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pyfastexcel

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This package enables high-performance Excel writing by integrating with the streaming API from the golang package excelize. Users can leverage this functionality without the need to write any Go code, as the entire process can be accomplished through Python.

Features

  • Python and Golang Integration: Seamlessly call Golang built shared libraries from Python.

  • No Golang Code Required: Users can solely rely on Python for Excel file generation, eliminating the need for Golang expertise.

Installation

Install via pip (Recommended)

You can easily install the package via pip

pip install pyfastexcel

Install manually

If you prefer to build the package manually, follow these steps:

  1. Clone the repository:

    git clone https://github.com/Zncl2222/pyfastexcel.git

  2. Go to the project root directory:

    cd pyfastexcel

  3. Install the required golang packages:

    go mod download

  4. Build the Golang shared library using the Makefile:

    make

  5. Install the required python packages:

    pip install -r requirements.txt

    or

    pipenv install

  6. Import the project and start using it!

Requirements

Operating System Version
Linux Ubuntu 18.04 or higher
macOS macOS 13 (x86-64)
Windows Windows 10 or higher

Python Versions

  • Python 3.8 or higher

For earlier versions of Python or other operating systems, compatibility is not guaranteed.

Usage

The index assignment is now avaliable in Workbook and the StreamWriter. Here is the example usage:

from pyfastexcel import Workbook
from pyfastexcel.utils import set_custom_style

from pyfastexcel import CustomStyle


if __name__ == '__main__':
    # Workbook
    wb = Workbook()

    # Set and register CustomStyle
    bold_style = CustomStyle(font_size=15, font_bold=True)
    set_custom_style('bold_style', bold_style)

    ws = wb['Sheet1']
    # Write value with default style
    ws['A1'] = 'A1 value'
    # Write value with custom style
    ws['B1'] = ('B1 value', 'bold_style')

    # Write value in slice with default style
    ws['A2': 'C2'] = [1, 2, 3]
    # Write value in slice with custom style
    ws['A3': 'C3'] = [(1, 'bold_style'), (2, 'bold_style'), (3, 'bold_style')]

    # Write value by row with default style (python index 0 is the index 1 in excel)
    ws[3] = [9, 8, 'go']
    # Write value by row with custom style
    ws[4] = [(9, 'bold_style'), (8, 'bold_style'), ('go', 'bold_style')]

    # Send request to golang lib and create excel
    wb.read_lib_and_create_excel()

    # File path to save
    file_path = 'pyexample_workbook.xlsx'
    wb.save(file_path)

For row-by-row Excel writing, consider using StreamWriter, a subclass of Workbook. This class is optimized for streaming large datasets. Learn more in the StreamWriter documentation.

Explore additional examples in the FullExamples.

Documentation

The documentation is hosted on Read the Docs.

Benchmark

The following result displays the performance comparison between pyfastexcel and openpyxl for writing 50000 rows with 30 columns (Total 1500000 cells). To see more benchmark results, please see the benchmark.

How it Works

Python keeps the existing workbook and (value, style_name) API. With the bundled ABI-v2 library it sends JSON metadata plus MessagePack row frames over a length-aware ctypes boundary; Go decodes one row at a time and writes it with excelize. Older native libraries are detected automatically and continue to use the complete JSON/base64 protocol. The generated XLSX is returned as raw bytes, or written through the compatible direct-file path when save(path) is used.

Row decoding runs concurrently with excelize's row serialization, workbooks with multiple stream sheets are written with one worker per sheet, and the hot Python paths (row_append, the wire encoder) use cached style resolution with tight per-row loops. Two opt-in speedups are available on top of that: append_row/append_rows write whole rows per call (2-3x faster than a per-cell loop, styles may vary per column), and set_zip_compression_level(6) swaps the final DEFLATE stage for klauspost/compress (about 3x faster compression for roughly 20% larger, fully standard files). Without opt-ins the output archives stay byte-for-byte identical to previous releases.

Project links

Data verified by PyPI on Jul 21, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Stable release available (0.1.9)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for Zncl2222 from gravatar.com Zncl2222

Credits

Author/Maintainer: Zncl2222

GitHub Statistics

Data verified by PyPI on Jul 21, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

MIT License (MIT)

Requires

Python >=3.10

Provides Extra

dev docs

Tags

excel xlsx spreadsheet high-performance golang

Classifiers

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Release history Release notifications | RSS feed

This release
Pre-release

0.2.0rc0 This release

3 files

0.1.9

3 files

0.1.8

3 files

0.1.7

2 files

0.1.6

2 files

0.1.5

2 files

0.1.4

2 files

0.1.3

2 files

0.1.2

2 files

0.1.1

2 files

0.1.0

2 files

0.0.10

2 files

Yanked

0.0.9

2 files

Yanked reason: Yank due to the bugs of Selection instance

0.0.8

2 files

0.0.7

2 files

0.0.6

2 files

0.0.5

2 files

0.0.4

2 files

Yanked

0.0.3

2 files

Yanked reason: The style do not rendering correctly in this version

0.0.2

2 files

0.0.1

2 files

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