Fast cartesian product.
Retrieves every possible combination between several arrays (cartesian product).
Fastest available library in JavaScript.
When producing millions of combinations or combining hundreds of arrays,
big-cartesian should be used
instead.
Testimonials
We are now using this library for ourworldindata.org and have seen an almost 50-fold performance increase from the naive method we used before!
@MarcelGerber
Example
import fastCartesian from 'fast-cartesian'
console.log(
  fastCartesian([
    ['red', 'blue'],
    ['circle', 'square'],
  ]),
)
// [
//   [ 'red', 'circle' ],
//   [ 'red', 'square' ],
//   [ 'blue', 'circle' ],
//   [ 'blue', 'square' ]
// ]
// Return initial indexes
console.log(
  fastCartesian(
    [
      ['red', 'blue'],
      ['circle', 'square'],
    ].map(Object.entries),
  ),
)
// [
//   [ [ '0', 'red' ], [ '0', 'circle' ] ],
//   [ [ '0', 'red' ], [ '1', 'square' ] ],
//   [ [ '1', 'blue' ], [ '0', 'circle' ] ],
//   [ [ '1', 'blue' ], [ '1', 'square' ] ]
// ]Install
npm install fast-cartesianThis package works in both Node.js >=18.18.0 and browsers.
This is an ES module. It must be loaded using
an import or import() statement,
not require(). If TypeScript is used, it must be configured to
output ES modules,
not CommonJS.
API
fastCartesian(inputs)
inputs: Array<Array>\
Return value: Array<Array>
Returns a two-dimensional Array where each row is a combination of inputs.
Benchmarks
The following benchmarks compare the performance of this
library against alternatives
(big-cartesian,
cx-product,
cartesian-product,
fast-cartesian-product,
power-cartesian-product,
cartesian and
lodash.product).
## fast-cartesian ######################
1 array                           1.22ms
2 arrays                          1.82ms
4 arrays                          3.12ms
8 arrays                          1.87ms
16 arrays                         4.82ms
## cxproduct ###########################
1 array                           1.91ms
2 arrays                          3.47ms
4 arrays                          3.62ms
8 arrays                          2.39ms
16 arrays                         5.05ms
## cartesian-product ###################
1 array                           4.61ms
2 arrays                          2.92ms
4 arrays                         11.80ms
8 arrays                         14.78ms
16 arrays                        21.00ms
## big-cartesian #######################
1 array                           7.21ms
2 arrays                          6.68ms
4 arrays                          8.53ms
8 arrays                          7.80ms
16 arrays                        18.30ms
## power-cartesian-product #############
1 array                           6.84ms
2 arrays                          8.54ms
4 arrays                         12.35ms
8 arrays                         11.78ms
16 arrays                        18.98ms
## cartesian ###########################
1 array                           3.44ms
2 arrays                         11.12ms
4 arrays                         13.27ms
8 arrays                         16.11ms
16 arrays                        22.90ms
## fast-cartesian-product ##############
1 array                          23.04ms
2 arrays                         24.11ms
4 arrays                         30.46ms
8 arrays                         45.65ms
16 arrays                        65.12ms
## lodash.product ######################
1 array                          36.51ms
2 arrays                         37.89ms
4 arrays                         41.71ms
8 arrays                         52.72ms
16 arrays                        80.84msSupport
For any question, don't hesitate to submit an issue on GitHub.
Everyone is welcome regardless of personal background. We enforce a Code of conduct in order to promote a positive and inclusive environment.
Contributing
This project was made with ❤️. The simplest way to give back is by starring and sharing it online.
If the documentation is unclear or has a typo, please click on the page's Edit
button (pencil icon) and suggest a correction.
If you would like to help us fix a bug or add a new feature, please check our guidelines. Pull requests are welcome!
ehmicky 💻 🎨 🤔 📖  | 
    Marcel Gerber 💻  | 
    Paul Heidenreich 💻  |