# Incremental: A Library for Efficient Computations

Create calculations that respond quickly to changing data.

- **Source:** [Hacker News (news.ycombinator.com)](https://brifing.si/source/13c923cd-6d99-442b-9b8b-1181f4d8cd91)
- **Published:** 2026-07-21
- **Topic:** [Data & AI](https://brifing.si/c/data-ai)
- **Original article:** <https://github.com/janestreet/incremental>
- **On Brifing:** https://brifing.si/s/4e708cc8-07ab-400f-91b1-285dea215af7

## What is Incremental?

Incremental is a library designed to create complex computations that can efficiently respond to changing inputs. This library is particularly useful in large-scale calculations and GUI applications.

## Inspiration

Incremental is inspired by the work of Umut Acar and his team on self-adjusting computations. This approach allows calculations to be dynamically updated.

## Use Cases

Incremental can be used in various fields such as performing large calculations in spreadsheets, creating efficient views in GUI applications, and computing derived data synchronized with source data.

## Efficiency Advantage

This library provides significant efficiency gains by updating only the changed parts of calculations. This is particularly important when working with large data sets.

## Documentation and Resources

Detailed documentation and user guide for the Incremental library can be found in the incremental/src/incremental_intf.ml file. Additionally, blog posts and videos are useful for learning the library.

## Why It Matters

Incremental is an important tool for increasing efficiency and facilitating dynamic calculations in modern software development. This library can make a significant difference, especially in large and complex projects.

## Sources covering this story

- https://github.com/janestreet/incremental — 

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_Summary written by Brifing from the original reporting. Copyright in the original article belongs to its publisher; read the full piece at the link above._