We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN 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. 

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `napari/utils/io.py`
Content:
```
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 FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

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

{"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"}], "after_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\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(path):\n    \"\"\"Read a zarr dataset, including an array or a group of arrays.\n\n    Parameters\n    --------\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    image : array-like\n        Array or list of arrays\n    shape : tuple\n        Shape of array or first array in list\n    \"\"\"\n    if os.path.exists(os.path.join(path, '.zarray')):\n        # load zarr array\n        image = da.from_zarr(path)\n        shape = image.shape\n    elif os.path.exists(os.path.join(path, '.zgroup')):\n        # else load zarr all arrays inside file, useful for pyramid data\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", "path": "napari/utils/io.py"}]}