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155 lines (141 loc) · 5.34 KB
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from typing import Dict, List, Optional, Tuple, Any, Union, Literal
import pyarrow as pa
from .index import BTree, IvfFlat, IvfPq, Bitmap, LabelList, HnswPq, HnswSq, FTS
class Connection(object):
uri: str
async def table_names(
self, start_after: Optional[str], limit: Optional[int]
) -> list[str]: ...
async def create_table(
self,
name: str,
mode: str,
data: pa.RecordBatchReader,
storage_options: Optional[Dict[str, str]] = None,
data_storage_version: Optional[str] = None,
enable_v2_manifest_paths: Optional[bool] = None,
) -> Table: ...
async def create_empty_table(
self,
name: str,
mode: str,
schema: pa.Schema,
storage_options: Optional[Dict[str, str]] = None,
data_storage_version: Optional[str] = None,
enable_v2_manifest_paths: Optional[bool] = None,
) -> Table: ...
async def rename_table(self, old_name: str, new_name: str) -> None: ...
async def drop_table(self, name: str) -> None: ...
class Table:
def name(self) -> str: ...
def __repr__(self) -> str: ...
def is_open(self) -> bool: ...
def close(self) -> None: ...
async def schema(self) -> pa.Schema: ...
async def add(
self, data: pa.RecordBatchReader, mode: Literal["append", "overwrite"]
) -> None: ...
async def update(self, updates: Dict[str, str], where: Optional[str]) -> None: ...
async def count_rows(self, filter: Optional[str]) -> int: ...
async def create_index(
self,
column: str,
index: Union[IvfFlat, IvfPq, HnswPq, HnswSq, BTree, Bitmap, LabelList, FTS],
replace: Optional[bool],
): ...
async def list_versions(self) -> List[Dict[str, Any]]: ...
async def version(self) -> int: ...
async def checkout(self, version: int): ...
async def checkout_latest(self): ...
async def restore(self): ...
async def list_indices(self) -> list[IndexConfig]: ...
async def delete(self, filter: str): ...
async def add_columns(self, columns: list[tuple[str, str]]) -> None: ...
async def alter_columns(self, columns: list[dict[str, Any]]) -> None: ...
async def optimize(
self,
*,
cleanup_since_ms: Optional[int] = None,
delete_unverified: Optional[bool] = None,
) -> OptimizeStats: ...
def query(self) -> Query: ...
def vector_search(self) -> VectorQuery: ...
class IndexConfig:
index_type: str
columns: List[str]
async def connect(
uri: str,
api_key: Optional[str],
region: Optional[str],
host_override: Optional[str],
read_consistency_interval: Optional[float],
) -> Connection: ...
class RecordBatchStream:
def schema(self) -> pa.Schema: ...
async def next(self) -> Optional[pa.RecordBatch]: ...
class Query:
def where(self, filter: str): ...
def select(self, columns: Tuple[str, str]): ...
def select_columns(self, columns: List[str]): ...
def limit(self, limit: int): ...
def offset(self, offset: int): ...
def fast_search(self): ...
def with_row_id(self): ...
def postfilter(self): ...
def nearest_to(self, query_vec: pa.Array) -> VectorQuery: ...
def nearest_to_text(self, query: dict) -> FTSQuery: ...
async def execute(self, max_batch_length: Optional[int]) -> RecordBatchStream: ...
class FTSQuery:
def where(self, filter: str): ...
def select(self, columns: List[str]): ...
def limit(self, limit: int): ...
def offset(self, offset: int): ...
def fast_search(self): ...
def with_row_id(self): ...
def postfilter(self): ...
def get_query(self) -> str: ...
def add_query_vector(self, query_vec: pa.Array) -> None: ...
def nearest_to(self, query_vec: pa.Array) -> HybridQuery: ...
async def execute(self, max_batch_length: Optional[int]) -> RecordBatchStream: ...
async def explain_plan(self) -> str: ...
class VectorQuery:
async def execute(self) -> RecordBatchStream: ...
def where(self, filter: str): ...
def select(self, columns: List[str]): ...
def select_with_projection(self, columns: Tuple[str, str]): ...
def limit(self, limit: int): ...
def offset(self, offset: int): ...
def column(self, column: str): ...
def distance_type(self, distance_type: str): ...
def postfilter(self): ...
def refine_factor(self, refine_factor: int): ...
def nprobes(self, nprobes: int): ...
def bypass_vector_index(self): ...
def nearest_to_text(self, query: dict) -> HybridQuery: ...
class HybridQuery:
def where(self, filter: str): ...
def select(self, columns: List[str]): ...
def limit(self, limit: int): ...
def offset(self, offset: int): ...
def fast_search(self): ...
def with_row_id(self): ...
def postfilter(self): ...
def distance_type(self, distance_type: str): ...
def refine_factor(self, refine_factor: int): ...
def nprobes(self, nprobes: int): ...
def bypass_vector_index(self): ...
def to_vector_query(self) -> VectorQuery: ...
def to_fts_query(self) -> FTSQuery: ...
def get_limit(self) -> int: ...
def get_with_row_id(self) -> bool: ...
class CompactionStats:
fragments_removed: int
fragments_added: int
files_removed: int
files_added: int
class RemovalStats:
bytes_removed: int
old_versions_removed: int
class OptimizeStats:
compaction: CompactionStats
prune: RemovalStats