@itentialopensource/groupby-property NPM

Deprecation Notice

This Pre-Built has been deprecated as of 01-15-2024 and will be end of life on 01-15-2025. The capabilities of this Pre-Built have been replaced by the IAP - Data Manipulation

Group By Property

Overview
Installation Prerequisites
How to Install
How to Run
Attributes
Examples
Additional Information

Overview

This JST allows IAP users to pass in: (1) an array of objects and (2) a property/key by which to group the objects. The result will be an object of objects grouped by the unique property/key specified by the user ((2) above). The embedded object lists the remaining keys (excluding the groupByProperty as it is the top-level object) and its matching values in an array with comma-separated values.

Note 1: Values within each array are listed in the same order as the "groupByProperty".
Note 2: Please see examples below for clarity on input and output data.

Installation Prerequisites

Users must satisfy the following prerequisites:

Itential Automation Platform : ^2022.1

How to Install

To install the pre-built:

Verify you are running a supported version of the Itential Automation Platform (IAP) as listed above in the Prerequisites section.
The pre-built can be installed from within App-Admin_Essential. Simply search for the name of your desired pre-built and click the install button.

How to Run

Use the following to run the pre-built: 1. Once the JST is installed as outlined in the How to Install section above, navigate to the workflow where you would like to group an array of objects by a common property (with the result object similar to SQL's groupby) and add a JSON Transformation (JST) task. 2. Inside the Transformation task, search for and select groupByProperty (the name of the JST). 3. The inputs to the JST would be (1) an array of objects and (2) a property/key by which to group the objects. (See above image as an examplee.) 4. Save your input and the task is ready to run inside of IAP.

Attributes

Attributes for the pre-built are outlined in the following tables.

Input:
Output:

Examples

Example 1

Input

{
  "array": [
    {
      "item": "apple",
      "price": "42.2",
      "type": "fruit"
    },
    {
      "item": "banana",
      "price": "10.1",
      "type": "fruit"
    },
    {
      "item": "potato",
      "price": "20",
      "type": "vegetable"
    }
  ],
  "groupByProperty": "type"
}

Output

{
  "fruit": {
    "item": [
      "apple",
      "banana"
    ],
    "price": [
      "42.2",
      "10.1"
    ]
  },
  "vegetable": {
    "item": [
      "potato"
    ],
    "price": [
      "20"
    ]
  }
}

Example 2

Input

{
  "array": [
    {
      "number": 43,
      "president": "George W. Bush",
      "took_office": "2001-01-20",
      "left_office": "2009-01-20",
      "party": "Republican"
    },
    {
      "number": 44,
      "president": "Barack Obama",
      "took_office": "2009-01-20",
      "left_office": "2017-01-20",
      "party": "Democratic"
    },
    {
      "number": 45,
      "president": "Donald J. Trump",
      "took_office": "2017-01-20",
      "left_office": null,
      "party": "Republican"
    }
  ],
  "groupByProperty": "party"
}

Output

{
  "Republican": {
    "number": [
      43,
      45
    ],
    "president": [
      "George W. Bush",
      "Donald J. Trump"
    ],
    "took_office": [
      "2001-01-20",
      "2017-01-20"
    ],
    "left_office": [
      "2009-01-20",
      null
    ]
  },
  "Democratic": {
    "number": [
      44
    ],
    "president": [
      "Barack Obama"
    ],
    "took_office": [
      "2009-01-20"
    ],
    "left_office": [
      "2017-01-20"
    ]
  }
}