DataCollection.js

Manipulate data from API responses with ease.

Inspired by modern Object Relational Managers, DataCollection.js is a JavaScript library for storage, filtration, manipulation and accession of large datasets. It is ideal for working with data returned from RESTful API endpoints.

Boasting synchronous performance that nears native Array manipulation for large (>10,000) recordsets, let DataCollection.js do your heavy lifting for you.

Installation

You can begin using DataCollection.js by embedding the following script (assumes it has been placed in your root directory)

Web

<script src="/data_collection-1.1.6.js"></script>

Alternatively, the minified version can be found at

<script src="/data_collection-1.1.6-min.js"></script>

You can then start using DataCollection objects with

var dc = new DataCollection();

node

$ npm install data-collection

Followed by a script with this require...

var DataCollection = require('data-collection');

Woohoo!

Examples

DataCollection can be used for fast, synchronous processing of large datasets (arrays of objects) - i.e. a RESTful API response.

It is especially useful for maintaining maps of specific keys and indexing results.

Let's say that I have a standardized Array containing the results of a RESTful API response. My data set looks like this:

var characters = [
  {
    id: 1,
    first_name: 'Jon',
    last_name: 'Snow',
    gender: 'm',
    age: 14,
    location: 'Winterfell'
  },
  {
    id: 2,
    first_name: 'Eddard',
    last_name: 'Stark',
    gender: 'm',
    age: 35,
    location: 'Winterfell'
  },
  {
    id: 3,
    first_name: 'Catelyn',
    last_name: 'Stark',
    gender: 'f',
    age: 33,
    location: 'Winterfell'
  },
  {
    id: 4,
    first_name: 'Roose',
    last_name: 'Bolton',
    gender: 'm',
    age: 40,
    location: 'Dreadfort'
  },
  {
    id: 5,
    first_name: 'Ramsay',
    last_name: 'Snow',
    gender: 'm',
    age: 15,
    location: 'Dreadfort'
  }
];

First off, let's load this data into a DataCollection...

var charDC = new DataCollection(characters);

Now, let's approach some problems...

---

How do I find the Bastards from the North?

filter allows us to look for a specific value.

var bastards = charDC.query().filter({last_name: 'Snow'}).values();

---

How do I find out the highest age?

A simple max() call will do the trick.

var topAge = charDC.query().max('age');

---

How do I find all the unique locations?

DataCollection provides an easy distinct function for use.

DataCollection

var locations = charDC.query().distinct('location');

---

What if I want to permanently remove Catelyn and Eddard?

No problem!

DataCollection

charDC.query().filter({first_name__in: ['Catelyn', 'Eddard']}).remove();

---

More examples

// Will return Jon, Eddard and Ramsay
charDC.query()
  .filter({gender: 'm', age__lt: 40})
  .values();

// Updates location
charDC.query()
  .filter({location: 'Winterfell'})
  .exclude({first_name: 'Jon'})
  .update({location: 'King\'s Landing'});

// Finds Roose, Ramsay
chardDC.query()
  .filter({first_name__contains: 'R'});

// Finds Roose, Ramsay, Eddard --- case insensitive
charDC.query()
  .filter({first_name__icontains: 'R'})
  .values();

// Creates a mapping for current future values...
charDC.createMapping('is_bastard', function(row) {
  return row.last_name === 'Snow';
});

// true
charDC.query().filter({first_name: 'Jon'}).first().is_bastard;
// false
charDC.query().filter({first_name: 'Catelyn'}).first().is_bastard;

// Add an entry (Can accept each entry as an argument, or an array)
charDC.insert({
  id: 6,
  first_name: 'Rob',
  last_name: 'Stark',
  gender: 'm',
  age: 14,
  location: 'Winterfell'
});

// new entry, but is also false
charDC.query().filter({first_name: 'Rob'}).first().is_bastard;

// will return Eddard and Catelyn rows
charDC.query()
  .sort('age', true) // sortDesc = true
  .limit(1, 2)
  .values();

Nested objects

What if I have object inside of my DataCollection? Can I filter and sort by those fields as well?

Of course! Separate nested fields by double underscores (__).

Please note that when using this method, exact values must be checked for using '__is'.

var dc = new DataCollection();
dc.load([{
  main: {
    sub: 7,
    sub2: {
      low: 8
    }
  }
}, {
  main: {
    sub: 7,
    sub2: {
      low: 20
    }
  }
}, {
  main: {
    sub: -1,
    sub2: {
      low: 16
    }
  }
}]);

// Returns only first two rows
dc.query().filter({main__sub__is: 7}).values();

// Returns only last two rows
dc.query().filter({main__sub__low__gte: 10}).values();

And there's more! Try playing around.

Documentation

DataCollection Object

DataCollection

DataCollection( [Optional Array] data )

Constructor (used with new keyword)

If provided data, will run DataCollection.prototype.load(data)

---

Methods

---

DataCollection.prototype.defineIndex

defineIndex( [String] key )
  returns self

Define a unique key to use as an index for this collection used for DataCollection.prototype.exists, DataCollection.prototype.fetch and DataCollection.prototype.destroy

All indexed values will be converted to strings, be careful about uniqueness

---

DataCollection.prototype.createMapping

createMapping( [String] key, [Function] map -> ([Object] row) )
  returns self

Define a mapped key, and a function that returns the associated value based on the input row. Can be used any time, new mappings will be applied to your DataCollection immediately.

Example:

var dc = new DataCollection();
dc.createMapping('c', function(row) { return row['a'] + row['b']; });
dc.load([{a: 1, b: 2}, {a: 2, b: 3}]);
console.log(dc.query().last()); // logs {a: 2, b: 3, c: 5}

---

DataCollection.prototype.exists

exists( [String] indexedValue )
  returns boolean

Determine whether the DataCollection has an entry with the specified index based on your index key

---

DataCollection.prototype.fetch

fetch( [String] indexedValue )
  returns Object

fetches object (if it exists) associated with the specified index based on your index key. Otherwise, returns null.

---

DataCollection.prototype.destroy

destroy( [String] indexedValue )
  returns true

Destroys object (if it exists) associated with the specified index based on your index key. Otherwise, throws an error.

---

DataCollection.prototype.load

load( [Object] row_1, ..., [Object] row_n )
load( [Array] data )
  returns true

Loads (truncates, then adds) new data from individual row Objects or an array of row Objects

---

DataCollection.prototype.insert

insert( [Object] row_1, ..., [Object] row_n )
insert( [Array] data )
  returns true

Inserts new data from individual row Objects or an array of row Objects

---

DataCollection.prototype.truncate

truncate()
  returns true

Empties all data from DataCollection

---

DataCollection.prototype.query

query()
  returns DataCollectionQuery

returns a new DataCollectionQuery containing a referential set of all data from the parent DataCollection.

DataCollectionQuery Object

DataCollectionQuery

DataCollectionQuery()

Constructor, only accessible via DataCollection.prototype.query()

---

Methods

---

DataCollectionQuery.prototype.filter

filter( [Object] filters_1, ..., [Object] filters_n )
  returns new DataCollectionQuery

Returns a new DataCollectionQuery containing a referential subset of its parent. Contains filtered values (see: Filters).

Providing new filter objects via separate arguments does a logical OR between the filter sets. (Within a filter set is logical AND.)

---

DataCollectionQuery.prototype.exclude

exclude( [Object] filters )
  returns new DataCollectionQuery

Returns a new DataCollectionQuery containing a referential subset of its parent. Excludes filtered values (see: Filters)

---

DataCollectionQuery.prototype.spawn

spawn( [Boolean] ignoreIndex )
  returns new DataCollection

Creates a new DataCollection object (non-referential, new values) from all data contained within the current DataCollectionQuery. Will inherit the parent DataCollection's index unless ignoreIndex is set to true.

---

DataCollectionQuery.prototype.each

each( [Function] callback -> ([Object] row, [Integer] index) )
  returns self

Loops through all rows of data, and performs callback for each one

Example

var dc = new DataCollection([{a: 1, b: 2}, {a: 2, c: 3}]);
var query = dc.query();
query.each(function(row, index) {
  console.log(index + ': ' + row['a'] + ', ' + row['b']);
});

// logs
//    0: 1, 2
//    1: 2, 3

---

DataCollectionQuery.prototype.update

update( [Object] values )
  returns self

Assigns all key-value pairs from values to every row in the current selection (updates parent DataCollection)

---

DataCollectionQuery.prototype.remove

remove()
  returns true

Removes all rows contained in DataCollectionQuery from the parent DataCollection

---

DataCollectionQuery.prototype.order

order( [String] key, [Optional Boolean] orderDesc = false )
  returns DataCollectionQuery

Returns a new DataCollectionQuery containing the parent's rows, sorted by a specific key (descending if sortDesc = true).

Sort order is as follows (regardless of ASC or DESC): Function, Object, Date Object, String, Boolean, Number, NaN, null, undefined

Strings, Booleans, and Numbers will be sorted based on their values (ASC/DESC) Functions, Objects and identical values will be sorted based on the order in which they were inserted (stable sort).

---

DataCollectionQuery.prototype.sort

sort( [String] key, [Optional Boolean] orderDesc = false )
  returns DataCollectionQuery

Alias of .order

---

DataCollectionQuery.prototype.sequence

sequence( [String or Number] indexedValue_1, ..., [String or Number] indexedValue_n )
sequence( [Array] indexedValues )
  returns DataCollectionQuery

Returns a new DataCollectionQuery containing the parent's rows with specified indices, ordered in the sequence provided.

Can accept indices as arguments or in an Array.

---

DataCollectionQuery.prototype.values

values( [Optional String] key )
  returns Array

Returns an array of all row Objects (each Object is referential!) in the DataCollectionQuery, or an array of all values from a specific key if provided

---

DataCollectionQuery.prototype.json

json( [Optional String] key )
  returns String

Returns a JSON-stringified version of .values()

---

DataCollectionQuery.prototype.max

max( [String] key )
  returns Float

Returns the maximum value (JavaScript "greater than (>)") contained in key from the DataCollectionQuery subset

---

DataCollectionQuery.prototype.min

min( [String] key )
  returns Float

Returns the minimum value (JavaScript "greater than (>)") contained in key from the DataCollectionQuery subset

---

DataCollectionQuery.prototype.sum

sum( [String] key )
  returns Float

Returns the numeric sum of all values contained in key from the DataCollectionQuery subset

---

DataCollectionQuery.prototype.avg

avg( [String] key )
  returns Float

Returns the numeric average of all values contained in key from the DataCollectionQuery subset

---

DataCollectionQuery.prototype.transform

transform( [Object] keyMapPair )
  returns new DataCollectionQuery

Maps each row of the current DataCollectionQuery to a new object with specified keys.

The "map" in keyMapPair can be either a string representation of a key or a mapping function.

  dc.load([
    {a: 1, b: 2, c: 3},
    {a: 4, b: 5, c: 6}
  ]);

  dc.query().transform({d: 'a', e: 'b', f: function(row) { return row.a + row.b + row.c; }}).values();

  /* will return...

  [
    {d: 1, e: 2, c: 6},
    {d: 4, e: 5, c: 15}
  ]

  */

---

DataCollectionQuery.prototype.reduce

reduce( [String] key, [Function] callback -> ([Any] prevValue, [Any] curValue, [Any] index) )
  returns Any

Runs a specified reduction function on all values contained in key from the DataCollectionQuery subset.

---

DataCollectionQuery.prototype.distinct

distinct( [String] key )
  returns Array

Returns an array of all unique values (converted to String) with specified key from the DataCollectionQuery subset

---

DataCollectionQuery.prototype.limit

limit( [Integer] count )
limit( [Integer] offset, [Integer] count )
  returns new DataCollectionQuery

Returns a new DataCollectionQuery containing the first count items from the current DataCollectionQuery, or containing count items beginning at offset

---

DataCollectionQuery.prototype.count

count()
  returns Integer

Returns the amount of items (rows) in the current DataCollectionQuery

Filters

DataCollection supports a number of filters in the filter() and exclude() functions. Many will be familiar if you've used the Django ORM or checked out another project of ours, FastAPI.

All filters are prefixed with a double underscore when used.

Please note that DataCollection supports filtering (and sorting) based on nested objects. The syntax is for find the is filtered value of a nested field would be {field__nestedField__is: 7}. You can nest indefinitely using double underscores.

is

a === b

Checks for exact equivalence. Equivalent to no specified filter. (Only the field name). Exists for the purpose of standardization and edge cases (i.e. if your field ends with __).

---

not

a !== b

Checks for inequivalence. (Not exactly matching.)

---

gt

a > b

Checks if contained value is greater than provided value.

---

gte

a >= b

Checks if contained value is greater than or equal to provided value.

---

lt

a < b

Checks if contained value is less than provided value.

---

lte

a <= b

Checks if contained value is less than or equal to provided value.

---

contains

a.indexOf(b) > -1

Checks if contained value contains the provided value. Works for strings or arrays.

---

icontains

a.toLowerCase().indexOf(b.toLowerCase()) > -1

Case insensitive contains. Only works for strings comparisons.

---

in

b.indexOf(a) > -1

Checks if the contained value exists in the provided value. Works for strings or arrays.

---

not_in

b.indexOf(a) === -1

Checks if the contained value does not exist in the provided value. Works for strings or arrays.

Tests and Benchmarks

Current test coverage is 100%

Included with this repository are tests (in /tests) to make sure everything is running as expected.

There is a node webserver in the root repository directory that can be used for testing on localhost:8888. To start the server (with node installed) simply run:

$ node testserv.js

Tests are run using QUnit, coverage sampled using Blanket.js.

A few benchmarks are logged in the JavaScript developer console.

Acknowledgements

DataCollection is MIT licensed, feel free to use it wherever you'd like. Thanks for checking us out! We welcome good, thoughtful contributions.

DataCollection was created at Storefront, Inc. in 2014 by Keith Horwood.

Feel free to follow on Twitter:

@thestorefront, @keithwhor

Or check out our GitHub Repositories for more libraries:

Storefront on GitHub, Keith Horwood on GitHub