:
    • response success is True
  • failure: Exception

table_obj.drop_index

Drops an index.

table_obj.drop_index("my_index")

Details

This method drops an index by index name.

Parameters

  • index_name : str The name of the index to drop.

Returns

  • success:
    • response success is True
  • failure: Exception

table_obj.insert

Inserts a record into the table.

table_obj.insert([{"profile": [1.1, 2.2, 3.3], "age": 30, "c3": "Michael"}])
table_obj.insert([{"c1": [1.1, 2.2, 3.3]}])

Details

This method inserts a record into a table. The inserted record is a list of dict.

  • dict
    • key: column name :str
    • value: str ,int , float ,list

Parameters

  • data : list[dict[str, Union[str, int, float, list[Union[int, float]]]]]

Returns

  • success:
    • response success is True
  • failure: Exception

table_obj.import

Imports data into the table.

table_obj.import_data(test_csv_dir, None)

Details

This method imports data into the table object. Supported file types:

  • csv
  • fvecs
  • json

Parameters

  • file_path : str
  • options : None

Returns

  • success:
    • response success is True
  • failure: Exception

table_obj.delete

Delete rows by condition.

table_obj.delete("c1 = 1")
table_obj.delete()

Details

The condition is similar to the WHERE conditions in SQL. If condition is not specified, this method deletes all data in the table object.

Parameters

  • cond : Optional[str]
  • options : None

Returns

  • success:
    • response success is True
  • failure: Exception

table_obj.update

Updates rows by condition.

table_obj.update("c1 = 1", [{"c2": 90, "c3": 900}])

Details

This method searches for rows that satisfy the search condition and updates them using the provided values.

  • The search condition is similar to the WHERE conditions in SQL.
  • Data is what needs to be updated.

Parameters

  • cond : str
  • data : list[dict[str, Union[str, int, float]]]

Returns

  • success:
    • response success is True
  • failure: Exception

table_obj.query_builder

Gets a query_builder by self.

query_builder=table_obj.query_builder()

Details

This method retrieves a query_builder by self table.

Returns

  • success:
    • A query_builder object.
  • failure: Exception

query_builder.output

Specifies the columns to display in the search output.

query_builder.output(["num", "body"])
# To display all columns
query_builder.output(["*"])
# To display row ID
query_builder.output(["_row_id"])

Details

This method specifies the columns to display in the search output. You must input a list of str

  • To display all columns:["*"]
  • To display row ID: ["_row_id"]

Parameters

  • columns : Optional[list[str]]

Returns

  • self : InfinityThriftQueryBuilder

query_builder.filter

Builds a filtering condition expression.

query_builder.filter("(-7 < c1 or 9 >= c1) and (c2 = 3)")

Details

This method builds a filtering expression.

str: Similar to the WHERE condition in SQL.

Parameters

  • where : Optional[str]

Returns

  • self : InfinityThriftQueryBuilder

query_builder.knn

Builds a KNN search expression.

query_builder.knn('col1', [0.1,0.2,0.3], 'float', 'l2', 100)
query_builder.knn('vec', [3.0] * 5, 'float', 'ip', 2)

Details

VEC supports list or np.ndarray.

Parameters

  • vector_column_name : str

  • embedding_data : VEC

  • embedding_data_type : `str``

    • float
    • int

  • distance_type : str

    • l2
    • cosine
    • ip
    • hamming

  • topn : int

Returns

  • self : InfinityThriftQueryBuilder

query_builder.match

Builds a full-text search expression.

query_builder.match('body', 'harmful', 'topn=2')

Details

This method builds a full-text search expression.

Parameters

  • fields : str The text’s body
  • matching_text : str The text to match.
  • options_text : str 'topn=2': The display count is 2.

Returns

  • self : InfinityThriftQueryBuilder

query_builder.fusion

Builds a fusion expression.

query_builder.fusion('rrf')

Details

rrf: Reciprocal rank fusion method.

Reciprocal rank fusion (RRF) is a method that combines multiple result sets with different relevance indicators into one result set. RRF does not requires tuning, and the different relevance indicators do not have to be related to each other to achieve high-quality results.

Parameters

  • method : str

Returns

  • self : InfinityThriftQueryBuilder

query_builder.to_result

Returns a data result.

table_obj.query_builder().output(["*"]).to_result()

Details

This method returns a data result of Python's built-in type.

(data_dict, data_type_dict)

Returns

  • tuple[dict[str, list[Any]], dict[str, Any]]

query_builder.to_df

Returns a pandas result.

table_obj.query_builder().output(["*"]).to_df()

Details

This method returns a data result in pandas DataFrame.

Returns

  • pandas.DataFrame

query_builder.to_pl

Returns a polars result.

table_obj.query_builder().output(["*"]).to_pl()

Details

This method returns a data result in polars DataFrame

Returns

  • polars.DataFrame

query_builder.to_arrow

Returns a pyarrow result.

table_obj.query_builder().output(["*"]).to_arrow()

Details

The method returns a data result in arrow Table.

Returns

  • pyarrow.Table