Code Monkey home page Code Monkey logo

recipe-parser's Introduction

recipe-ingredient-parser

Natural language parser for recipes and lists of ingredients. Can parse a string into an object and also combine an array of these ingredient objects.

To install

npm install recipe-ingredient-parser or yarn add recipe-ingredient-parser

To use

import { parse } from 'recipe-ingredient-parser';

And then use on a string, for example: parse('1 teaspoon basil');

Will return an object:

{
  quantity: 1,
  unit: 'teaspoon',
  ingredient: 'basil'
};

Combine ingredient objects

combine([{
  quantity: 1,
  unit: 'teaspoon',
  ingredient: 'basil'
},
{
  quantity: 1,
  unit: 'teaspoon',
  ingredient: 'basil'
}]);

Will return

[{
  quantity: 2,
  unit: 'teaspoon',
  ingredient: 'basil'
}]

Unicode Fractions

Will also correctly parse unicode fractions into the proper amount

Development

Clone the repo and yarn to install packages. If yarn test comes back good after your code changes, give yourself a pat on the back.

Natural Language Parsing

This project uses Natural, for more information, see https://dzone.com/articles/using-natural-nlp-module

Publishing

Checkout https://docs.npmjs.com/getting-started/publishing-npm-packages for more info

recipe-parser's People

Contributors

mackenziemcclaskey avatar wadepeterson avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar

recipe-parser's Issues

Doesn't handle multiple consecutive numerics

I tried the following input:

"1 8.5oz can blah"
and I get the following error:

TypeError: strVal.split(...)[1] is undefined
at
node_modules/recipe-ingredient-parser/lib/convert.js:86

This is probably an odd case, but I figured I'd mention it because I could see users entering something oddball like that.

possible to add configure/add custom units of measurement?

I'd love to add some custom units to my project using your npm module, for ex: tsp. and tbsp. and possibly even 'large'.

Is it possible to configure custom units using your npm module, already?

If not, could I raise a PR to add that functionality?

Units do not seem to be parsed properly

Version of package: 1.5.6
Node version: 10.9.0

➜ node
> parse=require('recipe-ingredient-parser').parse
[Function: parse]
> parse('- ½ cup coconut flour')
{ quantity: '0.5',
  unit: null,
  ingredient: '-  cup coconut flour' }
> parse('- 1 ½ teaspoon vanilla extract')
{ quantity: '1.5',
  unit: null,
  ingredient: '- 1  teaspoon vanilla extract' }

Expected behaviour: "cup" and "teaspoon" should be parsed as units.

Actual behaviour: unit seems to end up under ingredient, unit is null

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.