prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  new zarr release / numcodecs
  ## 🐛 Bug
  
  Looks like zarr's new release requires numcodecs > 0.6.4, but we pinned to exclude it see discussion #666. I think we need to resolve this ASAP and then make the 0.2.10 release (which also includes the #866 bug fix). Thoughts @tlambert03 @jni? Has the 0.6.4 numcodecs install problem been resolved? You can see our failing tests in #867. 
  
  </issue>
  <code>
  [start of napari/utils/io.py]
  1 import os
  2 
  3 from glob import glob
  4 from pathlib import Path
  5 
  6 import numpy as np
  7 from skimage import io
  8 from skimage.io.collection import alphanumeric_key
  9 
  10 from dask import delayed
  11 from dask import array as da
  12 import zarr
  13 
  14 
  15 def magic_imread(filenames, *, use_dask=None, stack=True):
  16     """Dispatch the appropriate reader given some files.
  17 
  18     The files are assumed to all have the same shape.
  19 
  20     Parameters
  21     -------
  22     filenames : list
  23         List of filenames or directories to be opened.
  24         A list of `pathlib.Path` objects and a single filename or `Path` object
  25         are also accepted.
  26     use_dask : bool
  27         Whether to use dask to create a lazy array, rather than NumPy.
  28         Default of None will resolve to True if filenames contains more than
  29         one image, False otherwise.
  30     stack : bool
  31         Whether to stack the images in multiple files into a single array. If
  32         False, a list of arrays will be returned.
  33 
  34     Returns
  35     -------
  36     image : array-like
  37         Array or list of images
  38     """
  39     # cast Path to string
  40     if isinstance(filenames, Path):
  41         filenames = filenames.as_posix()
  42 
  43     if len(filenames) == 0:
  44         return None
  45     if isinstance(filenames, str):
  46         filenames = [filenames]  # ensure list
  47 
  48     # replace folders with their contents
  49     filenames_expanded = []
  50     for filename in filenames:
  51         ext = os.path.splitext(filename)[-1]
  52         # zarr files are folders, but should be read as 1 file
  53         if os.path.isdir(filename) and not ext == '.zarr':
  54             dir_contents = sorted(
  55                 glob(os.path.join(filename, '*.*')), key=alphanumeric_key
  56             )
  57             # remove subdirectories
  58             dir_contents_files = filter(
  59                 lambda f: not os.path.isdir(f), dir_contents
  60             )
  61             filenames_expanded.extend(dir_contents_files)
  62         else:
  63             filenames_expanded.append(filename)
  64 
  65     if use_dask is None:
  66         use_dask = len(filenames_expanded) > 1
  67 
  68     # then, read in images
  69     images = []
  70     shape = None
  71     for filename in filenames_expanded:
  72         ext = os.path.splitext(filename)[-1]
  73         if ext == '.zarr':
  74             image, zarr_shape = read_zarr_dataset(filename)
  75             if shape is None:
  76                 shape = zarr_shape
  77         else:
  78             if shape is None:
  79                 image = io.imread(filename)
  80                 shape = image.shape
  81                 dtype = image.dtype
  82             if use_dask:
  83                 image = da.from_delayed(
  84                     delayed(io.imread)(filename), shape=shape, dtype=dtype
  85                 )
  86             elif len(images) > 0:  # not read by shape clause
  87                 image = io.imread(filename)
  88         images.append(image)
  89     if len(images) == 1:
  90         image = images[0]
  91     else:
  92         if stack:
  93             if use_dask:
  94                 image = da.stack(images)
  95             else:
  96                 image = np.stack(images)
  97         else:
  98             image = images  # return a list
  99     return image
  100 
  101 
  102 def read_zarr_dataset(filename):
  103     """Read a zarr dataset, including an array or a group of arrays.
  104 
  105     Parameters
  106     --------
  107     filename : str
  108         Path to file ending in '.zarr'. File can contain either an array
  109         or a group of arrays in the case of pyramid data.
  110     Returns
  111     -------
  112     image : array-like
  113         Array or list of arrays
  114     shape : tuple
  115         Shape of array or first array in list
  116     """
  117     zr = zarr.open(filename, mode='r')
  118     if isinstance(zr, zarr.core.Array):
  119         # load zarr array
  120         image = da.from_zarr(filename)
  121         shape = image.shape
  122     else:
  123         # else load zarr all arrays inside file, useful for pyramid data
  124         image = [da.from_zarr(filename, component=c) for c, a in zr.arrays()]
  125         shape = image[0].shape
  126     return image, shape
  127
  [end of napari/utils/io.py]
  </code>
  
  I need you to solve this issue by generating a single patch file that I can apply directly to this repository using git apply. Please respond with a single patch file in the following format.
  <patch>
  diff --git a/file.py b/file.py
  --- a/file.py
  +++ b/file.py
  @@ -1,27 +1,35 @@
   def euclidean(a, b):
  -    while b:
  -        a, b = b, a % b
  -    return a
  +    if b == 0:
  +        return a
  +    return euclidean(b, a % b)
   
   
   def bresenham(x0, y0, x1, y1):
       points = []
       dx = abs(x1 - x0)
       dy = abs(y1 - y0)
  -    sx = 1 if x0 < x1 else -1
  -    sy = 1 if y0 < y1 else -1
  -    err = dx - dy
  +    x, y = x0, y0
  +    sx = -1 if x0 > x1 else 1
  +    sy = -1 if y0 > y1 else 1
   
  -    while True:
  -        points.append((x0, y0))
  -        if x0 == x1 and y0 == y1:
  -            break
  -        e2 = 2 * err
  -        if e2 > -dy:
  -            err -= dy
  -            x0 += sx
  -        if e2 < dx:
  -            err += dx
  -            y0 += sy
  +    if dx > dy:
  +        err = dx / 2.0
  +        while x != x1:
  +            points.append((x, y))
  +            err -= dy
  +            if err < 0:
  +                y += sy
  +                err += dx
  +            x += sx
  +    else:
  +        err = dy / 2.0
  +        while y != y1:
  +            points.append((x, y))
  +            err -= dx
  +            if err < 0:
  +                x += sx
  +                err += dy
  +            y += sy
  +
  +    points.append((x, y))
       return points
  
  </patch>
golden_diff: diff --git a/napari/utils/io.py b/napari/utils/io.py
  --- a/napari/utils/io.py
  +++ b/napari/utils/io.py
  @@ -9,7 +9,6 @@
   
   from dask import delayed
   from dask import array as da
  -import zarr
   
   
   def magic_imread(filenames, *, use_dask=None, stack=True):
  @@ -99,13 +98,13 @@
       return image
   
   
  -def read_zarr_dataset(filename):
  +def read_zarr_dataset(path):
       """Read a zarr dataset, including an array or a group of arrays.
   
       Parameters
       --------
  -    filename : str
  -        Path to file ending in '.zarr'. File can contain either an array
  +    path : str
  +        Path to directory ending in '.zarr'. Path can contain either an array
           or a group of arrays in the case of pyramid data.
       Returns
       -------
  @@ -114,13 +113,17 @@
       shape : tuple
           Shape of array or first array in list
       """
  -    zr = zarr.open(filename, mode='r')
  -    if isinstance(zr, zarr.core.Array):
  +    if os.path.exists(os.path.join(path, '.zarray')):
           # load zarr array
  -        image = da.from_zarr(filename)
  +        image = da.from_zarr(path)
           shape = image.shape
  -    else:
  +    elif os.path.exists(os.path.join(path, '.zgroup')):
           # else load zarr all arrays inside file, useful for pyramid data
  -        image = [da.from_zarr(filename, component=c) for c, a in zr.arrays()]
  +        image = []
  +        for subpath in sorted(os.listdir(path)):
  +            if not subpath.startswith('.'):
  +                image.append(read_zarr_dataset(os.path.join(path, subpath))[0])
           shape = image[0].shape
  +    else:
  +        raise ValueError(f"Not a zarr dataset or group: {path}")
       return image, shape
  
verification_info: {"golden_diff": "diff --git a/napari/utils/io.py b/napari/utils/io.py\n--- a/napari/utils/io.py\n+++ b/napari/utils/io.py\n@@ -9,7 +9,6 @@\n \n from dask import delayed\n from dask import array as da\n-import zarr\n \n \n def magic_imread(filenames, *, use_dask=None, stack=True):\n@@ -99,13 +98,13 @@\n     return image\n \n \n-def read_zarr_dataset(filename):\n+def read_zarr_dataset(path):\n     \"\"\"Read a zarr dataset, including an array or a group of arrays.\n \n     Parameters\n     --------\n-    filename : str\n-        Path to file ending in '.zarr'. File can contain either an array\n+    path : str\n+        Path to directory ending in '.zarr'. Path can contain either an array\n         or a group of arrays in the case of pyramid data.\n     Returns\n     -------\n@@ -114,13 +113,17 @@\n     shape : tuple\n         Shape of array or first array in list\n     \"\"\"\n-    zr = zarr.open(filename, mode='r')\n-    if isinstance(zr, zarr.core.Array):\n+    if os.path.exists(os.path.join(path, '.zarray')):\n         # load zarr array\n-        image = da.from_zarr(filename)\n+        image = da.from_zarr(path)\n         shape = image.shape\n-    else:\n+    elif os.path.exists(os.path.join(path, '.zgroup')):\n         # else load zarr all arrays inside file, useful for pyramid data\n-        image = [da.from_zarr(filename, component=c) for c, a in zr.arrays()]\n+        image = []\n+        for subpath in sorted(os.listdir(path)):\n+            if not subpath.startswith('.'):\n+                image.append(read_zarr_dataset(os.path.join(path, subpath))[0])\n         shape = image[0].shape\n+    else:\n+        raise ValueError(f\"Not a zarr dataset or group: {path}\")\n     return image, shape\n", "issue": "new zarr release / numcodecs\n## \ud83d\udc1b Bug\r\n\r\nLooks like zarr's new release requires numcodecs > 0.6.4, but we pinned to exclude it see discussion #666. I think we need to resolve this ASAP and then make the 0.2.10 release (which also includes the #866 bug fix). Thoughts @tlambert03 @jni? Has the 0.6.4 numcodecs install problem been resolved? You can see our failing tests in #867. \n", "before_files": [{"content": "import os\n\nfrom glob import glob\nfrom pathlib import Path\n\nimport numpy as np\nfrom skimage import io\nfrom skimage.io.collection import alphanumeric_key\n\nfrom dask import delayed\nfrom dask import array as da\nimport zarr\n\n\ndef magic_imread(filenames, *, use_dask=None, stack=True):\n    \"\"\"Dispatch the appropriate reader given some files.\n\n    The files are assumed to all have the same shape.\n\n    Parameters\n    -------\n    filenames : list\n        List of filenames or directories to be opened.\n        A list of `pathlib.Path` objects and a single filename or `Path` object\n        are also accepted.\n    use_dask : bool\n        Whether to use dask to create a lazy array, rather than NumPy.\n        Default of None will resolve to True if filenames contains more than\n        one image, False otherwise.\n    stack : bool\n        Whether to stack the images in multiple files into a single array. If\n        False, a list of arrays will be returned.\n\n    Returns\n    -------\n    image : array-like\n        Array or list of images\n    \"\"\"\n    # cast Path to string\n    if isinstance(filenames, Path):\n        filenames = filenames.as_posix()\n\n    if len(filenames) == 0:\n        return None\n    if isinstance(filenames, str):\n        filenames = [filenames]  # ensure list\n\n    # replace folders with their contents\n    filenames_expanded = []\n    for filename in filenames:\n        ext = os.path.splitext(filename)[-1]\n        # zarr files are folders, but should be read as 1 file\n        if os.path.isdir(filename) and not ext == '.zarr':\n            dir_contents = sorted(\n                glob(os.path.join(filename, '*.*')), key=alphanumeric_key\n            )\n            # remove subdirectories\n            dir_contents_files = filter(\n                lambda f: not os.path.isdir(f), dir_contents\n            )\n            filenames_expanded.extend(dir_contents_files)\n        else:\n            filenames_expanded.append(filename)\n\n    if use_dask is None:\n        use_dask = len(filenames_expanded) > 1\n\n    # then, read in images\n    images = []\n    shape = None\n    for filename in filenames_expanded:\n        ext = os.path.splitext(filename)[-1]\n        if ext == '.zarr':\n            image, zarr_shape = read_zarr_dataset(filename)\n            if shape is None:\n                shape = zarr_shape\n        else:\n            if shape is None:\n                image = io.imread(filename)\n                shape = image.shape\n                dtype = image.dtype\n            if use_dask:\n                image = da.from_delayed(\n                    delayed(io.imread)(filename), shape=shape, dtype=dtype\n                )\n            elif len(images) > 0:  # not read by shape clause\n                image = io.imread(filename)\n        images.append(image)\n    if len(images) == 1:\n        image = images[0]\n    else:\n        if stack:\n            if use_dask:\n                image = da.stack(images)\n            else:\n                image = np.stack(images)\n        else:\n            image = images  # return a list\n    return image\n\n\ndef read_zarr_dataset(filename):\n    \"\"\"Read a zarr dataset, including an array or a group of arrays.\n\n    Parameters\n    --------\n    filename : str\n        Path to file ending in '.zarr'. File can contain either an array\n        or a group of arrays in the case of pyramid data.\n    Returns\n    -------\n    image : array-like\n        Array or list of arrays\n    shape : tuple\n        Shape of array or first array in list\n    \"\"\"\n    zr = zarr.open(filename, mode='r')\n    if isinstance(zr, zarr.core.Array):\n        # load zarr array\n        image = da.from_zarr(filename)\n        shape = image.shape\n    else:\n        # else load zarr all arrays inside file, useful for pyramid data\n        image = [da.from_zarr(filename, component=c) for c, a in zr.arrays()]\n        shape = image[0].shape\n    return image, shape\n", "path": "napari/utils/io.py"}]}