prop-extractor

Contents

1. Creating Extractor instance and test data
2. Getting single values
   2.1. ... if path exists
   2.2. ... if path doesn't exist
   2.3. ... with checking of path existence
3. Getting arrays of values
   3.1. ... if path exists
   3.2. ... if path doesn't exist
   3.3. ... with checking of path existence
4. More examples
   4.1. Getting of array elements
   4.2. Getting a defined property of array elements (objects)
   4.3. Getting a defined property of array elements (objects) that are deeply nested
5. Using filters
   5.1. Getting names of countries with population bigger than 300 millions
   5.2. Getting names of cities where name starts with ‘S’
   5.3. Getting cities with population bigger than 20 millions in countries with population bigger than 1 billion

1. Creating Extractor instance and test data

const Extractor = require('prop-extractor');
let extractor = new Extractor();
 
let data = {
    countries: [
        {
            name: 'Australia',
            population: 24641662,
            cities: [
                {name: 'Sydney', population: 5029768},
                {name: 'Melbourne', population: 4725316},
                {name: 'Canberra', population: 435019}
            ]
        },
        {
            name: 'Brazil',
            population: 211243220,
            cities: [
                {name: 'São Paulo', population: 12038175},
                {name: 'Rio de Janeiro', population: 6498837},
                {name: 'Salvador', population: 2938092}
            ]
        },
        {
            name: 'China',
            population: 1388232693,
            cities: [
                {name: 'Shanghai', population: 24152700},
                {name: 'Beijing', population: 21700000},
                {name: 'Guangzhou', population: 14043500}
            ]
        },
        {
            name: 'United States',
            population: 326474013,
            cities: [
                {name: 'New York', population: 8537673},
                {name: 'Los Angeles', population: 3976322},
                {name: 'Chicago', population: 2704958}
            ]
        }
    ],
    country_codes: ['AU', 'BR', 'CN', 'US'],
    count: 4
};
 

2. Getting single values

2.1. ... if path exists

extractor.setPath('data.count');
console.log(extractor.extractFrom(data).get());
 
// 4

2.2. ... if path doesn't exist

extractor.setPath('data.foo.bar.baz');
console.log(extractor.extractFrom(data).get());
 
// undefined

2.3. ... with checking of path existence

extractor.setPath('data.count');
let response = extractor.extractFrom(data);
 
if (response.has()) {
  console.log(response.get());
}
 
// 4

3. Getting arrays of values

3.1. ... if path exists

extractor.setPath('data.country_codes.[]');
console.log(extractor.extractFrom(data).get());
 
// ['AU', 'BR', 'CN', 'US']

3.2. ... if path doesn't exist

extractor.setPath('data.foo.[].bar');
console.log(extractor.extractFrom(data).get());
 
// []

3.3. ... with checking of path existence

extractor.setPath('data.country_codes.[]');
response = extractor.extractFrom(data);
 
if (response.has()) {
  console.log(response.get());
}
 
// ['AU', 'BR', 'CN', 'US']

4. More examples

4.1. Getting of array elements

extractor.setPath('data.countries.[]');
console.log(extractor.extractFrom(data).get());
 
// [ { name: 'Australia', population: 24641662, cities: [ ... ] },
// { name: 'Brazil', population: 211243220, cities: [ ... ] },
// { name: 'China', population: 1388232693, cities: [ ... ] },
// { name: 'United States', population: 326474013, cities: [ ... ] } ]

4.2. Getting a defined property of array elements (objects)

extractor.setPath('data.countries.[].name');
console.log(extractor.extractFrom(data).get());
 
// [ 'Australia', 'Brazil', 'China', 'United States' ]

4.3. Getting a defined property of array elements (objects) that are deeply nested

extractor.setPath('data.countries.[].cities.[].name');
console.log(extractor.extractFrom(data).get());
 
// [ 'Sydney', 'Melbourne', 'Canberra', 'São Paulo',
// 'Rio de Janeiro', 'Salvador', 'Shanghai', 'Beijing',
// 'Guangzhou', 'New York', 'Los Angeles', 'Chicago' ]

5. Using filters

5.1. Getting names of countries with population bigger than 300 millions

extractor.setPath('data.countries.[population].name');
extractor.removeAllFilters();
extractor.setFilter('population', (item) => {
  return (item.population > 300000000);
});
console.log(extractor.extractFrom(data).get());
 
// [ 'China', 'United States' ]

5.2. Getting names of cities where name starts with 'S'

extractor.setPath('data.countries.[].cities.[city_name].name');
extractor.removeAllFilters();
extractor.setFilter('city_name', (item) => {
  return (item.name[0] === 'S');
});
console.log(extractor.extractFrom(data).get());
 
// [ 'Sydney', 'São Paulo', 'Salvador', 'Shanghai' ]

5.3. Getting cities with population bigger than 20 millions in countries with population bigger than 1 billion

extractor.setPath('data.countries.[country_population].cities.[city_population]');
extractor.removeAllFilters();
extractor.setFilter('country_population', (item) => {
  return (item.population > 1000000000);
});
extractor.setFilter('city_population', (item) => {
  return (item.population > 20000000);
});
console.log(extractor.extractFrom(data).get());
 
// [ { name: 'Shanghai', population: 24152700 },
// { name: 'Beijing', population: 21700000 } ]