Shortcuts

qdrant_client.uploader.uploader module

class BaseUploader[source]

Bases: Worker, ABC

classmethod iterate_batches(vectors: Union[Dict[str, ndarray[Any, dtype[Union[bool_, int8, int16, int32, int64, uint8, uint16, uint32, uint64, float16, float32, float64, float128]]]], ndarray[Any, dtype[Union[bool_, int8, int16, int32, int64, uint8, uint16, uint32, uint64, float16, float32, float64, float128]]], Iterable[Union[List[float[float]], Dict[str[str], Union[List[float[float]], SparseVector]]]]], payload: Optional[Iterable[dict]], ids: Optional[Iterable[Union[int[int], str[str]]]], batch_size: int) Iterable[source]
classmethod iterate_records_batches(records: Iterable[Union[Record, PointStruct]], batch_size: int) Iterable[source]
iter_batch(iterable: Union[Iterable, Generator], size: int) Iterable[source]
>>> list(iter_batch([1,2,3,4,5], 3))
[[1, 2, 3], [4, 5]]

Qdrant

Learn more about Qdrant vector search project and ecosystem

Discover Qdrant

Similarity Learning

Explore practical problem solving with Similarity Learning

Learn Similarity Learning

Community

Find people dealing with similar problems and get answers to your questions

Join Community