Flutter

Flutter – How to Create Dart Object from JSON

In this post, we will understand the concepts in relation to creating a Dart object from a JSON object and how to use these DART objects in Flutter app. We will build an app and run the code shown in this post. 

Here is an example JSON object which we will work with, in order to create a custom Dart object called as School. The JSON represents information about a school including name, address, departments. You may note that the JSON object is primarily of type Map<String, dynamic> where key is String and value is of dynamic type. The key, name, is of type <String, String>, the key, address, is of type <String, Object> and the key, departments is of type <String, List<Object>>

 

{
    "name": "IIT Kharagpur",
    "address": {"city": "Kharagpur", "state": "West Bengal"},
    "departments": [
      {"name": "Computer Science",
        "seats": 50
      },
      {"name": "Electronics",
        "seats": 70
      },
      {"name": "Electrical",
        "seats": 80
      },
      {"name": "Mechanical",
        "seats": 100
      },
    ]
  }

In order to read above object, we will need to create a DART representation of School. School class will be composed of an Address and List of Department objects. Take a look at the following code. It comprises of three classes.

  • School class which comprises of three member variables such as name, address and list of departments
  • Address class
  • Department class

Each of the classes have static or factory method to create the respective DART object from JSON object

// School Object
class School {

  String name;
  Address address;
  List<Department> departments;

  School({
    this.name,
    this.address,
    this.departments
  });

  static fromJson(Map<String, dynamic> parsedJson){
    return School(
        name: parsedJson['name'],
        address : Address.fromJson(parsedJson['address']),
        departments : Department.listFromJson(parsedJson['departments'])
    );
  }
}
//
// Department object
//
class Department {
  String name;
  int seats;

  Department({
    this.name,
    this.seats
  });

  static listFromJson(List<Map<String, dynamic>> list) {
    List<Department> departments = [];
    for (var value in list) {
      departments.add(Department.fromJson(value));
    }
    return departments;
  }

  static fromJson(Map<String, dynamic> parsedJson){
    return Department(
        name: parsedJson["name"],
        seats: parsedJson["seats"]
    );
  }

}
//
// Address object
//
class Address {
  String city;
  String state;

  Address({
    this.city,
    this.state
  });

  static fromJson(Map<String, dynamic> parsedJson){
    return Address(
      city: parsedJson["city"],
      state: parsedJson["state"]
    );
  }
}

Once we have the Dart representation of objects ready, we will see how to read and display the JSON object on Flutter app. A stateless widget, SchoolInfoWidget is defined and the build method is used to build the widget / element tree as shown in the diagram later. Pay attention to the code School schoolInfo = School.fromJson(_school) which is passed the JSON object and returns the School DART object.

class SchoolInfoWidget extends StatelessWidget {

  Map<String, dynamic> _school = {
    "name": "IIT Kharagpur",
    "address": {
      "city": "Kharagpur",
      "state": "West Bengal"
    },
    "departments": [
      {"name": "Computer Science",
        "seats": 50
      },
      {"name": "Electronics",
        "seats": 70
      },
      {"name": "Electrical",
        "seats": 80
      },
      {"name": "Mechanical",
        "seats": 100
      },
    ]
  };

  @override
  Widget build(BuildContext context) {
    School schoolInfo =  School.fromJson(_school);
    return ListView(
        children: List.generate(schoolInfo.departments.length,(index){
            return Container(
                padding: const EdgeInsets.fromLTRB(20.0, 10.0, 10.0, 10.0),
                child: Text("Name: " + schoolInfo.departments[index].name.toString() +"\n" "Seats: " + schoolInfo.departments[index].seats.toString())
            );
          })
      );
  }
  
}

Finally, we will load the SchoolInfoWidget in the Flutter app using the following code:

import 'dart:io';

import 'package:device_info/device_info.dart';
import 'package:flutter/material.dart';

import 'School.dart';

void main() {
  runApp(MyApp());
}

class MyApp extends StatelessWidget {
  @override
  Widget build(BuildContext context) {
    return MaterialApp(
        title: 'Hello World App',
        home: Scaffold(
          appBar: AppBar(
            title: Text('School Information'),
          ),
          body: Center(
            child: SchoolInfoWidget(),
          ),
        ));
  }
}

And, running above app will look like the following in the mobile device.

Fig 1. Flutter App

The code given in this post will be very useful in reading JSON from REST API response as a set of DART objects.

Ajitesh Kumar

I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking.

Share
Published by
Ajitesh Kumar
Tags: flutter

Recent Posts

Agentic Reasoning Design Patterns in AI: Examples

In recent years, artificial intelligence (AI) has evolved to include more sophisticated and capable agents,…

1 month ago

LLMs for Adaptive Learning & Personalized Education

Adaptive learning helps in tailoring learning experiences to fit the unique needs of each student.…

1 month ago

Sparse Mixture of Experts (MoE) Models: Examples

With the increasing demand for more powerful machine learning (ML) systems that can handle diverse…

2 months ago

Anxiety Disorder Detection & Machine Learning Techniques

Anxiety is a common mental health condition that affects millions of people around the world.…

2 months ago

Confounder Features & Machine Learning Models: Examples

In machine learning, confounder features or variables can significantly affect the accuracy and validity of…

2 months ago

Credit Card Fraud Detection & Machine Learning

Last updated: 26 Sept, 2024 Credit card fraud detection is a major concern for credit…

2 months ago