npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

efrt

v2.7.0

Published

neato compression of key-value data

Downloads

239,789

Readme

if your data looks like this:

var data = {
  bedfordshire: 'England',
  aberdeenshire: 'Scotland',
  buckinghamshire: 'England',
  argyllshire: 'Scotland',
  bambridgeshire: 'England',
  cheshire: 'England',
  ayrshire: 'Scotland',
  banffshire: 'Scotland'
}

you can compress it like this:

import { pack } from 'efrt'
var str = pack(data)
//'England:b0che1;ambridge0edford0uckingham0;shire|Scotland:a0banff1;berdeen0rgyll0yr0;shire'

then _very!_ quickly flip it back into:

import { unpack } from 'efrt'
var obj = unpack(str)
obj['bedfordshire'] //'England'

efrt packs category-type data into a very compressed prefix trie format, so that redundancies in the data are shared, and nothing is repeated.

By doing this clever-stuff ahead-of-time, efrt lets you ship much more data to the client-side, without hassle or overhead.

The whole library is 8kb, the unpack half is barely 2kb.

it is based on:

Benchmarks!

  • get a js object into very compact form
  • reduce filesize/bandwidth a bunch
  • ensure the unpacking time is negligible
  • keep word-lookups on critical-path
import { pack, unpack } from 'efrt' // const {pack, unpack} = require('efrt')

var foods = {
  strawberry: 'fruit',
  blueberry: 'fruit',
  blackberry: 'fruit',
  tomato: ['fruit', 'vegetable'],
  cucumber: 'vegetable',
  pepper: 'vegetable'
}
var str = pack(foods)
//'{"fruit":"bl0straw1tomato;ack0ue0;berry","vegetable":"cucumb0pepp0tomato;er"}'

var obj = unpack(str)
console.log(obj.tomato)
//['fruit', 'vegetable']

if you pass it an array of strings, it just creates an object with true values:

const data = [
  'january',
  'february',
  'april',
  'june',
  'july',
  'august',
  'september',
  'october',
  'november',
  'december'
]
const packd = pack(data)
// true¦a6dec4febr3j1ma0nov4octo5sept4;rch,y;an1u0;ly,ne;uary;em0;ber;pril,ugust
const sameArray = Object.keys(unpack(packd))
// same thing !

Reserved characters

the keys of the object are normalized. Spaces/unicode are good, but numbers, case-sensitivity, and some punctuation (semicolon, comma, exclamation-mark) are not (yet) supported.

specialChars = new RegExp('[0-9A-Z,;!:|¦]')

efrt is built-for, and used heavily in compromise, to expand the amount of data it can ship onto the client-side. If you find another use for efrt, please drop us a line🎈

Performance

efrt is tuned to be very quick to unzip. It is O(1) to lookup. Packing-up the data is the slowest part, which is usually fine:

var compressed = pack(skateboarders) //1k words (on a macbook)
var trie = unpack(compressed)
// unpacking-step: 5.1ms

trie.hasOwnProperty('tony hawk')
// cached-lookup: 0.02ms

Size

efrt will pack filesize down as much as possible, depending upon the redundancy of the prefixes/suffixes in the words, and the size of the list.

  • list of countries - 1.5k -> 0.8k (46% compressed)
  • all adverbs in wordnet - 58k -> 24k (58% compressed)
  • all adjectives in wordnet - 265k -> 99k (62% compressed)
  • all nouns in wordnet - 1,775k -> 692k (61% compressed)

but there are some things to consider:

  • bigger files compress further (see 🎈 birthday problem)
  • using efrt will reduce gains from gzip compression, which most webservers quietly use
  • english is more suffix-redundant than prefix-redundant, so non-english words may benefit from other styles

Assuming your data has a low category-to-data ratio, you will hit-breakeven with at about 250 keys. If your data is in the thousands, you can very be confident about saving your users some considerable bandwidth.

Use

IE9+

<script src="https://unpkg.com/efrt@latest/builds/efrt.min.cjs"></script>
<script>
  var smaller = efrt.pack(['larry', 'curly', 'moe'])
  var trie = efrt.unpack(smaller)
  console.log(trie['moe'])
</script>

if you're doing the second step in the client, you can load just the CJS unpack-half of the library(~3k):

const unpack = require('efrt/unpack') // node/cjs
<script src="https://unpkg.com/efrt@latest/builds/efrt-unpack.min.cjs"></script>
<script>
  var trie = unpack(compressedStuff)
  trie.hasOwnProperty('miles davis')
</script>

Thanks to John Resig for his fun trie-compression post on his blog, and Wiktor Jakubczyc for his performance analysis work

MIT