We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Note on `Add x.str.cat (#3028)` (lines 125-126)
It's not clear to me why `String.str.cat` isn't supported in Dask when `others == None`. Not having the ability to concat a single series into a string is a significant cost, I think. Unless there's a reason for this condition, I recommend deleting lines 126-126.


--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `dask/dataframe/accessor.py`
Content:
```
1 from functools import partial
2 
3 import numpy as np
4 import pandas as pd
5 
6 from ..utils import derived_from
7 
8 
9 def maybe_wrap_pandas(obj, x):
10     if isinstance(x, np.ndarray):
11         if isinstance(obj, pd.Series):
12             return pd.Series(x, index=obj.index, dtype=x.dtype)
13         return pd.Index(x)
14     return x
15 
16 
17 class Accessor:
18     """
19     Base class for pandas Accessor objects cat, dt, and str.
20 
21     Notes
22     -----
23     Subclasses should define ``_accessor_name``
24     """
25 
26     _not_implemented = set()
27 
28     def __init__(self, series):
29         from .core import Series
30 
31         if not isinstance(series, Series):
32             raise ValueError("Accessor cannot be initialized")
33 
34         series_meta = series._meta
35         if hasattr(series_meta, "to_series"):  # is index-like
36             series_meta = series_meta.to_series()
37         meta = getattr(series_meta, self._accessor_name)
38 
39         self._meta = meta
40         self._series = series
41 
42     @staticmethod
43     def _delegate_property(obj, accessor, attr):
44         out = getattr(getattr(obj, accessor, obj), attr)
45         return maybe_wrap_pandas(obj, out)
46 
47     @staticmethod
48     def _delegate_method(obj, accessor, attr, args, kwargs):
49         out = getattr(getattr(obj, accessor, obj), attr)(*args, **kwargs)
50         return maybe_wrap_pandas(obj, out)
51 
52     def _property_map(self, attr):
53         meta = self._delegate_property(self._series._meta, self._accessor_name, attr)
54         token = "%s-%s" % (self._accessor_name, attr)
55         return self._series.map_partitions(
56             self._delegate_property, self._accessor_name, attr, token=token, meta=meta
57         )
58 
59     def _function_map(self, attr, *args, **kwargs):
60         if "meta" in kwargs:
61             meta = kwargs.pop("meta")
62         else:
63             meta = self._delegate_method(
64                 self._series._meta_nonempty, self._accessor_name, attr, args, kwargs
65             )
66         token = "%s-%s" % (self._accessor_name, attr)
67         return self._series.map_partitions(
68             self._delegate_method,
69             self._accessor_name,
70             attr,
71             args,
72             kwargs,
73             meta=meta,
74             token=token,
75         )
76 
77     @property
78     def _delegates(self):
79         return set(dir(self._meta)) - self._not_implemented
80 
81     def __dir__(self):
82         o = self._delegates
83         o.update(self.__dict__)
84         o.update(dir(type(self)))
85         return list(o)
86 
87     def __getattr__(self, key):
88         if key in self._delegates:
89             if callable(getattr(self._meta, key)):
90                 return partial(self._function_map, key)
91             else:
92                 return self._property_map(key)
93         else:
94             raise AttributeError(key)
95 
96 
97 class DatetimeAccessor(Accessor):
98     """Accessor object for datetimelike properties of the Series values.
99 
100     Examples
101     --------
102 
103     >>> s.dt.microsecond  # doctest: +SKIP
104     """
105 
106     _accessor_name = "dt"
107 
108 
109 class StringAccessor(Accessor):
110     """Accessor object for string properties of the Series values.
111 
112     Examples
113     --------
114 
115     >>> s.str.lower()  # doctest: +SKIP
116     """
117 
118     _accessor_name = "str"
119     _not_implemented = {"get_dummies"}
120 
121     @derived_from(pd.core.strings.StringMethods)
122     def split(self, pat=None, n=-1, expand=False):
123         if expand:
124             if n == -1:
125                 raise NotImplementedError(
126                     "To use the expand parameter you must specify the number of "
127                     "expected splits with the n= parameter. Usually n splits result in n+1 output columns."
128                 )
129             else:
130                 delimiter = " " if pat is None else pat
131                 meta = self._series._meta._constructor(
132                     [delimiter.join(["a"] * (n + 1))],
133                     index=self._series._meta_nonempty[:1].index,
134                 )
135                 meta = meta.str.split(n=n, expand=expand, pat=pat)
136         else:
137             meta = (self._series.name, object)
138         return self._function_map("split", pat=pat, n=n, expand=expand, meta=meta)
139 
140     @derived_from(pd.core.strings.StringMethods)
141     def cat(self, others=None, sep=None, na_rep=None):
142         from .core import Index, Series
143 
144         if others is None:
145             raise NotImplementedError("x.str.cat() with `others == None`")
146 
147         valid_types = (Series, Index, pd.Series, pd.Index)
148         if isinstance(others, valid_types):
149             others = [others]
150         elif not all(isinstance(a, valid_types) for a in others):
151             raise TypeError("others must be Series/Index")
152 
153         return self._series.map_partitions(
154             str_cat, *others, sep=sep, na_rep=na_rep, meta=self._series._meta
155         )
156 
157     @derived_from(pd.core.strings.StringMethods)
158     def extractall(self, pat, flags=0):
159         return self._series.map_partitions(
160             str_extractall, pat, flags, token="str-extractall"
161         )
162 
163     def __getitem__(self, index):
164         return self._series.map_partitions(str_get, index, meta=self._series._meta)
165 
166 
167 def str_extractall(series, pat, flags):
168     return series.str.extractall(pat, flags=flags)
169 
170 
171 def str_get(series, index):
172     """ Implements series.str[index] """
173     return series.str[index]
174 
175 
176 def str_cat(self, *others, **kwargs):
177     return self.str.cat(others=others, **kwargs)
178
```
--- 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/dask/dataframe/accessor.py b/dask/dataframe/accessor.py
--- a/dask/dataframe/accessor.py
+++ b/dask/dataframe/accessor.py
@@ -142,7 +142,15 @@
         from .core import Index, Series
 
         if others is None:
-            raise NotImplementedError("x.str.cat() with `others == None`")
+
+            def str_cat_none(x):
+
+                if isinstance(x, (Series, Index)):
+                    x = x.compute()
+
+                return x.str.cat(sep=sep, na_rep=na_rep)
+
+            return self._series.reduction(chunk=str_cat_none, aggregate=str_cat_none)
 
         valid_types = (Series, Index, pd.Series, pd.Index)
         if isinstance(others, valid_types):

{"golden_diff": "diff --git a/dask/dataframe/accessor.py b/dask/dataframe/accessor.py\n--- a/dask/dataframe/accessor.py\n+++ b/dask/dataframe/accessor.py\n@@ -142,7 +142,15 @@\n         from .core import Index, Series\n \n         if others is None:\n-            raise NotImplementedError(\"x.str.cat() with `others == None`\")\n+\n+            def str_cat_none(x):\n+\n+                if isinstance(x, (Series, Index)):\n+                    x = x.compute()\n+\n+                return x.str.cat(sep=sep, na_rep=na_rep)\n+\n+            return self._series.reduction(chunk=str_cat_none, aggregate=str_cat_none)\n \n         valid_types = (Series, Index, pd.Series, pd.Index)\n         if isinstance(others, valid_types):\n", "issue": "Note on `Add x.str.cat (#3028)` (lines 125-126)\nIt's not clear to me why `String.str.cat` isn't supported in Dask when `others == None`. Not having the ability to concat a single series into a string is a significant cost, I think. Unless there's a reason for this condition, I recommend deleting lines 126-126.\r\n\n", "before_files": [{"content": "from functools import partial\n\nimport numpy as np\nimport pandas as pd\n\nfrom ..utils import derived_from\n\n\ndef maybe_wrap_pandas(obj, x):\n    if isinstance(x, np.ndarray):\n        if isinstance(obj, pd.Series):\n            return pd.Series(x, index=obj.index, dtype=x.dtype)\n        return pd.Index(x)\n    return x\n\n\nclass Accessor:\n    \"\"\"\n    Base class for pandas Accessor objects cat, dt, and str.\n\n    Notes\n    -----\n    Subclasses should define ``_accessor_name``\n    \"\"\"\n\n    _not_implemented = set()\n\n    def __init__(self, series):\n        from .core import Series\n\n        if not isinstance(series, Series):\n            raise ValueError(\"Accessor cannot be initialized\")\n\n        series_meta = series._meta\n        if hasattr(series_meta, \"to_series\"):  # is index-like\n            series_meta = series_meta.to_series()\n        meta = getattr(series_meta, self._accessor_name)\n\n        self._meta = meta\n        self._series = series\n\n    @staticmethod\n    def _delegate_property(obj, accessor, attr):\n        out = getattr(getattr(obj, accessor, obj), attr)\n        return maybe_wrap_pandas(obj, out)\n\n    @staticmethod\n    def _delegate_method(obj, accessor, attr, args, kwargs):\n        out = getattr(getattr(obj, accessor, obj), attr)(*args, **kwargs)\n        return maybe_wrap_pandas(obj, out)\n\n    def _property_map(self, attr):\n        meta = self._delegate_property(self._series._meta, self._accessor_name, attr)\n        token = \"%s-%s\" % (self._accessor_name, attr)\n        return self._series.map_partitions(\n            self._delegate_property, self._accessor_name, attr, token=token, meta=meta\n        )\n\n    def _function_map(self, attr, *args, **kwargs):\n        if \"meta\" in kwargs:\n            meta = kwargs.pop(\"meta\")\n        else:\n            meta = self._delegate_method(\n                self._series._meta_nonempty, self._accessor_name, attr, args, kwargs\n            )\n        token = \"%s-%s\" % (self._accessor_name, attr)\n        return self._series.map_partitions(\n            self._delegate_method,\n            self._accessor_name,\n            attr,\n            args,\n            kwargs,\n            meta=meta,\n            token=token,\n        )\n\n    @property\n    def _delegates(self):\n        return set(dir(self._meta)) - self._not_implemented\n\n    def __dir__(self):\n        o = self._delegates\n        o.update(self.__dict__)\n        o.update(dir(type(self)))\n        return list(o)\n\n    def __getattr__(self, key):\n        if key in self._delegates:\n            if callable(getattr(self._meta, key)):\n                return partial(self._function_map, key)\n            else:\n                return self._property_map(key)\n        else:\n            raise AttributeError(key)\n\n\nclass DatetimeAccessor(Accessor):\n    \"\"\"Accessor object for datetimelike properties of the Series values.\n\n    Examples\n    --------\n\n    >>> s.dt.microsecond  # doctest: +SKIP\n    \"\"\"\n\n    _accessor_name = \"dt\"\n\n\nclass StringAccessor(Accessor):\n    \"\"\"Accessor object for string properties of the Series values.\n\n    Examples\n    --------\n\n    >>> s.str.lower()  # doctest: +SKIP\n    \"\"\"\n\n    _accessor_name = \"str\"\n    _not_implemented = {\"get_dummies\"}\n\n    @derived_from(pd.core.strings.StringMethods)\n    def split(self, pat=None, n=-1, expand=False):\n        if expand:\n            if n == -1:\n                raise NotImplementedError(\n                    \"To use the expand parameter you must specify the number of \"\n                    \"expected splits with the n= parameter. Usually n splits result in n+1 output columns.\"\n                )\n            else:\n                delimiter = \" \" if pat is None else pat\n                meta = self._series._meta._constructor(\n                    [delimiter.join([\"a\"] * (n + 1))],\n                    index=self._series._meta_nonempty[:1].index,\n                )\n                meta = meta.str.split(n=n, expand=expand, pat=pat)\n        else:\n            meta = (self._series.name, object)\n        return self._function_map(\"split\", pat=pat, n=n, expand=expand, meta=meta)\n\n    @derived_from(pd.core.strings.StringMethods)\n    def cat(self, others=None, sep=None, na_rep=None):\n        from .core import Index, Series\n\n        if others is None:\n            raise NotImplementedError(\"x.str.cat() with `others == None`\")\n\n        valid_types = (Series, Index, pd.Series, pd.Index)\n        if isinstance(others, valid_types):\n            others = [others]\n        elif not all(isinstance(a, valid_types) for a in others):\n            raise TypeError(\"others must be Series/Index\")\n\n        return self._series.map_partitions(\n            str_cat, *others, sep=sep, na_rep=na_rep, meta=self._series._meta\n        )\n\n    @derived_from(pd.core.strings.StringMethods)\n    def extractall(self, pat, flags=0):\n        return self._series.map_partitions(\n            str_extractall, pat, flags, token=\"str-extractall\"\n        )\n\n    def __getitem__(self, index):\n        return self._series.map_partitions(str_get, index, meta=self._series._meta)\n\n\ndef str_extractall(series, pat, flags):\n    return series.str.extractall(pat, flags=flags)\n\n\ndef str_get(series, index):\n    \"\"\" Implements series.str[index] \"\"\"\n    return series.str[index]\n\n\ndef str_cat(self, *others, **kwargs):\n    return self.str.cat(others=others, **kwargs)\n", "path": "dask/dataframe/accessor.py"}], "after_files": [{"content": "from functools import partial\n\nimport numpy as np\nimport pandas as pd\n\nfrom ..utils import derived_from\n\n\ndef maybe_wrap_pandas(obj, x):\n    if isinstance(x, np.ndarray):\n        if isinstance(obj, pd.Series):\n            return pd.Series(x, index=obj.index, dtype=x.dtype)\n        return pd.Index(x)\n    return x\n\n\nclass Accessor:\n    \"\"\"\n    Base class for pandas Accessor objects cat, dt, and str.\n\n    Notes\n    -----\n    Subclasses should define ``_accessor_name``\n    \"\"\"\n\n    _not_implemented = set()\n\n    def __init__(self, series):\n        from .core import Series\n\n        if not isinstance(series, Series):\n            raise ValueError(\"Accessor cannot be initialized\")\n\n        series_meta = series._meta\n        if hasattr(series_meta, \"to_series\"):  # is index-like\n            series_meta = series_meta.to_series()\n        meta = getattr(series_meta, self._accessor_name)\n\n        self._meta = meta\n        self._series = series\n\n    @staticmethod\n    def _delegate_property(obj, accessor, attr):\n        out = getattr(getattr(obj, accessor, obj), attr)\n        return maybe_wrap_pandas(obj, out)\n\n    @staticmethod\n    def _delegate_method(obj, accessor, attr, args, kwargs):\n        out = getattr(getattr(obj, accessor, obj), attr)(*args, **kwargs)\n        return maybe_wrap_pandas(obj, out)\n\n    def _property_map(self, attr):\n        meta = self._delegate_property(self._series._meta, self._accessor_name, attr)\n        token = \"%s-%s\" % (self._accessor_name, attr)\n        return self._series.map_partitions(\n            self._delegate_property, self._accessor_name, attr, token=token, meta=meta\n        )\n\n    def _function_map(self, attr, *args, **kwargs):\n        if \"meta\" in kwargs:\n            meta = kwargs.pop(\"meta\")\n        else:\n            meta = self._delegate_method(\n                self._series._meta_nonempty, self._accessor_name, attr, args, kwargs\n            )\n        token = \"%s-%s\" % (self._accessor_name, attr)\n        return self._series.map_partitions(\n            self._delegate_method,\n            self._accessor_name,\n            attr,\n            args,\n            kwargs,\n            meta=meta,\n            token=token,\n        )\n\n    @property\n    def _delegates(self):\n        return set(dir(self._meta)) - self._not_implemented\n\n    def __dir__(self):\n        o = self._delegates\n        o.update(self.__dict__)\n        o.update(dir(type(self)))\n        return list(o)\n\n    def __getattr__(self, key):\n        if key in self._delegates:\n            if callable(getattr(self._meta, key)):\n                return partial(self._function_map, key)\n            else:\n                return self._property_map(key)\n        else:\n            raise AttributeError(key)\n\n\nclass DatetimeAccessor(Accessor):\n    \"\"\"Accessor object for datetimelike properties of the Series values.\n\n    Examples\n    --------\n\n    >>> s.dt.microsecond  # doctest: +SKIP\n    \"\"\"\n\n    _accessor_name = \"dt\"\n\n\nclass StringAccessor(Accessor):\n    \"\"\"Accessor object for string properties of the Series values.\n\n    Examples\n    --------\n\n    >>> s.str.lower()  # doctest: +SKIP\n    \"\"\"\n\n    _accessor_name = \"str\"\n    _not_implemented = {\"get_dummies\"}\n\n    @derived_from(pd.core.strings.StringMethods)\n    def split(self, pat=None, n=-1, expand=False):\n        if expand:\n            if n == -1:\n                raise NotImplementedError(\n                    \"To use the expand parameter you must specify the number of \"\n                    \"expected splits with the n= parameter. Usually n splits result in n+1 output columns.\"\n                )\n            else:\n                delimiter = \" \" if pat is None else pat\n                meta = self._series._meta._constructor(\n                    [delimiter.join([\"a\"] * (n + 1))],\n                    index=self._series._meta_nonempty[:1].index,\n                )\n                meta = meta.str.split(n=n, expand=expand, pat=pat)\n        else:\n            meta = (self._series.name, object)\n        return self._function_map(\"split\", pat=pat, n=n, expand=expand, meta=meta)\n\n    @derived_from(pd.core.strings.StringMethods)\n    def cat(self, others=None, sep=None, na_rep=None):\n        from .core import Index, Series\n\n        if others is None:\n\n            def str_cat_none(x):\n\n                if isinstance(x, (Series, Index)):\n                    x = x.compute()\n\n                return x.str.cat(sep=sep, na_rep=na_rep)\n\n            return self._series.reduction(chunk=str_cat_none, aggregate=str_cat_none)\n\n        valid_types = (Series, Index, pd.Series, pd.Index)\n        if isinstance(others, valid_types):\n            others = [others]\n        elif not all(isinstance(a, valid_types) for a in others):\n            raise TypeError(\"others must be Series/Index\")\n\n        return self._series.map_partitions(\n            str_cat, *others, sep=sep, na_rep=na_rep, meta=self._series._meta\n        )\n\n    @derived_from(pd.core.strings.StringMethods)\n    def extractall(self, pat, flags=0):\n        return self._series.map_partitions(\n            str_extractall, pat, flags, token=\"str-extractall\"\n        )\n\n    def __getitem__(self, index):\n        return self._series.map_partitions(str_get, index, meta=self._series._meta)\n\n\ndef str_extractall(series, pat, flags):\n    return series.str.extractall(pat, flags=flags)\n\n\ndef str_get(series, index):\n    \"\"\" Implements series.str[index] \"\"\"\n    return series.str[index]\n\n\ndef str_cat(self, *others, **kwargs):\n    return self.str.cat(others=others, **kwargs)\n", "path": "dask/dataframe/accessor.py"}]}