craftbeerpi4-pione/venv/lib/python3.8/site-packages/pandas/io/excel/_pyxlsb.py

75 lines
2.5 KiB
Python

from typing import List
from pandas._typing import FilePathOrBuffer, Scalar, StorageOptions
from pandas.compat._optional import import_optional_dependency
from pandas.io.excel._base import BaseExcelReader
class PyxlsbReader(BaseExcelReader):
def __init__(
self,
filepath_or_buffer: FilePathOrBuffer,
storage_options: StorageOptions = None,
):
"""
Reader using pyxlsb engine.
Parameters
----------
filepath_or_buffer : str, path object, or Workbook
Object to be parsed.
storage_options : dict, optional
passed to fsspec for appropriate URLs (see ``_get_filepath_or_buffer``)
"""
import_optional_dependency("pyxlsb")
# This will call load_workbook on the filepath or buffer
# And set the result to the book-attribute
super().__init__(filepath_or_buffer, storage_options=storage_options)
@property
def _workbook_class(self):
from pyxlsb import Workbook
return Workbook
def load_workbook(self, filepath_or_buffer: FilePathOrBuffer):
from pyxlsb import open_workbook
# TODO: hack in buffer capability
# This might need some modifications to the Pyxlsb library
# Actual work for opening it is in xlsbpackage.py, line 20-ish
return open_workbook(filepath_or_buffer)
@property
def sheet_names(self) -> List[str]:
return self.book.sheets
def get_sheet_by_name(self, name: str):
return self.book.get_sheet(name)
def get_sheet_by_index(self, index: int):
# pyxlsb sheets are indexed from 1 onwards
# There's a fix for this in the source, but the pypi package doesn't have it
return self.book.get_sheet(index + 1)
def _convert_cell(self, cell, convert_float: bool) -> Scalar:
# TODO: there is no way to distinguish between floats and datetimes in pyxlsb
# This means that there is no way to read datetime types from an xlsb file yet
if cell.v is None:
return "" # Prevents non-named columns from not showing up as Unnamed: i
if isinstance(cell.v, float) and convert_float:
val = int(cell.v)
if val == cell.v:
return val
else:
return float(cell.v)
return cell.v
def get_sheet_data(self, sheet, convert_float: bool) -> List[List[Scalar]]:
return [
[self._convert_cell(c, convert_float) for c in r]
for r in sheet.rows(sparse=False)
]