Table of Contents

CONSTRUCT JSON

Category: Transform / Web


Description

This action constructs a JSON object from a tabular dataset. It has two modes:

A constructed JSON object is effectively a regular text value that is stored in a datagrid cell in EasyMorph.


Action settings

Mode: "Object per row"

In this mode, each row of the source dataset is used to construct a flat JSON object in which every column value corresponds to one object property. For instance, the dataset below:

Name Kingdom Phylum Subphylum Class Order Family
Rabbit Animalia Chordata Vertebrata Mammalia Lagomorpha Leporidae

is constructed as the following JSON: 

{
  "Name":"Rabbit",
  "Kingdom":"Animalia",
  "Phylum":"Chordata",
  "Subphylum":"Vertebrata",
  "Class": "Mammalia",
  "Order":"Lagomorpha",
  "Family": "Leporidae"
}

If the source dataset contains multiple rows, they will be converted into an array of JSON objects where each object corresponds to one row. Example:

ID Name
1 Apple
2 Orange

Result: 

[
  {
    "ID":1,
    "Name":"Apple"
  },
  {
    "ID":2,
    "Name":"Orange"
  }
]


Mode: "Array per column"

In this mode, the source dataset is converted into a new dataset in which values of each column are rolled up into a JSON array. For instance, the table from the example above would be converted into the following table:

ID Name
[1,2] [Apple,Orange]



Data type conversion

EasyMorph data types are converted to JSON types as follows:

EasyMorph Example JSON Example
Text ABC string "ABC"
Number 123.45 number 123.45
Number (formatted as date) 2020-Jan-10 date 2020-01-10T00:00:00
Boolean TRUE boolean true
Empty null null
Error #Division by zero Fails to convert

Note that the action fails if the source dataset contains an error value.


Nesting JSON objects

EasyMorph automatically detects if a text value is already a JSON object or a JSON array. In this case, the text value is inserted verbatim, i.e. without wrapping in double-quotes. This feature allows creating complex hierarchical JSON objects that nest other JSON objects. For instance, converting the table below:

Track Country State/province City Location Hiatus
Circuit Gilles Villeneuve Canada QC Montreal {"lat":45.500578, "long":-73.522461} [1987, 2009]

would produce the following JSON: 

{
  "Track":"Circuit Gilles Villeneuve",
  "Country":"Canada",
  "State/province":"QC",
  "City":"Montreal"
  "Location": {
    "lat":45.500578, 
    "long":-73.522461
  },
  "Hiatus": [1987, 2009]
}

Notice that "Location" is inserted as a JSON object, not as text. Also, the field "Hiatus" is inserted as a JSON array, not as text.


Community examples


See also