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6331807b95
In addition, there are also a number of changes in nodejs to the docstrings of existing methods because this PR adds a jsdoc linter.
81 lines
2.6 KiB
Python
81 lines
2.6 KiB
Python
from typing import Dict, List, Optional, Tuple
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import pyarrow as pa
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class Index:
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@staticmethod
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def ivf_pq(
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distance_type: Optional[str],
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num_partitions: Optional[int],
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num_sub_vectors: Optional[int],
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max_iterations: Optional[int],
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sample_rate: Optional[int],
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) -> Index: ...
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@staticmethod
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def btree() -> Index: ...
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class Connection(object):
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async def table_names(
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self, start_after: Optional[str], limit: Optional[int]
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) -> list[str]: ...
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async def create_table(
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self, name: str, mode: str, data: pa.RecordBatchReader
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) -> Table: ...
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async def create_empty_table(
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self, name: str, mode: str, schema: pa.Schema
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) -> Table: ...
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class Table:
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def name(self) -> str: ...
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def __repr__(self) -> str: ...
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async def schema(self) -> pa.Schema: ...
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async def add(self, data: pa.RecordBatchReader, mode: str) -> None: ...
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async def update(self, updates: Dict[str, str], where: Optional[str]) -> None: ...
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async def count_rows(self, filter: Optional[str]) -> int: ...
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async def create_index(
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self, column: str, config: Optional[Index], replace: Optional[bool]
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): ...
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async def version(self) -> int: ...
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async def checkout(self, version): ...
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async def checkout_latest(self): ...
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async def restore(self): ...
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async def list_indices(self) -> List[IndexConfig]: ...
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def query(self) -> Query: ...
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def vector_search(self) -> VectorQuery: ...
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class IndexConfig:
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index_type: str
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columns: List[str]
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async def connect(
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uri: str,
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api_key: Optional[str],
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region: Optional[str],
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host_override: Optional[str],
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read_consistency_interval: Optional[float],
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) -> Connection: ...
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class RecordBatchStream:
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def schema(self) -> pa.Schema: ...
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async def next(self) -> Optional[pa.RecordBatch]: ...
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class Query:
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def where(self, filter: str): ...
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def select(self, columns: Tuple[str, str]): ...
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def limit(self, limit: int): ...
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def nearest_to(self, query_vec: pa.Array) -> VectorQuery: ...
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async def execute(self) -> RecordBatchStream: ...
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class VectorQuery:
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async def execute(self) -> RecordBatchStream: ...
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def where(self, filter: str): ...
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def select(self, columns: List[str]): ...
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def select_with_projection(self, columns: Tuple[str, str]): ...
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def limit(self, limit: int): ...
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def column(self, column: str): ...
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def distance_type(self, distance_type: str): ...
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def postfilter(self): ...
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def refine_factor(self, refine_factor: int): ...
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def nprobes(self, nprobes: int): ...
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def bypass_vector_index(self): ...
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