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

natural-script

v1.0.2

Published

Script language to parse english expressions.

Downloads

14

Readme

natural-script Build Status

Natural-script is a script language to easily parse english expressions. It also includes a node.js implementation of a parser.

When you write a bot (slack bot, messenger bot, etc) you have to parse user inputs, classify it and extract information you need. It is easy to classify simple user sentences like hello, How are you?, What time is it in London ?. But it is quite harder when you want to extract complex information. Try for example to parse the date from the expression my appointment is planned for tomorrow at 2pm at home.

You could use Natural Language Processing but sometimes it is a bit overkill. Besides sometimes you expect very specific commands and NLP may be as strict as expected.

With natural-script, describe the request you expect with a simplified expression based on english words. These are some examples of natural-script language :

Hello
~hello
how are you
my email is {email}
go to {url:var1}

Getting started

For now, this project is only available for node.js because it uses natural.

# with npm
$ npm install natural-script

# with yarn
$ yarn add natural-script
import { parse } from 'natural-script'
(async () => {
  // parse returns a promise
  // await parse(<user input>, <pattern to match>)

  // by default parse accepts only strict equal strings
  (await parse('Hello', 'hello')) === false

  // ~ accepts similar words
  (await parse('Hello', '~hello')) === true
  (await parse('Hello', '~helo')) === true
  (await parse('Bonjour', '~hello')) === false

  // detects words and returns them
  (await parse('hello thibault', 'hello {word}')) === true
  (await parse('hello thibault', 'hello {word:name}')) === { name: 'foo' }

  // detects emails and returns them
  (await parse('my email is [email protected]', 'my email is {email}')) === true
  (await parse('my email is [email protected]', 'my email is {email:foo}')) === { foo: '[email protected]' }

  // detects urls and returns them
  (await parse('go to http://foo.com', 'go to {url}')) === true
  (await parse('go to http://foo.com', 'go to {url:bar}')) === { bar: 'http://foo.com' }
})()

Contribution

This project is only at the beginning so do not hesitate to contribute or propose improvements. Please follow guidelines.

License

This project is distributed on MIT license.