Support pickle output of numpy arrays for endpoints. #812
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The region, thumbnail, and tile_frames endpoints can returned pickled
numpy arrays.
This facilitates getting numpy data from a tile source through Girder
Client. For instance, `numpyarray =
pickle.loads(gc.get('item/5c3e0590e45e326a5e2fb252/tiles/region',
parameters={'encoding': 'pickle:' + str(pickle.HIGHEST_PROTOCOL),
'width': 2000}, jsonResp=False).content)` would fetch a numpy array as
efficiently as possible. The protocol will be the lower of that
specified in the request and the maximum for the python version of the
server. Just using 'pickle' will use protocol 4, which will work with
any supported version of Python 3 -- specifying an explicit number is
more efficient and should adapt to clients using a Python version not
otherwise supported.
|
@banesullivan An equivalent endpoint or endpoint option would be useful for the django implementation -- it makes it much more convenient to process data in a Jupyter notebook when the data isn't local. |
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The region, thumbnail, and tile_frames endpoints can returned pickled numpy arrays.
This facilitates getting numpy data from a tile source through Girder Client. For instance,
numpyarray = pickle.loads(gc.get('item/5c3e0590e45e326a5e2fb252/tiles/region', parameters={'encoding': 'pickle:' + str(pickle.HIGHEST_PROTOCOL), 'width': 2000}, jsonResp=False).content)would fetch a numpy array as efficiently as possible. The protocol will be the lower of that specified in the request and the maximum for the python version of the server. Just using 'pickle' will use protocol 4, which will work with any supported version of Python 3 -- specifying an explicit number is more efficient and adapts to clients using a Python version not otherwise supported.