Using Aspose.Cells for Python via .NET as a Pandas Excel Engine

Why Use Aspose.Cells for Python via .NET?

Aspose.Cells offers:

  • Advanced Excel support (formulas, charts, formatting, merged cells, etc.)
  • Support for multiple formats: .xls, .xlsx, .xlsb, .ods, .csv, .html
  • Better accuracy for complex spreadsheets compared to openpyxl or xlrd

Prerequisites

  • Install a C compiler
  • Here, we use the Windows platform as an example for explanation.If you have installed Visual Studio 2022 on your Windows system, you can open the x64 Native Tools Command Prompt for VS 2022 and run the cl command to check the version of the C++ compiler. Make sure the compiler version is 19.3x or higher before proceeding with the following build steps.
  • Make sure that you have cloned the repository
git clone https://github.com/pandas-dev/pandas.git
  • cd to the pandas source directory you just created with the clone command

Step 1: Create an isolated environment

# Set up virtual environment
python -m venv .venv
.\.venv\Scripts\activate      # on Windows
# source .venv/bin/activate  # on Linux/macOS

# Install aspose-cells-python
pip install aspose-cells-python
# Install the build dependencies
python -m pip install -r requirements-dev.txt

Step 2: Create Aspose engine adapter

Create a new file:
pandas/io/excel/_asposecells.py
Add the following content:

# pandas/io/excel/_asposecells.py
import pandas as pd
from aspose.cells import Workbook

class AsposeCellsExcelReader:
    def __init__(self, filepath_or_buffer, sheet_name=0, header=0, **kwargs):
        self.filepath = filepath_or_buffer
        self.sheet_name = sheet_name
        self.header = header
 
    def parse(self, sheet_name, header=0, **kwargs):
        wb = Workbook(self.filepath)
        worksheet = wb.worksheets[sheet_name] if isinstance(sheet_name, int) else wb.worksheets.get(sheet_name)
        # Get the Cells collection from the worksheet
        cells = worksheet.cells

        # Calculate number of columns: max_col - min_col (both are 0-based)
        col_count = cells.max_data_column - cells.min_data_column

        # Initialize a list to hold all the row data
        output_data = []

        # Get the index of the first row that contains data
        first_data_row_Index = cells.min_data_row

        # Iterate through all the rows
        for row in cells.rows:
            if row is None:
                continue  # Skip if the row is not initialized

            row_data = []
            for cell in row:
                row_data.append(cell.value)
            output_data.append(row_data)

        # Prepare the column names
        columns = []
        if header is not None:
            row = cells.rows[first_data_row_Index]
            for cell in row:
                columns.append(cell.value)
            # Remove the header row from the data
            output_data = output_data[1:]
        else:
            # If no header, generate default column names like "Unnamed: 0", "Unnamed: 1", ...
            columns = [f"Unnamed: {i}" for i in range(col_count + 1)]

        # Convert the data into a pandas DataFrame
        return pd.DataFrame(output_data, columns=columns)
  
    def close(self):
        pass  # Required by pandas API

Step 3: Register the Aspose Engine in Pandas

In pandas/io/excel/_base.py, find the class ExcelFile class, and add Add the following import line after the existing from pandas.io.excel._xlrd import XlrdReader:

from pandas.io.excel._asposecells import AsposeCellsExcelReader

and then add the following code in _engines: Mapping[str, Any]

_engines: Mapping[str, Any] = {
    ...
    "asposecells": AsposeCellsExcelReader,
}

Step 4: Build and install pandas

# build and install pandas
python -m pip install -ve . --no-build-isolation

✅ If you encounter a compilation error during the build process, such as:Cython.Compiler.Errors.InternalError: Internal compiler error: ‘free_threading_config.pxi’ not found,you can try running the following command and then compile again.

# remove all untracked files, directories, and ignored files from the working directory.
git clean -xfd

Step 5: Use the Engine

You can use the following Excel file for testing.

import pandas as pd
# asposecells
df = pd.read_excel("test.xlsx", engine="asposecells", sheet_name=0, header=0)
# print and check DataFrame
print(df)

After running it, you should get a result like this.

todo:image_alt_text

Notes

  • For production use, a valid Aspose.Cells for Python via .NET license is required.
  • This approach is ideal for testing or local enhancement of read_excel behavior.
  • You can also use Aspose.Cells for Python via .NET directly outside of pandas if desired.

See Also

Convert Pandas DataFrame to Excel