Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.9/dist-packages/pandas/io/excel/_xlrd.py: 31%

1from __future__ import annotations 

2 

3from datetime import time 

4import math 

5from typing import TYPE_CHECKING 

6 

7import numpy as np 

8 

9from pandas.compat._optional import import_optional_dependency 

10from pandas.util._decorators import doc 

11 

12from pandas.core.shared_docs import _shared_docs 

13 

14from pandas.io.excel._base import BaseExcelReader 

15 

16if TYPE_CHECKING: 

17 from xlrd import Book 

18 

19 from pandas._typing import ( 

20 Scalar, 

21 StorageOptions, 

22 ) 

23 

24 

25class XlrdReader(BaseExcelReader["Book"]): 

26 @doc(storage_options=_shared_docs["storage_options"]) 

27 def __init__( 

28 self, 

29 filepath_or_buffer, 

30 storage_options: StorageOptions | None = None, 

31 engine_kwargs: dict | None = None, 

32 ) -> None: 

33 """ 

34 Reader using xlrd engine. 

35 

36 Parameters 

37 ---------- 

38 filepath_or_buffer : str, path object or Workbook 

39 Object to be parsed. 

40 {storage_options} 

41 engine_kwargs : dict, optional 

42 Arbitrary keyword arguments passed to excel engine. 

43 """ 

44 err_msg = "Install xlrd >= 2.0.1 for xls Excel support" 

45 import_optional_dependency("xlrd", extra=err_msg) 

46 super().__init__( 

47 filepath_or_buffer, 

48 storage_options=storage_options, 

49 engine_kwargs=engine_kwargs, 

50 ) 

51 

52 @property 

53 def _workbook_class(self) -> type[Book]: 

54 from xlrd import Book 

55 

56 return Book 

57 

58 def load_workbook(self, filepath_or_buffer, engine_kwargs) -> Book: 

59 from xlrd import open_workbook 

60 

61 if hasattr(filepath_or_buffer, "read"): 

62 data = filepath_or_buffer.read() 

63 return open_workbook(file_contents=data, **engine_kwargs) 

64 else: 

65 return open_workbook(filepath_or_buffer, **engine_kwargs) 

66 

67 @property 

68 def sheet_names(self): 

69 return self.book.sheet_names() 

70 

71 def get_sheet_by_name(self, name): 

72 self.raise_if_bad_sheet_by_name(name) 

73 return self.book.sheet_by_name(name) 

74 

75 def get_sheet_by_index(self, index): 

76 self.raise_if_bad_sheet_by_index(index) 

77 return self.book.sheet_by_index(index) 

78 

79 def get_sheet_data( 

80 self, sheet, file_rows_needed: int | None = None 

81 ) -> list[list[Scalar]]: 

82 from xlrd import ( 

83 XL_CELL_BOOLEAN, 

84 XL_CELL_DATE, 

85 XL_CELL_ERROR, 

86 XL_CELL_NUMBER, 

87 xldate, 

88 ) 

89 

90 epoch1904 = self.book.datemode 

91 

92 def _parse_cell(cell_contents, cell_typ): 

93 """ 

94 converts the contents of the cell into a pandas appropriate object 

95 """ 

96 if cell_typ == XL_CELL_DATE: 

97 # Use the newer xlrd datetime handling. 

98 try: 

99 cell_contents = xldate.xldate_as_datetime(cell_contents, epoch1904) 

100 except OverflowError: 

101 return cell_contents 

102 

103 # Excel doesn't distinguish between dates and time, 

104 # so we treat dates on the epoch as times only. 

105 # Also, Excel supports 1900 and 1904 epochs. 

106 year = (cell_contents.timetuple())[0:3] 

107 if (not epoch1904 and year == (1899, 12, 31)) or ( 

108 epoch1904 and year == (1904, 1, 1) 

109 ): 

110 cell_contents = time( 

111 cell_contents.hour, 

112 cell_contents.minute, 

113 cell_contents.second, 

114 cell_contents.microsecond, 

115 ) 

116 

117 elif cell_typ == XL_CELL_ERROR: 

118 cell_contents = np.nan 

119 elif cell_typ == XL_CELL_BOOLEAN: 

120 cell_contents = bool(cell_contents) 

121 elif cell_typ == XL_CELL_NUMBER: 

122 # GH5394 - Excel 'numbers' are always floats 

123 # it's a minimal perf hit and less surprising 

124 if math.isfinite(cell_contents): 

125 # GH54564 - don't attempt to convert NaN/Inf 

126 val = int(cell_contents) 

127 if val == cell_contents: 

128 cell_contents = val 

129 return cell_contents 

130 

131 data = [] 

132 

133 nrows = sheet.nrows 

134 if file_rows_needed is not None: 

135 nrows = min(nrows, file_rows_needed) 

136 for i in range(nrows): 

137 row = [ 

138 _parse_cell(value, typ) 

139 for value, typ in zip(sheet.row_values(i), sheet.row_types(i)) 

140 ] 

141 data.append(row) 

142 

143 return data