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112 lines
3.6 KiB
112 lines
3.6 KiB
from datetime import time
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import numpy as np
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from pandas._typing import StorageOptions
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from pandas.compat._optional import import_optional_dependency
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from pandas.io.excel._base import BaseExcelReader
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class XlrdReader(BaseExcelReader):
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def __init__(self, filepath_or_buffer, storage_options: StorageOptions = None):
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"""
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Reader using xlrd engine.
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Parameters
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----------
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filepath_or_buffer : str, path object or Workbook
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Object to be parsed.
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storage_options : dict, optional
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passed to fsspec for appropriate URLs (see ``_get_filepath_or_buffer``)
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"""
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err_msg = "Install xlrd >= 1.0.0 for Excel support"
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import_optional_dependency("xlrd", extra=err_msg)
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super().__init__(filepath_or_buffer, storage_options=storage_options)
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@property
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def _workbook_class(self):
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from xlrd import Book
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return Book
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def load_workbook(self, filepath_or_buffer):
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from xlrd import open_workbook
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if hasattr(filepath_or_buffer, "read"):
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data = filepath_or_buffer.read()
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return open_workbook(file_contents=data)
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else:
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return open_workbook(filepath_or_buffer)
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@property
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def sheet_names(self):
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return self.book.sheet_names()
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def get_sheet_by_name(self, name):
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self.raise_if_bad_sheet_by_name(name)
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return self.book.sheet_by_name(name)
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def get_sheet_by_index(self, index):
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self.raise_if_bad_sheet_by_index(index)
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return self.book.sheet_by_index(index)
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def get_sheet_data(self, sheet, convert_float):
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from xlrd import (
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XL_CELL_BOOLEAN,
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XL_CELL_DATE,
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XL_CELL_ERROR,
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XL_CELL_NUMBER,
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xldate,
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)
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epoch1904 = self.book.datemode
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def _parse_cell(cell_contents, cell_typ):
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"""
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converts the contents of the cell into a pandas appropriate object
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"""
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if cell_typ == XL_CELL_DATE:
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# Use the newer xlrd datetime handling.
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try:
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cell_contents = xldate.xldate_as_datetime(cell_contents, epoch1904)
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except OverflowError:
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return cell_contents
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# Excel doesn't distinguish between dates and time,
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# so we treat dates on the epoch as times only.
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# Also, Excel supports 1900 and 1904 epochs.
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year = (cell_contents.timetuple())[0:3]
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if (not epoch1904 and year == (1899, 12, 31)) or (
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epoch1904 and year == (1904, 1, 1)
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):
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cell_contents = time(
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cell_contents.hour,
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cell_contents.minute,
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cell_contents.second,
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cell_contents.microsecond,
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)
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elif cell_typ == XL_CELL_ERROR:
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cell_contents = np.nan
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elif cell_typ == XL_CELL_BOOLEAN:
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cell_contents = bool(cell_contents)
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elif convert_float and cell_typ == XL_CELL_NUMBER:
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# GH5394 - Excel 'numbers' are always floats
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# it's a minimal perf hit and less surprising
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val = int(cell_contents)
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if val == cell_contents:
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cell_contents = val
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return cell_contents
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data = []
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for i in range(sheet.nrows):
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row = [
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_parse_cell(value, typ)
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for value, typ in zip(sheet.row_values(i), sheet.row_types(i))
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]
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data.append(row)
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return data
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