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: 2026-07-13 · commit 188c268

cargo bench --features full -p duke-sheets

Group	Case	Library	Time
xlsx_read/100_cells	-	calamine	128.8 µs
xlsx_read/100_cells	-	duke-sheets	245.3 µs
xlsx_read/100_cells	-	umya-spreadsheet	366.7 µs
xlsx_read/10k_cells	-	calamine	7.593 ms
xlsx_read/10k_cells	-	duke-sheets	12.36 ms
xlsx_read/10k_cells	-	umya-spreadsheet	17.33 ms
xlsx_read/1k_cells	-	calamine	804.8 µs
xlsx_read/1k_cells	-	duke-sheets	1.383 ms
xlsx_read/1k_cells	-	umya-spreadsheet	1.98 ms
xlsx_write_serialize/100_cells	-	duke-sheets	516.7 µs
xlsx_write_serialize/100_cells	-	umya-spreadsheet	610.9 µs
xlsx_write_serialize/10k_cells	-	duke-sheets	25.73 ms
xlsx_write_serialize/10k_cells	-	umya-spreadsheet	21.17 ms
xlsx_write_serialize/1k_cells	-	duke-sheets	2.537 ms
xlsx_write_serialize/1k_cells	-	umya-spreadsheet	2.35 ms
xlsx_write_full/100_cells	-	duke-sheets	550 µs
xlsx_write_full/100_cells	-	rust_xlsxwriter	567.3 µs
xlsx_write_full/100_cells	-	umya-spreadsheet	786.2 µs
xlsx_write_full/10k_cells	-	duke-sheets	26.57 ms
xlsx_write_full/10k_cells	-	rust_xlsxwriter	17.43 ms
xlsx_write_full/10k_cells	-	umya-spreadsheet	28.19 ms
xlsx_write_full/1k_cells	-	duke-sheets	2.67 ms
xlsx_write_full/1k_cells	-	rust_xlsxwriter	1.952 ms
xlsx_write_full/1k_cells	-	umya-spreadsheet	3.08 ms
csv_read/100_cells	-	duke-sheets	40.18 µs
csv_read/10k_cells	-	duke-sheets	1.206 ms
csv_read/1k_cells	-	duke-sheets	154.1 µs
csv_write/100_cells	-	duke-sheets	10.78 µs
csv_write/10k_cells	-	duke-sheets	1.189 ms
csv_write/1k_cells	-	duke-sheets	111.7 µs
formula_parse/complex	-	-	19.4 µs
formula_parse/medium	-	-	9.855 µs
formula_parse/simple	-	-	2.999 µs
formula_parse/throughput_1000	-	-	1.06 ms
calculation/linear_chain	100	-	94.34 µs
calculation/linear_chain	500	-	469.5 µs
calculation/linear_chain	1000	-	933.1 µs
calculation/fan_out	26	-	86.49 µs
calculation/fan_out	52	-	189.6 µs
calculation/fan_out	100	-	419.2 µs
calculation/fan_out	200	-	1.057 ms
calculation/cross_sheet	100	-	130.5 µs
calculation/cross_sheet	500	-	590.9 µs
calculation/cross_sheet	1000	-	1.166 ms
calculation/cross_sheet	5000	-	4.943 ms
calculation/mixed	100	-	195.6 µs
calculation/mixed	500	-	841.2 µs
calculation/mixed	1000	-	1.681 ms
calculation/repeated_lookups	-	repeated_lookups	310.1 ms

License

MIT