old_contents: from .connectionpools import ConnectionPool
  from .cloudvolume import CloudVolume
  from .lib import Bbox, Vec
  from .provenance import DataLayerProvenance
  from .skeletonservice import PrecomputedSkeleton, SkeletonEncodeError, SkeletonDecodeError
  from .storage import Storage
  from .threaded_queue import ThreadedQueue
  from .exceptions import EmptyVolumeException, EmptyRequestException, AlignmentError
  from .volumecutout import VolumeCutout
  
  from . import exceptions
  from . import secrets
  from . import txrx
  
  from . import viewer
  from .viewer import view, hyperview
  
  __version__ = '0.49.3'
  
new_contents: """
  A "serverless" Python client for reading and writing arbitrarily large 
  Neuroglancer Precomputed volumes both locally and on cloud services. 
  Precomputed volumes consist of chunked numpy arrays, meshes, and 
  skeletons and can be visualized using Neuroglancer. Typically these 
  volumes represent one or three channel 3D image stacks of microscopy 
  data or labels annotating them, but they can also represent large 
  tensors with compatible dimensions. 
  
    https://github.com/seung-lab/cloud-volume
  
  Precomputed volumes can be stored on any service that provides a 
  key-value mapping between a file path and file data. Typically, 
  Precomputed volumes are located on cloud storage providers such 
  as Amazon S3 or Google Cloud Storage. However, these volumes can 
  be stored on any service, including the local file system or an 
  ordinary webserver that can process these key value mappings.
  
  Neuroglancer is a browser based WebGL 3D image viewer principally 
  authored by Jeremy Maitin-Shepard at Google. CloudVolume is a 
  third-party client for reading and writing Neuroglancer compatible 
  formats: 
  
    https://github.com/google/neuroglancer
  
  CloudVolume is often paired with Igneous, an image processing engine 
  for visualizing and managing Precomputed volumes. Igneous can be
  run locally or in the cloud using Kubernetes.
  
    https://github.com/seung-lab/igneous
  
  The combination of Neuroglancer, Igneous, and CloudVolume comprises 
  a system for visualizing, processing, and sharing (via browser viewable 
  URLs) petascale datasets within and between laboratories.
  
  CloudVolume Example: 
  
    from cloudvolume import CloudVolume
  
    vol = CloudVolume('gs://mylab/mouse/image', progress=True)
    image = vol[:,:,:] # Download an image stack as a numpy array
    vol[:,:,:] = image # Upload an image stack from a numpy array
  
    label = 1
    mesh = vol.mesh.get(label) 
    skel = vol.skeletons.get(label)
  """
  
  from .connectionpools import ConnectionPool
  from .cloudvolume import CloudVolume
  from .lib import Bbox, Vec
  from .provenance import DataLayerProvenance
  from .skeletonservice import PrecomputedSkeleton, SkeletonEncodeError, SkeletonDecodeError
  from .storage import Storage
  from .threaded_queue import ThreadedQueue
  from .exceptions import EmptyVolumeException, EmptyRequestException, AlignmentError
  from .volumecutout import VolumeCutout
  
  from . import exceptions
  from . import secrets
  from . import txrx
  
  from . import viewer
  from .viewer import view, hyperview
  
  __version__ = '0.49.3'
  
subject: add description of CloudVolume to __init__.py