prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  Add columns-parameter like in feather.read_dataframe
  Wes suggested to raise this feature request here again, after I wondered why `pandas.read_feather` is lacking a `columns`-parameter like the [`feather-format`](https://github.com/wesm/feather) package has it.
  
  You can read in only a subset of columns from a feather-file with e.g.: 
  `df = feather.read_dataframe('df_test.feather', columns='b')`
  
  It would be really nice if `pandas.read_feather` also had this built in, so you don't have to install and import the feather-package just for that.
  
  </issue>
  <code>
  [start of pandas/io/feather_format.py]
  1 """ feather-format compat """
  2 
  3 from distutils.version import LooseVersion
  4 
  5 from pandas.compat import range
  6 from pandas.util._decorators import deprecate_kwarg
  7 
  8 from pandas import DataFrame, Int64Index, RangeIndex
  9 
  10 from pandas.io.common import _stringify_path
  11 
  12 
  13 def _try_import():
  14     # since pandas is a dependency of pyarrow
  15     # we need to import on first use
  16     try:
  17         import pyarrow
  18         from pyarrow import feather
  19     except ImportError:
  20         # give a nice error message
  21         raise ImportError("pyarrow is not installed\n\n"
  22                           "you can install via conda\n"
  23                           "conda install pyarrow -c conda-forge\n"
  24                           "or via pip\n"
  25                           "pip install -U pyarrow\n")
  26 
  27     if LooseVersion(pyarrow.__version__) < LooseVersion('0.4.1'):
  28         raise ImportError("pyarrow >= 0.4.1 required for feather support\n\n"
  29                           "you can install via conda\n"
  30                           "conda install pyarrow -c conda-forge"
  31                           "or via pip\n"
  32                           "pip install -U pyarrow\n")
  33 
  34     return feather, pyarrow
  35 
  36 
  37 def to_feather(df, path):
  38     """
  39     Write a DataFrame to the feather-format
  40 
  41     Parameters
  42     ----------
  43     df : DataFrame
  44     path : string file path, or file-like object
  45 
  46     """
  47     path = _stringify_path(path)
  48     if not isinstance(df, DataFrame):
  49         raise ValueError("feather only support IO with DataFrames")
  50 
  51     feather = _try_import()[0]
  52     valid_types = {'string', 'unicode'}
  53 
  54     # validate index
  55     # --------------
  56 
  57     # validate that we have only a default index
  58     # raise on anything else as we don't serialize the index
  59 
  60     if not isinstance(df.index, Int64Index):
  61         raise ValueError("feather does not support serializing {} "
  62                          "for the index; you can .reset_index()"
  63                          "to make the index into column(s)".format(
  64                              type(df.index)))
  65 
  66     if not df.index.equals(RangeIndex.from_range(range(len(df)))):
  67         raise ValueError("feather does not support serializing a "
  68                          "non-default index for the index; you "
  69                          "can .reset_index() to make the index "
  70                          "into column(s)")
  71 
  72     if df.index.name is not None:
  73         raise ValueError("feather does not serialize index meta-data on a "
  74                          "default index")
  75 
  76     # validate columns
  77     # ----------------
  78 
  79     # must have value column names (strings only)
  80     if df.columns.inferred_type not in valid_types:
  81         raise ValueError("feather must have string column names")
  82 
  83     feather.write_feather(df, path)
  84 
  85 
  86 @deprecate_kwarg(old_arg_name='nthreads', new_arg_name='use_threads')
  87 def read_feather(path, use_threads=True):
  88     """
  89     Load a feather-format object from the file path
  90 
  91     .. versionadded 0.20.0
  92 
  93     Parameters
  94     ----------
  95     path : string file path, or file-like object
  96     nthreads : int, default 1
  97         Number of CPU threads to use when reading to pandas.DataFrame
  98 
  99        .. versionadded 0.21.0
  100        .. deprecated 0.24.0
  101     use_threads : bool, default True
  102         Whether to parallelize reading using multiple threads
  103 
  104        .. versionadded 0.24.0
  105 
  106     Returns
  107     -------
  108     type of object stored in file
  109 
  110     """
  111 
  112     feather, pyarrow = _try_import()
  113     path = _stringify_path(path)
  114 
  115     if LooseVersion(pyarrow.__version__) < LooseVersion('0.11.0'):
  116         int_use_threads = int(use_threads)
  117         if int_use_threads < 1:
  118             int_use_threads = 1
  119         return feather.read_feather(path, nthreads=int_use_threads)
  120 
  121     return feather.read_feather(path, use_threads=bool(use_threads))
  122
  [end of pandas/io/feather_format.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/pandas/io/feather_format.py b/pandas/io/feather_format.py
  --- a/pandas/io/feather_format.py
  +++ b/pandas/io/feather_format.py
  @@ -84,7 +84,7 @@
   
   
   @deprecate_kwarg(old_arg_name='nthreads', new_arg_name='use_threads')
  -def read_feather(path, use_threads=True):
  +def read_feather(path, columns=None, use_threads=True):
       """
       Load a feather-format object from the file path
   
  @@ -93,6 +93,10 @@
       Parameters
       ----------
       path : string file path, or file-like object
  +    columns : sequence, default None
  +        If not provided, all columns are read
  +
  +        .. versionadded 0.24.0
       nthreads : int, default 1
           Number of CPU threads to use when reading to pandas.DataFrame
   
  @@ -116,6 +120,8 @@
           int_use_threads = int(use_threads)
           if int_use_threads < 1:
               int_use_threads = 1
  -        return feather.read_feather(path, nthreads=int_use_threads)
  +        return feather.read_feather(path, columns=columns,
  +                                    nthreads=int_use_threads)
   
  -    return feather.read_feather(path, use_threads=bool(use_threads))
  +    return feather.read_feather(path, columns=columns,
  +                                use_threads=bool(use_threads))
  
verification_info: {"golden_diff": "diff --git a/pandas/io/feather_format.py b/pandas/io/feather_format.py\n--- a/pandas/io/feather_format.py\n+++ b/pandas/io/feather_format.py\n@@ -84,7 +84,7 @@\n \n \n @deprecate_kwarg(old_arg_name='nthreads', new_arg_name='use_threads')\n-def read_feather(path, use_threads=True):\n+def read_feather(path, columns=None, use_threads=True):\n     \"\"\"\n     Load a feather-format object from the file path\n \n@@ -93,6 +93,10 @@\n     Parameters\n     ----------\n     path : string file path, or file-like object\n+    columns : sequence, default None\n+        If not provided, all columns are read\n+\n+        .. versionadded 0.24.0\n     nthreads : int, default 1\n         Number of CPU threads to use when reading to pandas.DataFrame\n \n@@ -116,6 +120,8 @@\n         int_use_threads = int(use_threads)\n         if int_use_threads < 1:\n             int_use_threads = 1\n-        return feather.read_feather(path, nthreads=int_use_threads)\n+        return feather.read_feather(path, columns=columns,\n+                                    nthreads=int_use_threads)\n \n-    return feather.read_feather(path, use_threads=bool(use_threads))\n+    return feather.read_feather(path, columns=columns,\n+                                use_threads=bool(use_threads))\n", "issue": "Add columns-parameter like in feather.read_dataframe\nWes suggested to raise this feature request here again, after I wondered why `pandas.read_feather` is lacking a `columns`-parameter like the [`feather-format`](https://github.com/wesm/feather) package has it.\r\n\r\nYou can read in only a subset of columns from a feather-file with e.g.: \r\n`df = feather.read_dataframe('df_test.feather', columns='b')`\r\n\r\nIt would be really nice if `pandas.read_feather` also had this built in, so you don't have to install and import the feather-package just for that.\n", "before_files": [{"content": "\"\"\" feather-format compat \"\"\"\n\nfrom distutils.version import LooseVersion\n\nfrom pandas.compat import range\nfrom pandas.util._decorators import deprecate_kwarg\n\nfrom pandas import DataFrame, Int64Index, RangeIndex\n\nfrom pandas.io.common import _stringify_path\n\n\ndef _try_import():\n    # since pandas is a dependency of pyarrow\n    # we need to import on first use\n    try:\n        import pyarrow\n        from pyarrow import feather\n    except ImportError:\n        # give a nice error message\n        raise ImportError(\"pyarrow is not installed\\n\\n\"\n                          \"you can install via conda\\n\"\n                          \"conda install pyarrow -c conda-forge\\n\"\n                          \"or via pip\\n\"\n                          \"pip install -U pyarrow\\n\")\n\n    if LooseVersion(pyarrow.__version__) < LooseVersion('0.4.1'):\n        raise ImportError(\"pyarrow >= 0.4.1 required for feather support\\n\\n\"\n                          \"you can install via conda\\n\"\n                          \"conda install pyarrow -c conda-forge\"\n                          \"or via pip\\n\"\n                          \"pip install -U pyarrow\\n\")\n\n    return feather, pyarrow\n\n\ndef to_feather(df, path):\n    \"\"\"\n    Write a DataFrame to the feather-format\n\n    Parameters\n    ----------\n    df : DataFrame\n    path : string file path, or file-like object\n\n    \"\"\"\n    path = _stringify_path(path)\n    if not isinstance(df, DataFrame):\n        raise ValueError(\"feather only support IO with DataFrames\")\n\n    feather = _try_import()[0]\n    valid_types = {'string', 'unicode'}\n\n    # validate index\n    # --------------\n\n    # validate that we have only a default index\n    # raise on anything else as we don't serialize the index\n\n    if not isinstance(df.index, Int64Index):\n        raise ValueError(\"feather does not support serializing {} \"\n                         \"for the index; you can .reset_index()\"\n                         \"to make the index into column(s)\".format(\n                             type(df.index)))\n\n    if not df.index.equals(RangeIndex.from_range(range(len(df)))):\n        raise ValueError(\"feather does not support serializing a \"\n                         \"non-default index for the index; you \"\n                         \"can .reset_index() to make the index \"\n                         \"into column(s)\")\n\n    if df.index.name is not None:\n        raise ValueError(\"feather does not serialize index meta-data on a \"\n                         \"default index\")\n\n    # validate columns\n    # ----------------\n\n    # must have value column names (strings only)\n    if df.columns.inferred_type not in valid_types:\n        raise ValueError(\"feather must have string column names\")\n\n    feather.write_feather(df, path)\n\n\n@deprecate_kwarg(old_arg_name='nthreads', new_arg_name='use_threads')\ndef read_feather(path, use_threads=True):\n    \"\"\"\n    Load a feather-format object from the file path\n\n    .. versionadded 0.20.0\n\n    Parameters\n    ----------\n    path : string file path, or file-like object\n    nthreads : int, default 1\n        Number of CPU threads to use when reading to pandas.DataFrame\n\n       .. versionadded 0.21.0\n       .. deprecated 0.24.0\n    use_threads : bool, default True\n        Whether to parallelize reading using multiple threads\n\n       .. versionadded 0.24.0\n\n    Returns\n    -------\n    type of object stored in file\n\n    \"\"\"\n\n    feather, pyarrow = _try_import()\n    path = _stringify_path(path)\n\n    if LooseVersion(pyarrow.__version__) < LooseVersion('0.11.0'):\n        int_use_threads = int(use_threads)\n        if int_use_threads < 1:\n            int_use_threads = 1\n        return feather.read_feather(path, nthreads=int_use_threads)\n\n    return feather.read_feather(path, use_threads=bool(use_threads))\n", "path": "pandas/io/feather_format.py"}]}