mirror of
https://github.com/PiBrewing/craftbeerpi4.git
synced 2024-12-26 15:34:55 +01:00
214 lines
6.9 KiB
Python
214 lines
6.9 KiB
Python
from typing import List, cast
|
|
|
|
import numpy as np
|
|
|
|
from pandas._typing import FilePathOrBuffer, Scalar
|
|
from pandas.compat._optional import import_optional_dependency
|
|
|
|
import pandas as pd
|
|
|
|
from pandas.io.excel._base import _BaseExcelReader
|
|
|
|
|
|
class _ODFReader(_BaseExcelReader):
|
|
"""
|
|
Read tables out of OpenDocument formatted files.
|
|
|
|
Parameters
|
|
----------
|
|
filepath_or_buffer: string, path to be parsed or
|
|
an open readable stream.
|
|
"""
|
|
|
|
def __init__(self, filepath_or_buffer: FilePathOrBuffer):
|
|
import_optional_dependency("odf")
|
|
super().__init__(filepath_or_buffer)
|
|
|
|
@property
|
|
def _workbook_class(self):
|
|
from odf.opendocument import OpenDocument
|
|
|
|
return OpenDocument
|
|
|
|
def load_workbook(self, filepath_or_buffer: FilePathOrBuffer):
|
|
from odf.opendocument import load
|
|
|
|
return load(filepath_or_buffer)
|
|
|
|
@property
|
|
def empty_value(self) -> str:
|
|
"""Property for compat with other readers."""
|
|
return ""
|
|
|
|
@property
|
|
def sheet_names(self) -> List[str]:
|
|
"""Return a list of sheet names present in the document"""
|
|
from odf.table import Table
|
|
|
|
tables = self.book.getElementsByType(Table)
|
|
return [t.getAttribute("name") for t in tables]
|
|
|
|
def get_sheet_by_index(self, index: int):
|
|
from odf.table import Table
|
|
|
|
tables = self.book.getElementsByType(Table)
|
|
return tables[index]
|
|
|
|
def get_sheet_by_name(self, name: str):
|
|
from odf.table import Table
|
|
|
|
tables = self.book.getElementsByType(Table)
|
|
|
|
for table in tables:
|
|
if table.getAttribute("name") == name:
|
|
return table
|
|
|
|
raise ValueError(f"sheet {name} not found")
|
|
|
|
def get_sheet_data(self, sheet, convert_float: bool) -> List[List[Scalar]]:
|
|
"""
|
|
Parse an ODF Table into a list of lists
|
|
"""
|
|
from odf.table import CoveredTableCell, TableCell, TableRow
|
|
|
|
covered_cell_name = CoveredTableCell().qname
|
|
table_cell_name = TableCell().qname
|
|
cell_names = {covered_cell_name, table_cell_name}
|
|
|
|
sheet_rows = sheet.getElementsByType(TableRow)
|
|
empty_rows = 0
|
|
max_row_len = 0
|
|
|
|
table: List[List[Scalar]] = []
|
|
|
|
for i, sheet_row in enumerate(sheet_rows):
|
|
sheet_cells = [x for x in sheet_row.childNodes if x.qname in cell_names]
|
|
empty_cells = 0
|
|
table_row: List[Scalar] = []
|
|
|
|
for j, sheet_cell in enumerate(sheet_cells):
|
|
if sheet_cell.qname == table_cell_name:
|
|
value = self._get_cell_value(sheet_cell, convert_float)
|
|
else:
|
|
value = self.empty_value
|
|
|
|
column_repeat = self._get_column_repeat(sheet_cell)
|
|
|
|
# Queue up empty values, writing only if content succeeds them
|
|
if value == self.empty_value:
|
|
empty_cells += column_repeat
|
|
else:
|
|
table_row.extend([self.empty_value] * empty_cells)
|
|
empty_cells = 0
|
|
table_row.extend([value] * column_repeat)
|
|
|
|
if max_row_len < len(table_row):
|
|
max_row_len = len(table_row)
|
|
|
|
row_repeat = self._get_row_repeat(sheet_row)
|
|
if self._is_empty_row(sheet_row):
|
|
empty_rows += row_repeat
|
|
else:
|
|
# add blank rows to our table
|
|
table.extend([[self.empty_value]] * empty_rows)
|
|
empty_rows = 0
|
|
for _ in range(row_repeat):
|
|
table.append(table_row)
|
|
|
|
# Make our table square
|
|
for row in table:
|
|
if len(row) < max_row_len:
|
|
row.extend([self.empty_value] * (max_row_len - len(row)))
|
|
|
|
return table
|
|
|
|
def _get_row_repeat(self, row) -> int:
|
|
"""
|
|
Return number of times this row was repeated
|
|
Repeating an empty row appeared to be a common way
|
|
of representing sparse rows in the table.
|
|
"""
|
|
from odf.namespaces import TABLENS
|
|
|
|
return int(row.attributes.get((TABLENS, "number-rows-repeated"), 1))
|
|
|
|
def _get_column_repeat(self, cell) -> int:
|
|
from odf.namespaces import TABLENS
|
|
|
|
return int(cell.attributes.get((TABLENS, "number-columns-repeated"), 1))
|
|
|
|
def _is_empty_row(self, row) -> bool:
|
|
"""
|
|
Helper function to find empty rows
|
|
"""
|
|
for column in row.childNodes:
|
|
if len(column.childNodes) > 0:
|
|
return False
|
|
|
|
return True
|
|
|
|
def _get_cell_value(self, cell, convert_float: bool) -> Scalar:
|
|
from odf.namespaces import OFFICENS
|
|
|
|
if str(cell) == "#N/A":
|
|
return np.nan
|
|
|
|
cell_type = cell.attributes.get((OFFICENS, "value-type"))
|
|
if cell_type == "boolean":
|
|
if str(cell) == "TRUE":
|
|
return True
|
|
return False
|
|
if cell_type is None:
|
|
return self.empty_value
|
|
elif cell_type == "float":
|
|
# GH5394
|
|
cell_value = float(cell.attributes.get((OFFICENS, "value")))
|
|
if convert_float:
|
|
val = int(cell_value)
|
|
if val == cell_value:
|
|
return val
|
|
return cell_value
|
|
elif cell_type == "percentage":
|
|
cell_value = cell.attributes.get((OFFICENS, "value"))
|
|
return float(cell_value)
|
|
elif cell_type == "string":
|
|
return self._get_cell_string_value(cell)
|
|
elif cell_type == "currency":
|
|
cell_value = cell.attributes.get((OFFICENS, "value"))
|
|
return float(cell_value)
|
|
elif cell_type == "date":
|
|
cell_value = cell.attributes.get((OFFICENS, "date-value"))
|
|
return pd.to_datetime(cell_value)
|
|
elif cell_type == "time":
|
|
result = pd.to_datetime(str(cell))
|
|
result = cast(pd.Timestamp, result)
|
|
return result.time()
|
|
else:
|
|
raise ValueError(f"Unrecognized type {cell_type}")
|
|
|
|
def _get_cell_string_value(self, cell) -> str:
|
|
"""
|
|
Find and decode OpenDocument text:s tags that represent
|
|
a run length encoded sequence of space characters.
|
|
"""
|
|
from odf.element import Element
|
|
from odf.namespaces import TEXTNS
|
|
from odf.text import S
|
|
|
|
text_s = S().qname
|
|
|
|
value = []
|
|
|
|
for fragment in cell.childNodes:
|
|
if isinstance(fragment, Element):
|
|
if fragment.qname == text_s:
|
|
spaces = int(fragment.attributes.get((TEXTNS, "c"), 1))
|
|
value.append(" " * spaces)
|
|
else:
|
|
# recursive impl needed in case of nested fragments
|
|
# with multiple spaces
|
|
# https://github.com/pandas-dev/pandas/pull/36175#discussion_r484639704
|
|
value.append(self._get_cell_string_value(fragment))
|
|
else:
|
|
value.append(str(fragment))
|
|
return "".join(value)
|