prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  ASV Benchmark for read_excel
  Right now we don't benchmark performance of read_excel across the various engines (xlrd, openpyxl and odfpy) so would gladly accept contributions to improve benchmark coverage on those
  
  </issue>
  <code>
  [start of asv_bench/benchmarks/io/excel.py]
  1 from io import BytesIO
  2 
  3 import numpy as np
  4 
  5 from pandas import DataFrame, ExcelWriter, date_range, read_excel
  6 import pandas.util.testing as tm
  7 
  8 
  9 class Excel:
  10 
  11     params = ["openpyxl", "xlsxwriter", "xlwt"]
  12     param_names = ["engine"]
  13 
  14     def setup(self, engine):
  15         N = 2000
  16         C = 5
  17         self.df = DataFrame(
  18             np.random.randn(N, C),
  19             columns=["float{}".format(i) for i in range(C)],
  20             index=date_range("20000101", periods=N, freq="H"),
  21         )
  22         self.df["object"] = tm.makeStringIndex(N)
  23         self.bio_read = BytesIO()
  24         self.writer_read = ExcelWriter(self.bio_read, engine=engine)
  25         self.df.to_excel(self.writer_read, sheet_name="Sheet1")
  26         self.writer_read.save()
  27         self.bio_read.seek(0)
  28 
  29     def time_read_excel(self, engine):
  30         read_excel(self.bio_read)
  31 
  32     def time_write_excel(self, engine):
  33         bio_write = BytesIO()
  34         bio_write.seek(0)
  35         writer_write = ExcelWriter(bio_write, engine=engine)
  36         self.df.to_excel(writer_write, sheet_name="Sheet1")
  37         writer_write.save()
  38 
  39 
  40 from ..pandas_vb_common import setup  # noqa: F401 isort:skip
  41
  [end of asv_bench/benchmarks/io/excel.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/asv_bench/benchmarks/io/excel.py b/asv_bench/benchmarks/io/excel.py
  --- a/asv_bench/benchmarks/io/excel.py
  +++ b/asv_bench/benchmarks/io/excel.py
  @@ -1,40 +1,72 @@
   from io import BytesIO
   
   import numpy as np
  +from odf.opendocument import OpenDocumentSpreadsheet
  +from odf.table import Table, TableCell, TableRow
  +from odf.text import P
   
   from pandas import DataFrame, ExcelWriter, date_range, read_excel
   import pandas.util.testing as tm
   
   
  -class Excel:
  +def _generate_dataframe():
  +    N = 2000
  +    C = 5
  +    df = DataFrame(
  +        np.random.randn(N, C),
  +        columns=["float{}".format(i) for i in range(C)],
  +        index=date_range("20000101", periods=N, freq="H"),
  +    )
  +    df["object"] = tm.makeStringIndex(N)
  +    return df
  +
  +
  +class WriteExcel:
   
       params = ["openpyxl", "xlsxwriter", "xlwt"]
       param_names = ["engine"]
   
       def setup(self, engine):
  -        N = 2000
  -        C = 5
  -        self.df = DataFrame(
  -            np.random.randn(N, C),
  -            columns=["float{}".format(i) for i in range(C)],
  -            index=date_range("20000101", periods=N, freq="H"),
  -        )
  -        self.df["object"] = tm.makeStringIndex(N)
  -        self.bio_read = BytesIO()
  -        self.writer_read = ExcelWriter(self.bio_read, engine=engine)
  -        self.df.to_excel(self.writer_read, sheet_name="Sheet1")
  -        self.writer_read.save()
  -        self.bio_read.seek(0)
  -
  -    def time_read_excel(self, engine):
  -        read_excel(self.bio_read)
  +        self.df = _generate_dataframe()
   
       def time_write_excel(self, engine):
  -        bio_write = BytesIO()
  -        bio_write.seek(0)
  -        writer_write = ExcelWriter(bio_write, engine=engine)
  -        self.df.to_excel(writer_write, sheet_name="Sheet1")
  -        writer_write.save()
  +        bio = BytesIO()
  +        bio.seek(0)
  +        writer = ExcelWriter(bio, engine=engine)
  +        self.df.to_excel(writer, sheet_name="Sheet1")
  +        writer.save()
  +
  +
  +class ReadExcel:
  +
  +    params = ["xlrd", "openpyxl", "odf"]
  +    param_names = ["engine"]
  +    fname_excel = "spreadsheet.xlsx"
  +    fname_odf = "spreadsheet.ods"
  +
  +    def _create_odf(self):
  +        doc = OpenDocumentSpreadsheet()
  +        table = Table(name="Table1")
  +        for row in self.df.values:
  +            tr = TableRow()
  +            for val in row:
  +                tc = TableCell(valuetype="string")
  +                tc.addElement(P(text=val))
  +                tr.addElement(tc)
  +            table.addElement(tr)
  +
  +        doc.spreadsheet.addElement(table)
  +        doc.save(self.fname_odf)
  +
  +    def setup_cache(self):
  +        self.df = _generate_dataframe()
  +
  +        self.df.to_excel(self.fname_excel, sheet_name="Sheet1")
  +        self._create_odf()
  +
  +    def time_read_excel(self, engine):
  +        fname = self.fname_odf if engine == "odf" else self.fname_excel
  +        read_excel(fname, engine=engine)
   
   
   from ..pandas_vb_common import setup  # noqa: F401 isort:skip
  
verification_info: {"golden_diff": "diff --git a/asv_bench/benchmarks/io/excel.py b/asv_bench/benchmarks/io/excel.py\n--- a/asv_bench/benchmarks/io/excel.py\n+++ b/asv_bench/benchmarks/io/excel.py\n@@ -1,40 +1,72 @@\n from io import BytesIO\n \n import numpy as np\n+from odf.opendocument import OpenDocumentSpreadsheet\n+from odf.table import Table, TableCell, TableRow\n+from odf.text import P\n \n from pandas import DataFrame, ExcelWriter, date_range, read_excel\n import pandas.util.testing as tm\n \n \n-class Excel:\n+def _generate_dataframe():\n+    N = 2000\n+    C = 5\n+    df = DataFrame(\n+        np.random.randn(N, C),\n+        columns=[\"float{}\".format(i) for i in range(C)],\n+        index=date_range(\"20000101\", periods=N, freq=\"H\"),\n+    )\n+    df[\"object\"] = tm.makeStringIndex(N)\n+    return df\n+\n+\n+class WriteExcel:\n \n     params = [\"openpyxl\", \"xlsxwriter\", \"xlwt\"]\n     param_names = [\"engine\"]\n \n     def setup(self, engine):\n-        N = 2000\n-        C = 5\n-        self.df = DataFrame(\n-            np.random.randn(N, C),\n-            columns=[\"float{}\".format(i) for i in range(C)],\n-            index=date_range(\"20000101\", periods=N, freq=\"H\"),\n-        )\n-        self.df[\"object\"] = tm.makeStringIndex(N)\n-        self.bio_read = BytesIO()\n-        self.writer_read = ExcelWriter(self.bio_read, engine=engine)\n-        self.df.to_excel(self.writer_read, sheet_name=\"Sheet1\")\n-        self.writer_read.save()\n-        self.bio_read.seek(0)\n-\n-    def time_read_excel(self, engine):\n-        read_excel(self.bio_read)\n+        self.df = _generate_dataframe()\n \n     def time_write_excel(self, engine):\n-        bio_write = BytesIO()\n-        bio_write.seek(0)\n-        writer_write = ExcelWriter(bio_write, engine=engine)\n-        self.df.to_excel(writer_write, sheet_name=\"Sheet1\")\n-        writer_write.save()\n+        bio = BytesIO()\n+        bio.seek(0)\n+        writer = ExcelWriter(bio, engine=engine)\n+        self.df.to_excel(writer, sheet_name=\"Sheet1\")\n+        writer.save()\n+\n+\n+class ReadExcel:\n+\n+    params = [\"xlrd\", \"openpyxl\", \"odf\"]\n+    param_names = [\"engine\"]\n+    fname_excel = \"spreadsheet.xlsx\"\n+    fname_odf = \"spreadsheet.ods\"\n+\n+    def _create_odf(self):\n+        doc = OpenDocumentSpreadsheet()\n+        table = Table(name=\"Table1\")\n+        for row in self.df.values:\n+            tr = TableRow()\n+            for val in row:\n+                tc = TableCell(valuetype=\"string\")\n+                tc.addElement(P(text=val))\n+                tr.addElement(tc)\n+            table.addElement(tr)\n+\n+        doc.spreadsheet.addElement(table)\n+        doc.save(self.fname_odf)\n+\n+    def setup_cache(self):\n+        self.df = _generate_dataframe()\n+\n+        self.df.to_excel(self.fname_excel, sheet_name=\"Sheet1\")\n+        self._create_odf()\n+\n+    def time_read_excel(self, engine):\n+        fname = self.fname_odf if engine == \"odf\" else self.fname_excel\n+        read_excel(fname, engine=engine)\n \n \n from ..pandas_vb_common import setup  # noqa: F401 isort:skip\n", "issue": "ASV Benchmark for read_excel\nRight now we don't benchmark performance of read_excel across the various engines (xlrd, openpyxl and odfpy) so would gladly accept contributions to improve benchmark coverage on those\n", "before_files": [{"content": "from io import BytesIO\n\nimport numpy as np\n\nfrom pandas import DataFrame, ExcelWriter, date_range, read_excel\nimport pandas.util.testing as tm\n\n\nclass Excel:\n\n    params = [\"openpyxl\", \"xlsxwriter\", \"xlwt\"]\n    param_names = [\"engine\"]\n\n    def setup(self, engine):\n        N = 2000\n        C = 5\n        self.df = DataFrame(\n            np.random.randn(N, C),\n            columns=[\"float{}\".format(i) for i in range(C)],\n            index=date_range(\"20000101\", periods=N, freq=\"H\"),\n        )\n        self.df[\"object\"] = tm.makeStringIndex(N)\n        self.bio_read = BytesIO()\n        self.writer_read = ExcelWriter(self.bio_read, engine=engine)\n        self.df.to_excel(self.writer_read, sheet_name=\"Sheet1\")\n        self.writer_read.save()\n        self.bio_read.seek(0)\n\n    def time_read_excel(self, engine):\n        read_excel(self.bio_read)\n\n    def time_write_excel(self, engine):\n        bio_write = BytesIO()\n        bio_write.seek(0)\n        writer_write = ExcelWriter(bio_write, engine=engine)\n        self.df.to_excel(writer_write, sheet_name=\"Sheet1\")\n        writer_write.save()\n\n\nfrom ..pandas_vb_common import setup  # noqa: F401 isort:skip\n", "path": "asv_bench/benchmarks/io/excel.py"}]}