perf: Optimize document extraction for complex table files

[shaohuzhang1]

perf: Optimize document extraction for complex table files

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[shaohuzhang1]

There are several areas where refactoring can be beneficial to improve readability, maintainability, and efficiency of the provided code:

1. Avoid Repeated for loop Headers:
   The first couple of loops have similar header structures. Consider using a function or class method instead.

2. Optimize Merged Cells Handling:
   The merging process can be simplified by directly assigning cells based on their coordinates rather than iterating through all rows and columns repeatedly.

3. Refactor Data Processing Logic:
   Separate concerns between loading sheets and processing content into distinct methods for better clarity and modularity.

Here's a revised version with these improvements:

class ExcelHandler:
    def __init__(self):
        pass

    def _get_buffer(self, file):
        """Return buffer bytes from provided file."""
        ...

    def support(self, file, get_buffer):
        """Check support for specified file type here."""
        ...

    def _load_workbook(self, data_bytes):
        """Load workbook from byte data."""
        ...

    def _find_sheet_name(self, sheet_names, default=None):
        """Find desired sheet name in list; otherwise use default name."""
        ...

    def fill_merged_cells(self, sheet, image_dict):
        """
        Fill merged cells in worksheet and map cell keys to dictionary.
        Returns a list of dictionaries where each dict represents a row containing cell titles mapped to text/images.
        :param sheet:
        :param image_dict:
        :return:
        """
        data = []

        # Collect headers from non-empty topmost row
        headers = next((cell.value for row in sheet[:1] for cell in row if cell), [])

        # Process content starting from the second row
        for row in sheet.iter_rows(min_row=2):
            col_idx_to_key = {}
            row_data = {}

            for col_idx, (cell, header) in enumerate(zip(row, headers)):
                if cell.value is None:
                    # If empty cell within spanned area get corresponding header value
                    header_span_start = sheet._current_rowspan.get(cell.row, 0)
                    header_value = headers[header_span_start - 1]
                    col_idx_to_key[col_idx] = header_value
                    # Handle images similarly inside spanning regions
                else:
                    col_idx_to_key[col_idx] = cell.value

                formatted_cell_value = self._format_cell_value(cell.value, image_dict)
                row_data[col_idx_to_key[col_idx]] = formatted_cell_value

            data.append(row_data)

        # Assign final values across spans
        for row_data in data:
            for i in range(len(data[data.index(row_data)])):
                val = row_data[i]
                if isinstance(val, str) and ',' in val:  # Assuming comma delimiter in multi-value string
                    parts = val.split(',')
                    new_val_dict = {part.strip(): '' for part in parts}
                    del row_data[i]
                    row_data.extend(new_val_dict.items())

        return data

    def _format_cell_value(self, cell_value, image_dict):
        if cell_value is not None:
            image = image_dict.get(cell_value, None)
            if image is not None:
                cell_value = f'![](/api/image/{image.id})'
        return cell_value

    def handle(self, file, get_buffer, save_image):
        """
        Handles handling logic including getting sheet names, processing worksheets, etc.
        :param file:
        :param get_buffer:
        :param save_image:
        :return:
        """
        data_bytes = get_buffer(file)
        wb = self._load_workbook(data_bytes)
        result = []

        sheet_name = self._find_sheet_name(wb.sheetnames)

        while True:
            sheet = wb[sheet_name]

            contents = self.fill_merged_cells(sheet, {})

            paragraphs = []
            for row in contents:
                paragraph_content = " ; ".join(["{} : {}".format(key, str(value).strip()) for key, value in row.items()]).rstrip()
                paragraphs.append({"title": "", "content": paragraph_content})

            result.append({"name": sheet_name, "paragraphs": paragraphs})
            sheet_name = next(iter(set(wb.sheetnames) - set(result[-1]["name"]), False))

        return result

    def get_content(self, file, save_image):
        """
        Main processing handler responsible for fetching and parsing content out of an Excel document/file object,
        then returning it in markdown format.
        This will involve creating the necessary helper functions that read/load different excel files & return appropriate output formats (JSON, YAML, CSV, etc.)
        :param file:
        :param save_image:
        :return:
        """
        data_bytes = self._get_buffer(file)
        wb = self._load_workbook(data_bytes)

        result = []
        for name in [sheet.title for sheet in wb.worksheets]:
            sheet = wb[name]

            content = self.handle(sheet.name, self._get_buffer(sheet.read()), save_image)
            result.append(content)

        return {'data': [{'type': 'excel', 'payload': result}],
               'response_type': 'application/json'}

# Example usage:
# handler_instance = ExcelHandler()
# response = handler_instance.get_content("some_excel_file.xlsx", lambda x: x)

Key Changes Made:

• Extracted Helper Methods: Split off common operations like finding the default sheet name and formatting cell values into separate methods (_find_sheet_name and _format_cell_value, respectively).
• Merging Improvement: Reduced redundant merging checks by storing rowspan information and directly applying changes during row iteration.
• Data Structure Optimization: Simplified and structured data collection from merged cells, ensuring consistent handling across various scenarios.

These changes make the code more modular, easier to understand, and less prone to errors as complex operations become isolated tasks.