122 lines
3.4 KiB
Python
122 lines
3.4 KiB
Python
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from __future__ import annotations
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from datetime import (
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date,
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datetime,
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time,
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timedelta,
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)
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from typing import (
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TYPE_CHECKING,
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Any,
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Union,
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)
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from pandas.compat._optional import import_optional_dependency
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from pandas.util._decorators import doc
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import pandas as pd
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from pandas.core.shared_docs import _shared_docs
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from pandas.io.excel._base import BaseExcelReader
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if TYPE_CHECKING:
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from python_calamine import (
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CalamineSheet,
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CalamineWorkbook,
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)
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from pandas._typing import (
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FilePath,
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NaTType,
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ReadBuffer,
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Scalar,
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StorageOptions,
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)
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_CellValue = Union[int, float, str, bool, time, date, datetime, timedelta]
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class CalamineReader(BaseExcelReader["CalamineWorkbook"]):
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@doc(storage_options=_shared_docs["storage_options"])
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def __init__(
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self,
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filepath_or_buffer: FilePath | ReadBuffer[bytes],
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storage_options: StorageOptions | None = None,
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engine_kwargs: dict | None = None,
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) -> None:
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"""
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Reader using calamine engine (xlsx/xls/xlsb/ods).
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Parameters
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----------
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filepath_or_buffer : str, path to be parsed or
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an open readable stream.
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{storage_options}
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engine_kwargs : dict, optional
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Arbitrary keyword arguments passed to excel engine.
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"""
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import_optional_dependency("python_calamine")
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super().__init__(
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filepath_or_buffer,
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storage_options=storage_options,
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engine_kwargs=engine_kwargs,
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)
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@property
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def _workbook_class(self) -> type[CalamineWorkbook]:
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from python_calamine import CalamineWorkbook
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return CalamineWorkbook
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def load_workbook(
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self, filepath_or_buffer: FilePath | ReadBuffer[bytes], engine_kwargs: Any
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) -> CalamineWorkbook:
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from python_calamine import load_workbook
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return load_workbook(filepath_or_buffer, **engine_kwargs)
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@property
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def sheet_names(self) -> list[str]:
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from python_calamine import SheetTypeEnum
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return [
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sheet.name
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for sheet in self.book.sheets_metadata
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if sheet.typ == SheetTypeEnum.WorkSheet
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]
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def get_sheet_by_name(self, name: str) -> CalamineSheet:
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self.raise_if_bad_sheet_by_name(name)
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return self.book.get_sheet_by_name(name)
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def get_sheet_by_index(self, index: int) -> CalamineSheet:
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self.raise_if_bad_sheet_by_index(index)
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return self.book.get_sheet_by_index(index)
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def get_sheet_data(
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self, sheet: CalamineSheet, file_rows_needed: int | None = None
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) -> list[list[Scalar | NaTType | time]]:
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def _convert_cell(value: _CellValue) -> Scalar | NaTType | time:
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if isinstance(value, float):
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val = int(value)
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if val == value:
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return val
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else:
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return value
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elif isinstance(value, date):
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return pd.Timestamp(value)
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elif isinstance(value, timedelta):
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return pd.Timedelta(value)
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elif isinstance(value, time):
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return value
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return value
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rows: list[list[_CellValue]] = sheet.to_python(
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skip_empty_area=False, nrows=file_rows_needed
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)
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data = [[_convert_cell(cell) for cell in row] for row in rows]
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return data
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