qdrant_client.uploader.uploader module

class BaseUploader

Bases: Worker, ABC

classmethod iterate_batches(vectors: Union[dict[str, numpy.ndarray[tuple[int, ...], numpy.dtype[Union[numpy.bool, numpy.int8, numpy.int16, numpy.int32, numpy.int64, numpy.uint8, numpy.uint16, numpy.uint32, numpy.uint64, numpy.float16, numpy.float32, numpy.float64, numpy.longdouble]]]], ndarray[tuple[int, ...], dtype[Union[bool, int8, int16, int32, int64, uint8, uint16, uint32, uint64, float16, float32, float64, longdouble]]], Iterable[Union[List[float], List[List[float]], Dict[str, Union[List[float], SparseVector, List[List[float]], Document, Image, InferenceObject]], Document, Image, InferenceObject]]], payload: Optional[Iterable[dict]], ids: Optional[Iterable[Union[int, str]]], batch_size: int) → Iterable

classmethod iterate_records_batches(records: Iterable[Union[PointStruct, Record]], batch_size: int) → Iterable

iter_batch(iterable: Union[Iterable, Generator], size: int) → Iterable

>>> list(iter_batch([1,2,3,4,5], 3))
[[1, 2, 3], [4, 5]]