Duke Sheets

A library for reading, writing, manipulating, and evaluating Excel spreadsheets.

Includes bindings for:

• Python
• NodeJS
• WebAssembly
• Rust

Duke Sheets includes an extensive test suite:

• Formula tests covering Excel's documentation cases
• Compatibility & parity tests against both LibreOffice and Excel
• Fuzz testing
• Performance benchmarks
• Corpus testing on real-world spreadsheets

Duke Sheets has a multithreaded formula engine which can evaluate millions of formulas per second, and has been profiled against some of the most complex financial spreadsheets in the world.

Supported file formats: .xlsx, .xlsm, .xltx, .xltm, .xlsb, .xls, .csv

Duke Sheets supports all formulas, except ones that don't make sense such as CALL and REGISTER.ID. Even formulas such as WEBSERVICE are supported. Most workbook metadata is also supported such as formatting, images, charts, etc. Some advanced features are still in progress (e.g., pivot tables).

Warning

Duke Sheets is in alpha. Its API is not yet stable.

Feature Coverage

See FEATURES.md for the per-feature support matrix.

Node.js / TypeScript

npm install @dukelib/sheets

import { Workbook } from '@dukelib/sheets';

const wb = new Workbook();
const sheet = wb.getSheet(0);

sheet.setCell('A1', 10);
sheet.setCell('A2', 20);
sheet.setFormula('A3', '=A1+A2');
sheet.setCellStyle('A1', {
  font: { bold: true, color: { hex: 'FFFFFF' } },
  fill: { fillType: 'solid', color: { hex: '1F4E79' } },
});

wb.calculate();
console.log(sheet.getCalculatedValue('A3').asNumber()); // 30

wb.save('output.xlsx');

Open existing files from disk, bytes, or CSV strings:

const wb = Workbook.open('input.xlsx');
const wb2 = Workbook.fromBytes(buffer);
const wb3 = Workbook.fromCsvString('a,b,c\n1,2,3');

Async versions run on separate threads so the event loop stays free:

import { openAsync } from '@dukelib/sheets';

const wb = await openAsync('large-file.xlsx');
await wb.calculateAsync();
await wb.saveAsync('output.xlsx');

50+ accessors for styles, comments, hyperlinks, tables, conditional formatting, data validations, merged regions, page setup, and more.

Python

pip install duke-sheets

import duke_sheets

wb = duke_sheets.Workbook()
sheet = wb.get_sheet(0)

sheet.set_cell("A1", 10)
sheet.set_cell("A2", 20)
sheet.set_formula("A3", "=A1+A2")
sheet.set_cell_style("A1", {
    "font": {"bold": True, "color": {"hex": "FFFFFF"}},
    "fill": {"fill_type": "solid", "color": {"hex": "1F4E79"}},
})

wb.calculate()
print(sheet.get_calculated_value("A3").as_number())  # 30.0

wb.save("output.xlsx")

Open existing files:

wb = duke_sheets.Workbook.open("input.xlsx")
wb = duke_sheets.Workbook.from_bytes(data)
wb = duke_sheets.Workbook.from_csv_string("a,b,c\n1,2,3")

Same 50+ accessors as the Node.js API: cell styles, formatted values, comments, hyperlinks, tables, freeze panes, page setup, etc.

WebAssembly

npm install @dukelib/sheets-wasm

import { Workbook } from '@dukelib/sheets-wasm';

const wb = new Workbook();
const sheet = wb.getSheet(0);

sheet.setCell('A1', 10);
sheet.setCell('A2', 20);
sheet.setFormula('A3', '=A1+A2');

const stats = wb.calculate();
console.log(sheet.getCalculatedValue('A3').asNumber()); // 30

Load files from bytes or CSV:

const wb = Workbook.fromBytes(uint8Array);
const wb2 = Workbook.loadCsvString('a,b,c\n1,2,3');

// Export back out
const xlsxBytes = wb.saveXlsxBytes();   // Uint8Array
const csvString = wb.saveCsvString();    // string

Rust

Add to your Cargo.toml:

[dependencies]
duke-sheets = { git = "https://github.com/guseggert/duke-sheets.git", features = ["full"] }

use duke_sheets::prelude::*;

fn main() -> Result<()> {
    let mut workbook = Workbook::new();

    let sheet = workbook.worksheet_mut(0).unwrap();
    sheet.set_name("Sales Data")?;

    sheet.set_cell_value("A1", "Product")?;
    sheet.set_cell_value("B1", "Revenue")?;
    sheet.set_cell_value("A2", "Widget")?;
    sheet.set_cell_value("B2", 1500.0)?;

    sheet.set_cell_formula("B5", "=SUM(B2:B4)")?;

    let header_style = Style::new().bold(true);
    sheet.set_cell_style("A1", &header_style)?;
    sheet.set_cell_style("B1", &header_style)?;

    workbook.save("sales.xlsx")?;

    Ok(())
}

Benchmarks

Last updated: 2026-07-27 · commit 06f338f

cargo bench --features full -p duke-sheets

Group	Case	Library	Time
xlsx_read/100_cells	-	calamine	105.8 µs
xlsx_read/100_cells	-	duke-sheets	293 µs
xlsx_read/100_cells	-	umya-spreadsheet	329.4 µs
xlsx_read/10k_cells	-	calamine	6.058 ms
xlsx_read/10k_cells	-	duke-sheets	10.73 ms
xlsx_read/10k_cells	-	umya-spreadsheet	14.69 ms
xlsx_read/1k_cells	-	calamine	651.5 µs
xlsx_read/1k_cells	-	duke-sheets	1.276 ms
xlsx_read/1k_cells	-	umya-spreadsheet	1.665 ms
xlsx_write_serialize/100_cells	-	duke-sheets	406.2 µs
xlsx_write_serialize/100_cells	-	umya-spreadsheet	462 µs
xlsx_write_serialize/10k_cells	-	duke-sheets	20.91 ms
xlsx_write_serialize/10k_cells	-	umya-spreadsheet	17.96 ms
xlsx_write_serialize/1k_cells	-	duke-sheets	1.968 ms
xlsx_write_serialize/1k_cells	-	umya-spreadsheet	1.867 ms
xlsx_write_full/100_cells	-	duke-sheets	426.3 µs
xlsx_write_full/100_cells	-	rust_xlsxwriter	449.3 µs
xlsx_write_full/100_cells	-	umya-spreadsheet	579.7 µs
xlsx_write_full/10k_cells	-	duke-sheets	21.77 ms
xlsx_write_full/10k_cells	-	rust_xlsxwriter	14.05 ms
xlsx_write_full/10k_cells	-	umya-spreadsheet	23.99 ms
xlsx_write_full/1k_cells	-	duke-sheets	2.075 ms
xlsx_write_full/1k_cells	-	rust_xlsxwriter	1.469 ms
xlsx_write_full/1k_cells	-	umya-spreadsheet	2.472 ms
csv_read/100_cells	-	duke-sheets	34.2 µs
csv_read/10k_cells	-	duke-sheets	1.045 ms
csv_read/1k_cells	-	duke-sheets	134.6 µs
csv_write/100_cells	-	duke-sheets	9.552 µs
csv_write/10k_cells	-	duke-sheets	1.073 ms
csv_write/1k_cells	-	duke-sheets	95.94 µs
formula_parse/complex	-	-	17.38 µs
formula_parse/medium	-	-	8.672 µs
formula_parse/simple	-	-	2.461 µs
formula_parse/throughput_1000	-	-	934.4 µs
calculation/linear_chain	100	-	78.71 µs
calculation/linear_chain	500	-	393.7 µs
calculation/linear_chain	1000	-	792.8 µs
calculation/fan_out	26	-	72.34 µs
calculation/fan_out	52	-	159.3 µs
calculation/fan_out	100	-	351.2 µs
calculation/fan_out	200	-	875.6 µs
calculation/cross_sheet	100	-	109.2 µs
calculation/cross_sheet	500	-	497.2 µs
calculation/cross_sheet	1000	-	991.8 µs
calculation/cross_sheet	5000	-	4.244 ms
calculation/mixed	100	-	162.2 µs
calculation/mixed	500	-	712.2 µs
calculation/mixed	1000	-	1.412 ms
calculation/repeated_lookups	-	repeated_lookups	265.2 ms

License

MIT