prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  MAINT: Set only positional parameter for `(geo)accessor`
  <!--
  Thanks for contributing a pull request!
  
  Please follow these standard acronyms to start the commit message:
  
  - ENH: enhancement
  - BUG: bug fix
  - DOC: documentation
  - TYP: type annotations
  - TST: addition or modification of tests
  - MAINT: maintenance commit (refactoring, typos, etc.)
  - BLD: change related to building
  - REL: related to releasing
  - API: an (incompatible) API change
  - DEP: deprecate something, or remove a deprecated object
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  - CLN: Code cleanup
  -->
  
  - [ ] closes #xxxx
  - [x] whatsnew entry
  
  The first parameter of `(geo)accessor` methods must be set as only positional parameter.
  
  --- END ISSUE ---
  
  Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
  --- BEGIN FILES ---
  Path: `dtoolkit/accessor/dataframe/repeat.py`
  Content:
  ```
  1 from __future__ import annotations
  2 
  3 import numpy as np
  4 import pandas as pd
  5 
  6 from dtoolkit._typing import Axis
  7 from dtoolkit.accessor.register import register_dataframe_method
  8 
  9 
  10 @register_dataframe_method
  11 def repeat(
  12     df: pd.DataFrame,
  13     repeat: int | list[int],
  14     /,
  15     axis: Axis = 0,
  16 ) -> pd.DataFrame:
  17     """
  18     Repeat row or column of a :obj:`~pandas.DataFrame`.
  19 
  20     Returns a new DataFrame where each row/column is repeated
  21     consecutively a given number of times.
  22 
  23     A sugary syntax wraps :meth:`numpy.repeat`.
  24 
  25     Parameters
  26     ----------
  27     repeat : int or array of ints
  28         The number of repetitions for each element. This should be a
  29         non-negative integer. Repeating 0 times will return an empty
  30         :obj:`~pandas.DataFrame`.
  31 
  32     axis : {0 or 'index', 1 or 'columns'}, default 0
  33         The axis along which to repeat.
  34 
  35         * 0, or 'index' : Along the row to repeat.
  36         * 1, or 'columns' : Along the column to repeat.
  37 
  38     Returns
  39     -------
  40     DataFrame
  41         Newly created DataFrame with repeated elements.
  42 
  43     See Also
  44     --------
  45     numpy.repeat : This transformer's prototype method.
  46 
  47     Examples
  48     --------
  49     >>> import pandas as pd
  50     >>> import dtoolkit.accessor
  51     >>> df = pd.DataFrame({'a': [1, 2], 'b':[3, 4]})
  52     >>> df
  53        a  b
  54     0  1  3
  55     1  2  4
  56 
  57     Each row repeat two times.
  58 
  59     >>> df.repeat(2)
  60        a  b
  61     0  1  3
  62     0  1  3
  63     1  2  4
  64     1  2  4
  65 
  66     Each column repeat two times.
  67 
  68     >>> df.repeat(2, 1)
  69        a  a  b  b
  70     0  1  1  3  3
  71     1  2  2  4  4
  72 
  73     ``a`` column repeat 1 times, ``b`` column repeat 2 times.
  74 
  75     >>> df.repeat([1, 2], 1)
  76        a  b  b
  77     0  1  3  3
  78     1  2  4  4
  79     """
  80 
  81     axis = df._get_axis_number(axis)
  82     return pd.DataFrame(
  83         np.repeat(
  84             df._values,
  85             repeat,
  86             axis=axis,
  87         ),
  88         index=df.index.repeat(repeat) if axis == 0 else df.index,
  89         columns=df.columns.repeat(repeat) if axis == 1 else df.columns,
  90     )
  91
  ```
  --- 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()
  
  ```
  
golden_diff: diff --git a/dtoolkit/accessor/dataframe/repeat.py b/dtoolkit/accessor/dataframe/repeat.py
  --- a/dtoolkit/accessor/dataframe/repeat.py
  +++ b/dtoolkit/accessor/dataframe/repeat.py
  @@ -10,7 +10,7 @@
   @register_dataframe_method
   def repeat(
       df: pd.DataFrame,
  -    repeat: int | list[int],
  +    repeats: int | list[int],
       /,
       axis: Axis = 0,
   ) -> pd.DataFrame:
  @@ -24,7 +24,7 @@
   
       Parameters
       ----------
  -    repeat : int or array of ints
  +    repeats : int or array of ints
           The number of repetitions for each element. This should be a
           non-negative integer. Repeating 0 times will return an empty
           :obj:`~pandas.DataFrame`.
  @@ -78,13 +78,12 @@
       1  2  4  4
       """
   
  -    axis = df._get_axis_number(axis)
       return pd.DataFrame(
           np.repeat(
               df._values,
  -            repeat,
  -            axis=axis,
  +            repeats,
  +            axis=df._get_axis_number(axis),
           ),
  -        index=df.index.repeat(repeat) if axis == 0 else df.index,
  -        columns=df.columns.repeat(repeat) if axis == 1 else df.columns,
  +        index=df.index.repeat(repeats) if axis == 0 else df.index,
  +        columns=df.columns.repeat(repeats) if axis == 1 else df.columns,
       )
  
verification_info: {"golden_diff": "diff --git a/dtoolkit/accessor/dataframe/repeat.py b/dtoolkit/accessor/dataframe/repeat.py\n--- a/dtoolkit/accessor/dataframe/repeat.py\n+++ b/dtoolkit/accessor/dataframe/repeat.py\n@@ -10,7 +10,7 @@\n @register_dataframe_method\n def repeat(\n     df: pd.DataFrame,\n-    repeat: int | list[int],\n+    repeats: int | list[int],\n     /,\n     axis: Axis = 0,\n ) -> pd.DataFrame:\n@@ -24,7 +24,7 @@\n \n     Parameters\n     ----------\n-    repeat : int or array of ints\n+    repeats : int or array of ints\n         The number of repetitions for each element. This should be a\n         non-negative integer. Repeating 0 times will return an empty\n         :obj:`~pandas.DataFrame`.\n@@ -78,13 +78,12 @@\n     1  2  4  4\n     \"\"\"\n \n-    axis = df._get_axis_number(axis)\n     return pd.DataFrame(\n         np.repeat(\n             df._values,\n-            repeat,\n-            axis=axis,\n+            repeats,\n+            axis=df._get_axis_number(axis),\n         ),\n-        index=df.index.repeat(repeat) if axis == 0 else df.index,\n-        columns=df.columns.repeat(repeat) if axis == 1 else df.columns,\n+        index=df.index.repeat(repeats) if axis == 0 else df.index,\n+        columns=df.columns.repeat(repeats) if axis == 1 else df.columns,\n     )\n", "issue": "MAINT: Set only positional parameter for `(geo)accessor`\n<!--\r\nThanks for contributing a pull request!\r\n\r\nPlease follow these standard acronyms to start the commit message:\r\n\r\n- ENH: enhancement\r\n- BUG: bug fix\r\n- DOC: documentation\r\n- TYP: type annotations\r\n- TST: addition or modification of tests\r\n- MAINT: maintenance commit (refactoring, typos, etc.)\r\n- BLD: change related to building\r\n- REL: related to releasing\r\n- API: an (incompatible) API change\r\n- DEP: deprecate something, or remove a deprecated object\r\n- DEV: development tool or utility\r\n- REV: revert an earlier commit\r\n- PERF: performance improvement\r\n- BOT: always commit via a bot\r\n- CI: related to CI or CD\r\n- CLN: Code cleanup\r\n-->\r\n\r\n- [ ] closes #xxxx\r\n- [x] whatsnew entry\r\n\r\nThe first parameter of `(geo)accessor` methods must be set as only positional parameter.\n", "before_files": [{"content": "from __future__ import annotations\n\nimport numpy as np\nimport pandas as pd\n\nfrom dtoolkit._typing import Axis\nfrom dtoolkit.accessor.register import register_dataframe_method\n\n\n@register_dataframe_method\ndef repeat(\n    df: pd.DataFrame,\n    repeat: int | list[int],\n    /,\n    axis: Axis = 0,\n) -> pd.DataFrame:\n    \"\"\"\n    Repeat row or column of a :obj:`~pandas.DataFrame`.\n\n    Returns a new DataFrame where each row/column is repeated\n    consecutively a given number of times.\n\n    A sugary syntax wraps :meth:`numpy.repeat`.\n\n    Parameters\n    ----------\n    repeat : int or array of ints\n        The number of repetitions for each element. This should be a\n        non-negative integer. Repeating 0 times will return an empty\n        :obj:`~pandas.DataFrame`.\n\n    axis : {0 or 'index', 1 or 'columns'}, default 0\n        The axis along which to repeat.\n\n        * 0, or 'index' : Along the row to repeat.\n        * 1, or 'columns' : Along the column to repeat.\n\n    Returns\n    -------\n    DataFrame\n        Newly created DataFrame with repeated elements.\n\n    See Also\n    --------\n    numpy.repeat : This transformer's prototype method.\n\n    Examples\n    --------\n    >>> import pandas as pd\n    >>> import dtoolkit.accessor\n    >>> df = pd.DataFrame({'a': [1, 2], 'b':[3, 4]})\n    >>> df\n       a  b\n    0  1  3\n    1  2  4\n\n    Each row repeat two times.\n\n    >>> df.repeat(2)\n       a  b\n    0  1  3\n    0  1  3\n    1  2  4\n    1  2  4\n\n    Each column repeat two times.\n\n    >>> df.repeat(2, 1)\n       a  a  b  b\n    0  1  1  3  3\n    1  2  2  4  4\n\n    ``a`` column repeat 1 times, ``b`` column repeat 2 times.\n\n    >>> df.repeat([1, 2], 1)\n       a  b  b\n    0  1  3  3\n    1  2  4  4\n    \"\"\"\n\n    axis = df._get_axis_number(axis)\n    return pd.DataFrame(\n        np.repeat(\n            df._values,\n            repeat,\n            axis=axis,\n        ),\n        index=df.index.repeat(repeat) if axis == 0 else df.index,\n        columns=df.columns.repeat(repeat) if axis == 1 else df.columns,\n    )\n", "path": "dtoolkit/accessor/dataframe/repeat.py"}], "after_files": [{"content": "from __future__ import annotations\n\nimport numpy as np\nimport pandas as pd\n\nfrom dtoolkit._typing import Axis\nfrom dtoolkit.accessor.register import register_dataframe_method\n\n\n@register_dataframe_method\ndef repeat(\n    df: pd.DataFrame,\n    repeats: int | list[int],\n    /,\n    axis: Axis = 0,\n) -> pd.DataFrame:\n    \"\"\"\n    Repeat row or column of a :obj:`~pandas.DataFrame`.\n\n    Returns a new DataFrame where each row/column is repeated\n    consecutively a given number of times.\n\n    A sugary syntax wraps :meth:`numpy.repeat`.\n\n    Parameters\n    ----------\n    repeats : int or array of ints\n        The number of repetitions for each element. This should be a\n        non-negative integer. Repeating 0 times will return an empty\n        :obj:`~pandas.DataFrame`.\n\n    axis : {0 or 'index', 1 or 'columns'}, default 0\n        The axis along which to repeat.\n\n        * 0, or 'index' : Along the row to repeat.\n        * 1, or 'columns' : Along the column to repeat.\n\n    Returns\n    -------\n    DataFrame\n        Newly created DataFrame with repeated elements.\n\n    See Also\n    --------\n    numpy.repeat : This transformer's prototype method.\n\n    Examples\n    --------\n    >>> import pandas as pd\n    >>> import dtoolkit.accessor\n    >>> df = pd.DataFrame({'a': [1, 2], 'b':[3, 4]})\n    >>> df\n       a  b\n    0  1  3\n    1  2  4\n\n    Each row repeat two times.\n\n    >>> df.repeat(2)\n       a  b\n    0  1  3\n    0  1  3\n    1  2  4\n    1  2  4\n\n    Each column repeat two times.\n\n    >>> df.repeat(2, 1)\n       a  a  b  b\n    0  1  1  3  3\n    1  2  2  4  4\n\n    ``a`` column repeat 1 times, ``b`` column repeat 2 times.\n\n    >>> df.repeat([1, 2], 1)\n       a  b  b\n    0  1  3  3\n    1  2  4  4\n    \"\"\"\n\n    return pd.DataFrame(\n        np.repeat(\n            df._values,\n            repeats,\n            axis=df._get_axis_number(axis),\n        ),\n        index=df.index.repeat(repeats) if axis == 0 else df.index,\n        columns=df.columns.repeat(repeats) if axis == 1 else df.columns,\n    )\n", "path": "dtoolkit/accessor/dataframe/repeat.py"}]}