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from docarray.array.document import DocumentArray

from docarray.array.storage.memory import StorageMixins

class DocumentArrayInMemory(StorageMixins, DocumentArray):

"""

Default DocumentArray that stores Documents in memory.

With this implementation, :meth:`match` and :meth:`find` perform exact (exhaustive) vector search.

Example usage:

.. code-block:: python

from docarray import Document, DocumentArray

da = DocumentArray(

[Document(text='The cake is a lie'), Document(text='Do a barrel roll!')]

)

da.apply(Document.embed_feature_hashing)

query = Document(text='Can i have some cake?').embed_feature_hashing()

query.match(da, metric='jaccard', use_scipy=True)

print(query.matches[:, ('text', 'scores__jaccard__value')])

.. code-block:: bash

[['The cake is a lie', 'Do a barrel roll!'], [0.9, 1.0]]

.. seealso::

For further details, see our :ref:`user guide <documentarray>`.

"""

def __new__(cls, *args, **kwargs):

return super().__new__(cls)