lodash vs underscore vs ramda vs deepdash
JavaScript Utility Libraries Comparison
1 Year
lodashunderscoreramdadeepdashSimilar Packages:
What's JavaScript Utility Libraries?

JavaScript utility libraries provide a set of functions that facilitate common programming tasks, such as manipulating arrays, objects, and functions. These libraries enhance productivity by offering pre-built methods that simplify coding, reduce boilerplate, and improve code readability. Each library has its own design philosophy and feature set, catering to different programming styles and needs.

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lodash69,295,19860,475-1064 years agoMIT
underscore14,610,36427,386906 kB5210 months agoMIT
ramda11,414,35323,9941.18 MB151a year agoMIT
deepdash91,190279-274 years agoMIT
Feature Comparison: lodash vs underscore vs ramda vs deepdash

Functional Programming Support

  • lodash:

    Lodash supports functional programming with methods like _.curry, _.partial, and _.flow, allowing developers to create more reusable and composable functions.

  • underscore:

    Underscore offers some functional programming capabilities, such as _.map, _.reduce, and _.filter, but it is not as comprehensive as Ramda in this regard.

  • ramda:

    Ramda is designed with functional programming in mind, providing a rich set of tools for function composition, currying, and immutability, making it a favorite among functional programmers.

  • deepdash:

    Deepdash does not focus on functional programming principles but provides utility functions that can be used in a functional style when combined with lodash.

Performance

  • lodash:

    Lodash is known for its performance optimizations, especially for operations on arrays and objects. It is designed to be fast and efficient, making it suitable for performance-critical applications.

  • underscore:

    Underscore is generally slower than lodash due to its simpler implementation. It is suitable for small-scale applications where performance is not a critical concern.

  • ramda:

    Ramda's emphasis on immutability and functional programming can lead to performance trade-offs compared to lodash, especially when dealing with large datasets. However, its lazy evaluation can optimize performance in certain scenarios.

  • deepdash:

    Deepdash inherits performance characteristics from lodash but may incur additional overhead due to its deep traversal capabilities. It is optimized for deep data structures but should be used judiciously to avoid performance bottlenecks.

Modularity

  • lodash:

    Lodash is modular, allowing developers to import only the functions they need, which helps reduce bundle size and improve performance in modern applications.

  • underscore:

    Underscore is less modular compared to lodash and ramda, providing a single file that includes all functions. This can lead to larger bundle sizes if not managed properly.

  • ramda:

    Ramda is highly modular, enabling developers to import specific functions as needed. This modularity aligns well with tree-shaking and helps keep bundle sizes small.

  • deepdash:

    Deepdash extends lodash with additional functionality, but it is not modular in the sense that it requires lodash to function, which may increase bundle size if not tree-shaken properly.

Learning Curve

  • lodash:

    Lodash has a gentle learning curve, with clear documentation and a straightforward API that makes it accessible for beginners and experienced developers alike.

  • underscore:

    Underscore is easy to learn, especially for those familiar with JavaScript. Its API is simple and intuitive, making it a good starting point for utility libraries.

  • ramda:

    Ramda has a steeper learning curve due to its functional programming paradigm and point-free style. Developers new to functional programming may find it challenging initially.

  • deepdash:

    Deepdash has a moderate learning curve, especially for those already familiar with lodash. Understanding its deep traversal capabilities may require additional learning.

Community and Ecosystem

  • lodash:

    Lodash has a large and active community, extensive documentation, and numerous resources available, making it easy to find support and examples.

  • underscore:

    Underscore has a long-standing community, but it has seen a decline in usage as lodash has become more popular. However, it still has a wealth of legacy resources.

  • ramda:

    Ramda has a dedicated community focused on functional programming, with resources and discussions available, though it is smaller than lodash's community.

  • deepdash:

    Deepdash has a smaller community compared to lodash and ramda, which may result in fewer resources and examples available for learning and troubleshooting.

How to Choose: lodash vs underscore vs ramda vs deepdash
  • lodash:

    Choose Lodash for a well-rounded utility library that balances performance and functionality. It is widely used, well-documented, and provides a rich set of functions for array and object manipulation.

  • underscore:

    Choose Underscore if you need a lightweight library with essential utility functions. It provides a simpler API compared to Lodash and is a good choice for projects that require basic functionality without the overhead.

  • ramda:

    Choose Ramda if you prefer a functional programming style and immutability. It emphasizes a point-free style and allows for easier composition of functions, making it suitable for functional programming enthusiasts.

  • deepdash:

    Choose Deepdash if you need to perform deep operations on nested data structures, as it extends lodash with deep traversal capabilities, making it ideal for complex data manipulation.

README for lodash

lodash v4.17.21

The Lodash library exported as Node.js modules.

Installation

Using npm:

$ npm i -g npm
$ npm i --save lodash

In Node.js:

// Load the full build.
var _ = require('lodash');
// Load the core build.
var _ = require('lodash/core');
// Load the FP build for immutable auto-curried iteratee-first data-last methods.
var fp = require('lodash/fp');

// Load method categories.
var array = require('lodash/array');
var object = require('lodash/fp/object');

// Cherry-pick methods for smaller browserify/rollup/webpack bundles.
var at = require('lodash/at');
var curryN = require('lodash/fp/curryN');

See the package source for more details.

Note:
Install n_ for Lodash use in the Node.js < 6 REPL.

Support

Tested in Chrome 74-75, Firefox 66-67, IE 11, Edge 18, Safari 11-12, & Node.js 8-12.
Automated browser & CI test runs are available.