Excel Reader Refactor - Base Class Introduction (#24829)

Author: WillAyd

pandas/io/excel.py

@@ -375,60 +375,25 @@ def read_excel(io,
  **kwds)
 
 
-class _XlrdReader(object):
-
- def __init__(self, filepath_or_buffer):
- """Reader using xlrd engine.
-
- Parameters
- ----------
- filepath_or_buffer : string, path object or Workbook
- Object to be parsed.
- """
- err_msg = "Install xlrd >= 1.0.0 for Excel support"
-
- try:
- import xlrd
- except ImportError:
- raise ImportError(err_msg)
- else:
- if xlrd.__VERSION__ < LooseVersion("1.0.0"):
- raise ImportError(err_msg +
- ". Current version " + xlrd.__VERSION__)
+@add_metaclass(abc.ABCMeta)
+class _BaseExcelReader(object):
 
- # If filepath_or_buffer is a url, want to keep the data as bytes so
- # can't pass to get_filepath_or_buffer()
- if _is_url(filepath_or_buffer):
- filepath_or_buffer = _urlopen(filepath_or_buffer)
- elif not isinstance(filepath_or_buffer, (ExcelFile, xlrd.Book)):
- filepath_or_buffer, _, _, _ = get_filepath_or_buffer(
- filepath_or_buffer)
+ @property
+ @abc.abstractmethod
+ def sheet_names(self):
+ pass
 
- if isinstance(filepath_or_buffer, xlrd.Book):
- self.book = filepath_or_buffer
- elif not isinstance(filepath_or_buffer, xlrd.Book) and hasattr(
- filepath_or_buffer, "read"):
- # N.B. xlrd.Book has a read attribute too
- if hasattr(filepath_or_buffer, 'seek'):
- try:
- # GH 19779
- filepath_or_buffer.seek(0)
- except UnsupportedOperation:
- # HTTPResponse does not support seek()
- # GH 20434
- pass
+ @abc.abstractmethod
+ def get_sheet_by_name(self, name):
+ pass
 
- data = filepath_or_buffer.read()
- self.book = xlrd.open_workbook(file_contents=data)
- elif isinstance(filepath_or_buffer, compat.string_types):
- self.book = xlrd.open_workbook(filepath_or_buffer)
- else:
- raise ValueError('Must explicitly set engine if not passing in'
- ' buffer or path for io.')
+ @abc.abstractmethod
+ def get_sheet_by_index(self, index):
+ pass
 
- @property
- def sheet_names(self):
- return self.book.sheet_names()
+ @abc.abstractmethod
+ def get_sheet_data(self, sheet, convert_float):
+ pass
 
  def parse(self,
  sheet_name=0,
@@ -455,56 +420,14 @@ def parse(self,
 
  _validate_header_arg(header)
 
- from xlrd import (xldate, XL_CELL_DATE,
- XL_CELL_ERROR, XL_CELL_BOOLEAN,
- XL_CELL_NUMBER)
-
- epoch1904 = self.book.datemode
-
- def _parse_cell(cell_contents, cell_typ):
- """converts the contents of the cell into a pandas
- appropriate object"""
-
- if cell_typ == XL_CELL_DATE:
-
- # Use the newer xlrd datetime handling.
- try:
- cell_contents = xldate.xldate_as_datetime(
- cell_contents, epoch1904)
- except OverflowError:
- return cell_contents
-
- # Excel doesn't distinguish between dates and time,
- # so we treat dates on the epoch as times only.
- # Also, Excel supports 1900 and 1904 epochs.
- year = (cell_contents.timetuple())[0:3]
- if ((not epoch1904 and year == (1899, 12, 31)) or
- (epoch1904 and year == (1904, 1, 1))):
- cell_contents = time(cell_contents.hour,
- cell_contents.minute,
- cell_contents.second,
- cell_contents.microsecond)
-
- elif cell_typ == XL_CELL_ERROR:
- cell_contents = np.nan
- elif cell_typ == XL_CELL_BOOLEAN:
- cell_contents = bool(cell_contents)
- elif convert_float and cell_typ == XL_CELL_NUMBER:
- # GH5394 - Excel 'numbers' are always floats
- # it's a minimal perf hit and less surprising
- val = int(cell_contents)
- if val == cell_contents:
- cell_contents = val
- return cell_contents
-
  ret_dict = False
 
  # Keep sheetname to maintain backwards compatibility.
  if isinstance(sheet_name, list):
  sheets = sheet_name
  ret_dict = True
  elif sheet_name is None:
- sheets = self.book.sheet_names()
+ sheets = self.sheet_names
  ret_dict = True
  else:
  sheets = [sheet_name]
@@ -519,19 +442,13 @@ def _parse_cell(cell_contents, cell_typ):
  print("Reading sheet {sheet}".format(sheet=asheetname))
 
  if isinstance(asheetname, compat.string_types):
- sheet = self.book.sheet_by_name(asheetname)
+ sheet = self.get_sheet_by_name(asheetname)
  else: # assume an integer if not a string
- sheet = self.book.sheet_by_index(asheetname)
+ sheet = self.get_sheet_by_index(asheetname)
 
- data = []
+ data = self.get_sheet_data(sheet, convert_float)
  usecols = _maybe_convert_usecols(usecols)
 
- for i in range(sheet.nrows):
- row = [_parse_cell(value, typ)
- for value, typ in zip(sheet.row_values(i),
- sheet.row_types(i))]
- data.append(row)
-
  if sheet.nrows == 0:
  output[asheetname] = DataFrame()
  continue
@@ -620,6 +537,120 @@ def _parse_cell(cell_contents, cell_typ):
  return output[asheetname]
 
 
+class _XlrdReader(_BaseExcelReader):
+
+ def __init__(self, filepath_or_buffer):
+ """Reader using xlrd engine.
+
+ Parameters
+ ----------
+ filepath_or_buffer : string, path object or Workbook
+ Object to be parsed.
+ """
+ err_msg = "Install xlrd >= 1.0.0 for Excel support"
+
+ try:
+ import xlrd
+ except ImportError:
+ raise ImportError(err_msg)
+ else:
+ if xlrd.__VERSION__ < LooseVersion("1.0.0"):
+ raise ImportError(err_msg +
+ ". Current version " + xlrd.__VERSION__)
+
+ # If filepath_or_buffer is a url, want to keep the data as bytes so
+ # can't pass to get_filepath_or_buffer()
+ if _is_url(filepath_or_buffer):
+ filepath_or_buffer = _urlopen(filepath_or_buffer)
+ elif not isinstance(filepath_or_buffer, (ExcelFile, xlrd.Book)):
+ filepath_or_buffer, _, _, _ = get_filepath_or_buffer(
+ filepath_or_buffer)
+
+ if isinstance(filepath_or_buffer, xlrd.Book):
+ self.book = filepath_or_buffer
+ elif hasattr(filepath_or_buffer, "read"):
+ # N.B. xlrd.Book has a read attribute too
+ if hasattr(filepath_or_buffer, 'seek'):
+ try:
+ # GH 19779
+ filepath_or_buffer.seek(0)
+ except UnsupportedOperation:
+ # HTTPResponse does not support seek()
+ # GH 20434
+ pass
+
+ data = filepath_or_buffer.read()
+ self.book = xlrd.open_workbook(file_contents=data)
+ elif isinstance(filepath_or_buffer, compat.string_types):
+ self.book = xlrd.open_workbook(filepath_or_buffer)
+ else:
+ raise ValueError('Must explicitly set engine if not passing in'
+ ' buffer or path for io.')
+
+ @property
+ def sheet_names(self):
+ return self.book.sheet_names()
+
+ def get_sheet_by_name(self, name):
+ return self.book.sheet_by_name(name)
+
+ def get_sheet_by_index(self, index):
+ return self.book.sheet_by_index(index)
+
+ def get_sheet_data(self, sheet, convert_float):
+ from xlrd import (xldate, XL_CELL_DATE,
+ XL_CELL_ERROR, XL_CELL_BOOLEAN,
+ XL_CELL_NUMBER)
+
+ epoch1904 = self.book.datemode
+
+ def _parse_cell(cell_contents, cell_typ):
+ """converts the contents of the cell into a pandas
+ appropriate object"""
+
+ if cell_typ == XL_CELL_DATE:
+
+ # Use the newer xlrd datetime handling.
+ try:
+ cell_contents = xldate.xldate_as_datetime(
+ cell_contents, epoch1904)
+ except OverflowError:
+ return cell_contents
+
+ # Excel doesn't distinguish between dates and time,
+ # so we treat dates on the epoch as times only.
+ # Also, Excel supports 1900 and 1904 epochs.
+ year = (cell_contents.timetuple())[0:3]
+ if ((not epoch1904 and year == (1899, 12, 31)) or
+ (epoch1904 and year == (1904, 1, 1))):
+ cell_contents = time(cell_contents.hour,
+ cell_contents.minute,
+ cell_contents.second,
+ cell_contents.microsecond)
+
+ elif cell_typ == XL_CELL_ERROR:
+ cell_contents = np.nan
+ elif cell_typ == XL_CELL_BOOLEAN:
+ cell_contents = bool(cell_contents)
+ elif convert_float and cell_typ == XL_CELL_NUMBER:
+ # GH5394 - Excel 'numbers' are always floats
+ # it's a minimal perf hit and less surprising
+ val = int(cell_contents)
+ if val == cell_contents:
+ cell_contents = val
+ return cell_contents
+
+ data = []
+
+ for i in range(sheet.nrows):
+ row = [_parse_cell(value, typ)
+ for value, typ in zip(sheet.row_values(i),
+ sheet.row_types(i))]
+ data.append(row)
+
+ return data
+
+
 class ExcelFile(object):
  """
  Class for parsing tabular excel sheets into DataFrame objects.