old_contents: import os
  from glob import glob
  
  try:
      from skimage.io import imread as sk_imread
  except (AttributeError, ImportError):
      pass
  
  from dask.array.core import Array
  from dask.base import tokenize
  
  
  def add_leading_dimension(x):
      return x[None, ...]
  
  
  def imread(filename, imread=None, preprocess=None):
      """Read a stack of images into a dask array
  
      Parameters
      ----------
  
      filename: string
          A globstring like 'myfile.*.png'
      imread: function (optional)
          Optionally provide custom imread function.
          Function should expect a filename and produce a numpy array.
          Defaults to ``skimage.io.imread``.
      preprocess: function (optional)
          Optionally provide custom function to preprocess the image.
          Function should expect a numpy array for a single image.
  
      Examples
      --------
  
      >>> from dask.array.image import imread
      >>> im = imread('2015-*-*.png')  # doctest: +SKIP
      >>> im.shape  # doctest: +SKIP
      (365, 1000, 1000, 3)
  
      Returns
      -------
  
      Dask array of all images stacked along the first dimension.  All images
      will be treated as individual chunks
      """
      imread = imread or sk_imread
      filenames = sorted(glob(filename))
      if not filenames:
          raise ValueError("No files found under name %s" % filename)
  
      name = "imread-%s" % tokenize(filenames, map(os.path.getmtime, filenames))
  
      sample = imread(filenames[0])
      if preprocess:
          sample = preprocess(sample)
  
      keys = [(name, i) + (0,) * len(sample.shape) for i in range(len(filenames))]
      if preprocess:
          values = [
              (add_leading_dimension, (preprocess, (imread, fn))) for fn in filenames
          ]
      else:
          values = [(add_leading_dimension, (imread, fn)) for fn in filenames]
      dsk = dict(zip(keys, values))
  
      chunks = ((1,) * len(filenames),) + tuple((d,) for d in sample.shape)
  
      return Array(dsk, name, chunks, sample.dtype)
  
new_contents: import os
  from glob import glob
  
  try:
      from skimage.io import imread as sk_imread
  except (AttributeError, ImportError):
      pass
  
  from dask.array.core import Array
  from dask.base import tokenize
  
  
  def add_leading_dimension(x):
      return x[None, ...]
  
  
  def imread(filename, imread=None, preprocess=None):
      """Read a stack of images into a dask array
  
      Parameters
      ----------
  
      filename: string
          A globstring like 'myfile.*.png'
      imread: function (optional)
          Optionally provide custom imread function.
          Function should expect a filename and produce a numpy array.
          Defaults to ``skimage.io.imread``.
      preprocess: function (optional)
          Optionally provide custom function to preprocess the image.
          Function should expect a numpy array for a single image.
  
      Examples
      --------
  
      >>> from dask.array.image import imread
      >>> im = imread('2015-*-*.png')  # doctest: +SKIP
      >>> im.shape  # doctest: +SKIP
      (365, 1000, 1000, 3)
  
      Returns
      -------
  
      Dask array of all images stacked along the first dimension.
      Each separate image file will be treated as an individual chunk.
      """
      imread = imread or sk_imread
      filenames = sorted(glob(filename))
      if not filenames:
          raise ValueError("No files found under name %s" % filename)
  
      name = "imread-%s" % tokenize(filenames, map(os.path.getmtime, filenames))
  
      sample = imread(filenames[0])
      if preprocess:
          sample = preprocess(sample)
  
      keys = [(name, i) + (0,) * len(sample.shape) for i in range(len(filenames))]
      if preprocess:
          values = [
              (add_leading_dimension, (preprocess, (imread, fn))) for fn in filenames
          ]
      else:
          values = [(add_leading_dimension, (imread, fn)) for fn in filenames]
      dsk = dict(zip(keys, values))
  
      chunks = ((1,) * len(filenames),) + tuple((d,) for d in sample.shape)
  
      return Array(dsk, name, chunks, sample.dtype)
  
subject: Clarify chunking in `imread` docstring (#9082)