We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
cytoolz is required to import blaze, but it's not listed in requirements_strict.txt
In a fresh virtualenv, `pip install blaze && python -c "import blaze"` fails with:

```
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/ssanderson/.virtualenvs/blaze/local/lib/python2.7/site-packages/blaze/__init__.py", line 18, in <module>
    from .utils import ignoring
  File "/home/ssanderson/.virtualenvs/blaze/local/lib/python2.7/site-packages/blaze/utils.py", line 7, in <module>
    from cytoolz import nth
ImportError: No module named cytoolz
```

Is there a reason cytoolz isn't in the strict requirements if it's necessary to even import the top-level module?


--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `blaze/utils.py`
Content:
```
1 from __future__ import absolute_import, division, print_function
2 
3 import os
4 import datetime
5 from functools import wraps
6 
7 from cytoolz import nth
8 from itertools import islice
9 from collections import Iterator
10 from multiprocessing.pool import ThreadPool
11 
12 # these are used throughout blaze, don't remove them
13 from odo.utils import tmpfile, filetext, filetexts, raises, keywords, ignoring
14 
15 import psutil
16 import numpy as np
17 
18 # Imports that replace older utils.
19 from .compatibility import map, zip
20 
21 from .dispatch import dispatch
22 
23 thread_pool = ThreadPool(psutil.NUM_CPUS)
24 
25 
26 def nth_list(n, seq):
27     """
28 
29     >>> tuple(nth_list([0, 1, 4], 'Hello'))
30     ('H', 'e', 'o')
31     >>> tuple(nth_list([4, 1, 0], 'Hello'))
32     ('o', 'e', 'H')
33     >>> tuple(nth_list([0, 0, 0], 'Hello'))
34     ('H', 'H', 'H')
35     """
36     seq = iter(seq)
37 
38     result = []
39     old = 0
40     item = next(seq)
41     for index in sorted(n):
42         for i in range(index - old):
43             item = next(seq)
44         result.append(item)
45         old = index
46 
47     order = [x[1] for x in sorted(zip(n, range(len(n))))]
48     return (result[i] for i in order)
49 
50 
51 def get(ind, coll, lazy=False):
52     """
53 
54     >>> get(0, 'Hello')
55     'H'
56 
57     >>> get([1, 0], 'Hello')
58     ('e', 'H')
59 
60     >>> get(slice(1, 4), 'Hello')
61     ('e', 'l', 'l')
62 
63     >>> get(slice(1, 4), 'Hello', lazy=True)
64     <itertools.islice object at ...>
65     """
66     if isinstance(ind, list):
67         result = nth_list(ind, coll)
68     elif isinstance(ind, slice):
69         result = islice(coll, ind.start, ind.stop, ind.step)
70     else:
71         if isinstance(coll, Iterator):
72             result = nth(ind, coll)
73         else:
74             result = coll[ind]
75     if not lazy and isinstance(result, Iterator):
76         result = tuple(result)
77     return result
78 
79 
80 def ndget(ind, data):
81     """
82     Get from N-Dimensional getable
83 
84     Can index with elements, lists, or slices.  Mimic's numpy fancy indexing on
85     generic indexibles.
86 
87     >>> data = [[[1, 2], [3, 4]], [[5, 6], [7, 8]]]
88     >>> ndget(0, data)
89     [[1, 2], [3, 4]]
90     >>> ndget((0, 1), data)
91     [3, 4]
92     >>> ndget((0, 0, 0), data)
93     1
94     >>> ndget((slice(0, 2), [0, 1], 0), data)
95     ((1, 3), (5, 7))
96     """
97     if isinstance(ind, tuple) and len(ind) == 1:
98         ind = ind[0]
99     if not isinstance(ind, tuple):
100         return get(ind, data)
101     result = get(ind[0], data)
102     if isinstance(ind[0], (list, slice)):
103         return type(result)(ndget(ind[1:], row) for row in result)
104     else:
105         return ndget(ind[1:], result)
106 
107 
108 def normalize_to_date(dt):
109     if isinstance(dt, datetime.datetime) and not dt.time():
110         return dt.date()
111     else:
112         return dt
113 
114 
115 def assert_allclose(lhs, rhs):
116     for tb in map(zip, lhs, rhs):
117         for left, right in tb:
118             if isinstance(left, (np.floating, float)):
119                 # account for nans
120                 assert np.all(np.isclose(left, right, equal_nan=True))
121                 continue
122             if isinstance(left, datetime.datetime):
123                 left = normalize_to_date(left)
124             if isinstance(right, datetime.datetime):
125                 right = normalize_to_date(right)
126             assert left == right
127 
128 
129 def example(filename, datapath=os.path.join('examples', 'data')):
130     import blaze
131     return os.path.join(os.path.dirname(blaze.__file__), datapath, filename)
132 
133 
134 def available_memory():
135     return psutil.virtual_memory().available
136 
137 
138 def listpack(x):
139     """
140     >>> listpack(1)
141     [1]
142     >>> listpack((1, 2))
143     [1, 2]
144     >>> listpack([1, 2])
145     [1, 2]
146     """
147     if isinstance(x, tuple):
148         return list(x)
149     elif isinstance(x, list):
150         return x
151     else:
152         return [x]
153 
154 
155 @dispatch(datetime.datetime)
156 def json_dumps(dt):
157     s = dt.isoformat()
158     if not dt.tzname():
159         s = s + 'Z'
160     return s
161
```
--- 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/blaze/utils.py b/blaze/utils.py
--- a/blaze/utils.py
+++ b/blaze/utils.py
@@ -4,7 +4,11 @@
 import datetime
 from functools import wraps
 
-from cytoolz import nth
+try:
+    from cytoolz import nth
+except ImportError:
+    from toolz import nth
+
 from itertools import islice
 from collections import Iterator
 from multiprocessing.pool import ThreadPool

{"golden_diff": "diff --git a/blaze/utils.py b/blaze/utils.py\n--- a/blaze/utils.py\n+++ b/blaze/utils.py\n@@ -4,7 +4,11 @@\n import datetime\n from functools import wraps\n \n-from cytoolz import nth\n+try:\n+    from cytoolz import nth\n+except ImportError:\n+    from toolz import nth\n+\n from itertools import islice\n from collections import Iterator\n from multiprocessing.pool import ThreadPool\n", "issue": "cytoolz is required to import blaze, but it's not listed in requirements_strict.txt\nIn a fresh virtualenv, `pip install blaze && python -c \"import blaze\"` fails with:\n\n```\nTraceback (most recent call last):\n  File \"<stdin>\", line 1, in <module>\n  File \"/home/ssanderson/.virtualenvs/blaze/local/lib/python2.7/site-packages/blaze/__init__.py\", line 18, in <module>\n    from .utils import ignoring\n  File \"/home/ssanderson/.virtualenvs/blaze/local/lib/python2.7/site-packages/blaze/utils.py\", line 7, in <module>\n    from cytoolz import nth\nImportError: No module named cytoolz\n```\n\nIs there a reason cytoolz isn't in the strict requirements if it's necessary to even import the top-level module?\n\n", "before_files": [{"content": "from __future__ import absolute_import, division, print_function\n\nimport os\nimport datetime\nfrom functools import wraps\n\nfrom cytoolz import nth\nfrom itertools import islice\nfrom collections import Iterator\nfrom multiprocessing.pool import ThreadPool\n\n# these are used throughout blaze, don't remove them\nfrom odo.utils import tmpfile, filetext, filetexts, raises, keywords, ignoring\n\nimport psutil\nimport numpy as np\n\n# Imports that replace older utils.\nfrom .compatibility import map, zip\n\nfrom .dispatch import dispatch\n\nthread_pool = ThreadPool(psutil.NUM_CPUS)\n\n\ndef nth_list(n, seq):\n    \"\"\"\n\n    >>> tuple(nth_list([0, 1, 4], 'Hello'))\n    ('H', 'e', 'o')\n    >>> tuple(nth_list([4, 1, 0], 'Hello'))\n    ('o', 'e', 'H')\n    >>> tuple(nth_list([0, 0, 0], 'Hello'))\n    ('H', 'H', 'H')\n    \"\"\"\n    seq = iter(seq)\n\n    result = []\n    old = 0\n    item = next(seq)\n    for index in sorted(n):\n        for i in range(index - old):\n            item = next(seq)\n        result.append(item)\n        old = index\n\n    order = [x[1] for x in sorted(zip(n, range(len(n))))]\n    return (result[i] for i in order)\n\n\ndef get(ind, coll, lazy=False):\n    \"\"\"\n\n    >>> get(0, 'Hello')\n    'H'\n\n    >>> get([1, 0], 'Hello')\n    ('e', 'H')\n\n    >>> get(slice(1, 4), 'Hello')\n    ('e', 'l', 'l')\n\n    >>> get(slice(1, 4), 'Hello', lazy=True)\n    <itertools.islice object at ...>\n    \"\"\"\n    if isinstance(ind, list):\n        result = nth_list(ind, coll)\n    elif isinstance(ind, slice):\n        result = islice(coll, ind.start, ind.stop, ind.step)\n    else:\n        if isinstance(coll, Iterator):\n            result = nth(ind, coll)\n        else:\n            result = coll[ind]\n    if not lazy and isinstance(result, Iterator):\n        result = tuple(result)\n    return result\n\n\ndef ndget(ind, data):\n    \"\"\"\n    Get from N-Dimensional getable\n\n    Can index with elements, lists, or slices.  Mimic's numpy fancy indexing on\n    generic indexibles.\n\n    >>> data = [[[1, 2], [3, 4]], [[5, 6], [7, 8]]]\n    >>> ndget(0, data)\n    [[1, 2], [3, 4]]\n    >>> ndget((0, 1), data)\n    [3, 4]\n    >>> ndget((0, 0, 0), data)\n    1\n    >>> ndget((slice(0, 2), [0, 1], 0), data)\n    ((1, 3), (5, 7))\n    \"\"\"\n    if isinstance(ind, tuple) and len(ind) == 1:\n        ind = ind[0]\n    if not isinstance(ind, tuple):\n        return get(ind, data)\n    result = get(ind[0], data)\n    if isinstance(ind[0], (list, slice)):\n        return type(result)(ndget(ind[1:], row) for row in result)\n    else:\n        return ndget(ind[1:], result)\n\n\ndef normalize_to_date(dt):\n    if isinstance(dt, datetime.datetime) and not dt.time():\n        return dt.date()\n    else:\n        return dt\n\n\ndef assert_allclose(lhs, rhs):\n    for tb in map(zip, lhs, rhs):\n        for left, right in tb:\n            if isinstance(left, (np.floating, float)):\n                # account for nans\n                assert np.all(np.isclose(left, right, equal_nan=True))\n                continue\n            if isinstance(left, datetime.datetime):\n                left = normalize_to_date(left)\n            if isinstance(right, datetime.datetime):\n                right = normalize_to_date(right)\n            assert left == right\n\n\ndef example(filename, datapath=os.path.join('examples', 'data')):\n    import blaze\n    return os.path.join(os.path.dirname(blaze.__file__), datapath, filename)\n\n\ndef available_memory():\n    return psutil.virtual_memory().available\n\n\ndef listpack(x):\n    \"\"\"\n    >>> listpack(1)\n    [1]\n    >>> listpack((1, 2))\n    [1, 2]\n    >>> listpack([1, 2])\n    [1, 2]\n    \"\"\"\n    if isinstance(x, tuple):\n        return list(x)\n    elif isinstance(x, list):\n        return x\n    else:\n        return [x]\n\n\n@dispatch(datetime.datetime)\ndef json_dumps(dt):\n    s = dt.isoformat()\n    if not dt.tzname():\n        s = s + 'Z'\n    return s\n", "path": "blaze/utils.py"}], "after_files": [{"content": "from __future__ import absolute_import, division, print_function\n\nimport os\nimport datetime\nfrom functools import wraps\n\ntry:\n    from cytoolz import nth\nexcept ImportError:\n    from toolz import nth\n\nfrom itertools import islice\nfrom collections import Iterator\nfrom multiprocessing.pool import ThreadPool\n\n# these are used throughout blaze, don't remove them\nfrom odo.utils import tmpfile, filetext, filetexts, raises, keywords, ignoring\n\nimport psutil\nimport numpy as np\n\n# Imports that replace older utils.\nfrom .compatibility import map, zip\n\nfrom .dispatch import dispatch\n\nthread_pool = ThreadPool(psutil.NUM_CPUS)\n\n\ndef nth_list(n, seq):\n    \"\"\"\n\n    >>> tuple(nth_list([0, 1, 4], 'Hello'))\n    ('H', 'e', 'o')\n    >>> tuple(nth_list([4, 1, 0], 'Hello'))\n    ('o', 'e', 'H')\n    >>> tuple(nth_list([0, 0, 0], 'Hello'))\n    ('H', 'H', 'H')\n    \"\"\"\n    seq = iter(seq)\n\n    result = []\n    old = 0\n    item = next(seq)\n    for index in sorted(n):\n        for i in range(index - old):\n            item = next(seq)\n        result.append(item)\n        old = index\n\n    order = [x[1] for x in sorted(zip(n, range(len(n))))]\n    return (result[i] for i in order)\n\n\ndef get(ind, coll, lazy=False):\n    \"\"\"\n\n    >>> get(0, 'Hello')\n    'H'\n\n    >>> get([1, 0], 'Hello')\n    ('e', 'H')\n\n    >>> get(slice(1, 4), 'Hello')\n    ('e', 'l', 'l')\n\n    >>> get(slice(1, 4), 'Hello', lazy=True)\n    <itertools.islice object at ...>\n    \"\"\"\n    if isinstance(ind, list):\n        result = nth_list(ind, coll)\n    elif isinstance(ind, slice):\n        result = islice(coll, ind.start, ind.stop, ind.step)\n    else:\n        if isinstance(coll, Iterator):\n            result = nth(ind, coll)\n        else:\n            result = coll[ind]\n    if not lazy and isinstance(result, Iterator):\n        result = tuple(result)\n    return result\n\n\ndef ndget(ind, data):\n    \"\"\"\n    Get from N-Dimensional getable\n\n    Can index with elements, lists, or slices.  Mimic's numpy fancy indexing on\n    generic indexibles.\n\n    >>> data = [[[1, 2], [3, 4]], [[5, 6], [7, 8]]]\n    >>> ndget(0, data)\n    [[1, 2], [3, 4]]\n    >>> ndget((0, 1), data)\n    [3, 4]\n    >>> ndget((0, 0, 0), data)\n    1\n    >>> ndget((slice(0, 2), [0, 1], 0), data)\n    ((1, 3), (5, 7))\n    \"\"\"\n    if isinstance(ind, tuple) and len(ind) == 1:\n        ind = ind[0]\n    if not isinstance(ind, tuple):\n        return get(ind, data)\n    result = get(ind[0], data)\n    if isinstance(ind[0], (list, slice)):\n        return type(result)(ndget(ind[1:], row) for row in result)\n    else:\n        return ndget(ind[1:], result)\n\n\ndef normalize_to_date(dt):\n    if isinstance(dt, datetime.datetime) and not dt.time():\n        return dt.date()\n    else:\n        return dt\n\n\ndef assert_allclose(lhs, rhs):\n    for tb in map(zip, lhs, rhs):\n        for left, right in tb:\n            if isinstance(left, (np.floating, float)):\n                # account for nans\n                assert np.all(np.isclose(left, right, equal_nan=True))\n                continue\n            if isinstance(left, datetime.datetime):\n                left = normalize_to_date(left)\n            if isinstance(right, datetime.datetime):\n                right = normalize_to_date(right)\n            assert left == right\n\n\ndef example(filename, datapath=os.path.join('examples', 'data')):\n    import blaze\n    return os.path.join(os.path.dirname(blaze.__file__), datapath, filename)\n\n\ndef available_memory():\n    return psutil.virtual_memory().available\n\n\ndef listpack(x):\n    \"\"\"\n    >>> listpack(1)\n    [1]\n    >>> listpack((1, 2))\n    [1, 2]\n    >>> listpack([1, 2])\n    [1, 2]\n    \"\"\"\n    if isinstance(x, tuple):\n        return list(x)\n    elif isinstance(x, list):\n        return x\n    else:\n        return [x]\n\n\n@dispatch(datetime.datetime)\ndef json_dumps(dt):\n    s = dt.isoformat()\n    if not dt.tzname():\n        s = s + 'Z'\n    return s\n", "path": "blaze/utils.py"}]}