344 lines
11 KiB
Python
344 lines
11 KiB
Python
import logging
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from io import BytesIO
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from pathlib import Path
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from typing import Dict, Set, Tuple, Union
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from docling_core.types.doc import (
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DoclingDocument,
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DocumentOrigin,
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GroupLabel,
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ImageRef,
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TableCell,
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TableData,
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)
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# from lxml import etree
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from openpyxl import Workbook, load_workbook
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from openpyxl.cell.cell import Cell
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from openpyxl.drawing.image import Image
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from openpyxl.worksheet.worksheet import Worksheet
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from docling.backend.abstract_backend import DeclarativeDocumentBackend
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from docling.datamodel.base_models import InputFormat
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from docling.datamodel.document import InputDocument
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_log = logging.getLogger(__name__)
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from typing import Any, List
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from PIL import Image as PILImage
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from pydantic import BaseModel
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class ExcelCell(BaseModel):
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row: int
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col: int
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text: str
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row_span: int
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col_span: int
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class ExcelTable(BaseModel):
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num_rows: int
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num_cols: int
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data: List[ExcelCell]
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class MsExcelDocumentBackend(DeclarativeDocumentBackend):
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def __init__(self, in_doc: "InputDocument", path_or_stream: Union[BytesIO, Path]):
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super().__init__(in_doc, path_or_stream)
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# Initialise the parents for the hierarchy
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self.max_levels = 10
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self.parents: Dict[int, Any] = {}
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for i in range(-1, self.max_levels):
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self.parents[i] = None
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self.workbook = None
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try:
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if isinstance(self.path_or_stream, BytesIO):
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self.workbook = load_workbook(filename=self.path_or_stream)
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elif isinstance(self.path_or_stream, Path):
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self.workbook = load_workbook(filename=str(self.path_or_stream))
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self.valid = True
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except Exception as e:
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self.valid = False
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raise RuntimeError(
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f"MsPowerpointDocumentBackend could not load document with hash {self.document_hash}"
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) from e
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def is_valid(self) -> bool:
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_log.info(f"valid: {self.valid}")
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return self.valid
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@classmethod
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def supports_pagination(cls) -> bool:
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return True
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def unload(self):
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if isinstance(self.path_or_stream, BytesIO):
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self.path_or_stream.close()
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self.path_or_stream = None
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@classmethod
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def supported_formats(cls) -> Set[InputFormat]:
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return {InputFormat.XLSX}
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def convert(self) -> DoclingDocument:
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# Parses the XLSX into a structured document model.
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origin = DocumentOrigin(
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filename=self.file.name or "file.xlsx",
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mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
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binary_hash=self.document_hash,
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)
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doc = DoclingDocument(name=self.file.stem or "file.xlsx", origin=origin)
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if self.is_valid():
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doc = self._convert_workbook(doc)
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else:
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raise RuntimeError(
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f"Cannot convert doc with {self.document_hash} because the backend failed to init."
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)
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return doc
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def _convert_workbook(self, doc: DoclingDocument) -> DoclingDocument:
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if self.workbook is not None:
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# Iterate over all sheets
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for sheet_name in self.workbook.sheetnames:
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_log.info(f"Processing sheet: {sheet_name}")
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# Access the sheet by name
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sheet = self.workbook[sheet_name]
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self.parents[0] = doc.add_group(
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parent=None,
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label=GroupLabel.SECTION,
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name=f"sheet: {sheet_name}",
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)
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doc = self._convert_sheet(doc, sheet)
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else:
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_log.error("Workbook is not initialized.")
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return doc
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def _convert_sheet(self, doc: DoclingDocument, sheet: Worksheet):
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doc = self._find_tables_in_sheet(doc, sheet)
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doc = self._find_images_in_sheet(doc, sheet)
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return doc
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def _find_tables_in_sheet(self, doc: DoclingDocument, sheet: Worksheet):
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tables = self._find_data_tables(sheet)
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for excel_table in tables:
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num_rows = excel_table.num_rows
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num_cols = excel_table.num_cols
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table_data = TableData(
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num_rows=num_rows,
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num_cols=num_cols,
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table_cells=[],
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)
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for excel_cell in excel_table.data:
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cell = TableCell(
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text=excel_cell.text,
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row_span=excel_cell.row_span,
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col_span=excel_cell.col_span,
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start_row_offset_idx=excel_cell.row,
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end_row_offset_idx=excel_cell.row + excel_cell.row_span,
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start_col_offset_idx=excel_cell.col,
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end_col_offset_idx=excel_cell.col + excel_cell.col_span,
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column_header=excel_cell.row == 0,
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row_header=False,
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)
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table_data.table_cells.append(cell)
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doc.add_table(data=table_data, parent=self.parents[0])
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return doc
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def _find_data_tables(self, sheet: Worksheet) -> List[ExcelTable]:
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"""
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Find all compact rectangular data tables in a sheet.
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"""
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# _log.info("find_data_tables")
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tables = [] # List to store found tables
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visited: set[Tuple[int, int]] = set() # Track already visited cells
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# Iterate over all cells in the sheet
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for ri, row in enumerate(sheet.iter_rows(values_only=False)):
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for rj, cell in enumerate(row):
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# Skip empty or already visited cells
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if cell.value is None or (ri, rj) in visited:
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continue
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# If the cell starts a new table, find its bounds
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table_bounds, visited_cells = self._find_table_bounds(
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sheet, ri, rj, visited
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)
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visited.update(visited_cells) # Mark these cells as visited
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tables.append(table_bounds)
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return tables
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def _find_table_bounds(
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self,
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sheet: Worksheet,
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start_row: int,
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start_col: int,
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visited: set[Tuple[int, int]],
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):
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"""
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Determine the bounds of a compact rectangular table.
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Returns:
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- A dictionary with the bounds and data.
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- A set of visited cell coordinates.
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"""
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_log.info("find_table_bounds")
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max_row = self._find_table_bottom(sheet, start_row, start_col)
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max_col = self._find_table_right(sheet, start_row, start_col)
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# Collect the data within the bounds
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data = []
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visited_cells = set()
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for ri in range(start_row, max_row + 1):
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for rj in range(start_col, max_col + 1):
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cell = sheet.cell(row=ri + 1, column=rj + 1) # 1-based indexing
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# Check if the cell belongs to a merged range
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row_span = 1
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col_span = 1
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# _log.info(sheet.merged_cells.ranges)
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for merged_range in sheet.merged_cells.ranges:
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if (
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merged_range.min_row <= ri + 1
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and ri + 1 <= merged_range.max_row
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and merged_range.min_col <= rj + 1
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and rj + 1 <= merged_range.max_col
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):
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row_span = merged_range.max_row - merged_range.min_row + 1
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col_span = merged_range.max_col - merged_range.min_col + 1
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break
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if (ri, rj) not in visited_cells:
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data.append(
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ExcelCell(
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row=ri - start_row,
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col=rj - start_col,
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text=str(cell.value),
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row_span=row_span,
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col_span=col_span,
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)
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)
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# _log.info(f"cell: {ri}, {rj} -> {ri - start_row}, {rj - start_col}, {row_span}, {col_span}: {str(cell.value)}")
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# Mark all cells in the span as visited
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for span_row in range(ri, ri + row_span):
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for span_col in range(rj, rj + col_span):
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visited_cells.add((span_row, span_col))
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return (
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ExcelTable(
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num_rows=max_row + 1 - start_row,
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num_cols=max_col + 1 - start_col,
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data=data,
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),
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visited_cells,
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)
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def _find_table_bottom(self, sheet: Worksheet, start_row: int, start_col: int):
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"""Function to find the bottom boundary of the table"""
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max_row = start_row
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while max_row < sheet.max_row - 1:
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# Get the cell value or check if it is part of a merged cell
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cell = sheet.cell(row=max_row + 2, column=start_col + 1)
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# Check if the cell is part of a merged range
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merged_range = next(
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(mr for mr in sheet.merged_cells.ranges if cell.coordinate in mr),
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None,
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)
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if cell.value is None and not merged_range:
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break # Stop if the cell is empty and not merged
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# Expand max_row to include the merged range if applicable
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if merged_range:
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max_row = max(max_row, merged_range.max_row - 1)
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else:
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max_row += 1
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return max_row
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def _find_table_right(self, sheet: Worksheet, start_row: int, start_col: int):
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"""Function to find the right boundary of the table"""
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max_col = start_col
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while max_col < sheet.max_column - 1:
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# Get the cell value or check if it is part of a merged cell
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cell = sheet.cell(row=start_row + 1, column=max_col + 2)
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# Check if the cell is part of a merged range
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merged_range = next(
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(mr for mr in sheet.merged_cells.ranges if cell.coordinate in mr),
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None,
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)
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if cell.value is None and not merged_range:
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break # Stop if the cell is empty and not merged
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# Expand max_col to include the merged range if applicable
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if merged_range:
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max_col = max(max_col, merged_range.max_col - 1)
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else:
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max_col += 1
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return max_col
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def _find_images_in_sheet(
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self, doc: DoclingDocument, sheet: Worksheet
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) -> DoclingDocument:
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# Iterate over byte images in the sheet
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for idx, image in enumerate(sheet._images): # type: ignore
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try:
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pil_image = PILImage.open(image.ref)
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doc.add_picture(
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parent=self.parents[0],
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image=ImageRef.from_pil(image=pil_image, dpi=72),
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caption=None,
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)
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except:
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_log.error("could not extract the image from excel sheets")
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return doc
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