Markus  Bartell

Markus Bartell

1601541270

Difference Between JSON.parse() and JSON.stringify()

The JSON object has two useful methods which are used to parse JSON data from string or convert JavaScript object into string.

The JSON.stringify() method converts a JavaScript object or value into a JSON string whereas JSON.parse() method parses a JSON string into a JavaScript object.

If you have worked on AJAX’s XMLHttpRequest(), then you would have noticed that the response we get is basically a String. So to use that response data, you have to parse it to JavaScript object and there comes this JSON.parse() as rescue.

Let’s take a closer look on each of the methods.

JSON.stringify()

Stringify() with JavaScript objects
const obj = {
    name: 'Amitav',
    age: 24,
    designation: 'Software Engineer'
}
​
const objString = JSON.stringify(obj);
​
console.log(objString); 
// "{"name":"Amitav","age":24,"designation":"Software Engineer"}"
Stringify() with JavaScript Arrays
const arr = [1, 2, 'hello','world'];
​
const arrString = JSON.stringify(arr);
​
console.log(arrString); 
// "[1,2,"hello","world"]"

Some more examples:

JSON.stringify(45); // "45"
​
JSON.stringify(true); // "true"
​
JSON.stringify({a:1, b:undefined, c:null}); 
// "{"a":1,"c":null}" -> undefined value will be removed

JSON.stringify() can accept two additional arguments, one is replacer and other is spacer. A replacer can either be a function or an array.

#javascript #programming #developer

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Difference Between JSON.parse() and JSON.stringify()
Autumn  Blick

Autumn Blick

1593251880

JSON Parsing in Android - Step by Step Implementation

JSON Structures in Android

JSON uses two types of brackets that are as follows:

  • [] – To declare the elements of Array in JSON, they’re written in square brackets.
  • {} – To create JSON objects, the elements are written in curly brackets.

JSON has the following types of structures that are:

1. JSON Objects

The elements inside the curly brackets are known as Objects.

2. JSON Array

A list of values, known as Arrays.

3. JSON Key-Value

This data is stored as a pair of keys and values. Here the keys can be a name, a number for which the values can be Seema, 98767586 etc.

Why JSON Parsing in Android over XML?

Let us see some reasons for why to choose JSON over XML:

  • It is much easier and quicker with high performance
  • It can use arrays
  • Its libraries do not depend on other libraries
  • The codes written in JSON are short, clean and easy to understand
  • It is free to open use and open-source tool
  • In JSON value retrieval is easy
  • It has a fully automated way of serializing/deserializing JavaScript.
  • It is supported by many Ajax toolkits and most of the backend technologies.

Examples of XML and JSON

Let us see the code difference of JSON and XML files:

XML Example:

<?xml version= “1.0” encoding= “” ?>
<student>
        <student>
  <name> Sia Sharma</name>
  <city> Chandigarh</city>
         </student>
        <student>
  <name>Dimple D’souza</name>
  <city> Nagpur</city>
         </student>
      <student>
  <name>Anna Jones</name>
  <city> Mumbai</city>
         </student>
  </student>

JSON Example:

{ “students”: [
{ “name”: “Sia Sharma”, “city”: “Chandigarh”},
{ “name”: “Prachi D’Souza”, “city”: “Nagpur”},
{ “name”: “Annas Jones”, “city”: “Mumbai”}
]}

I hope the difference is all clear in front of you. This is how simple JSON is and how easily it could be understood.

#android tutorials #json parsing in android #json parsing in android example #json parsing in android step by step #json parsing with android #read json file android

Brandon  Adams

Brandon Adams

1625637060

What is JSON? | JSON Objects and JSON Arrays | Working with JSONs Tutorial

In this video, we work with JSONs, which are a common data format for most web services (i.e. APIs). Thank you for watching and happy coding!

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Endpoint Example
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#jsons #json arrays #json objects #what is json #jsons tutorial #blondiebytes

Hollie  Ratke

Hollie Ratke

1596800220

Complex JSON parsing with Ansible and JMESPath

JSON has become the lingua franca of the computer world for sharing information between applications. Just about anyone who writes code to interact with Web APIs or retrieve the results of an application will need to know how to parse JSON. Luckily, due to JSON’s popularity, it has wide support and there are many packages, like JMESPath, available to help parse complex JSON structures.

Frequently when I am deploying or updating infrastructure using Ansible I have to parse JSON results from a cloud provider or the output of a command like kubectl when interacting with Kubernetes. The output from these sources often contains a lot of information, parsing all of that information just to get what needed and transforming it into a usable format is often difficult.

In the following example output from kubectl get node node-name -o json , there isn’t an easy way to get the status for the type Ready using Ansible’s native JSON parsing without looping through the list.

{
  "conditions": [
              {
                  "status": "False",
                  "type": "NetworkUnavailable"
              },
              {
                 "status": "False",
                  "type": "MemoryPressure"
              },
              {
                  "status": "False",
                  "type": "DiskPressure"
              },
              {
                  "status": "False",
                  "type": "PIDPressure"
              },
              {
                 "status": "True",
                  "type": "Ready"
              }
  ]
}

However, Ansible has solved this problem by exposing the JMESPath JSON parsing library using the json_query filter.

In this example I will demonstrate how to use Ansible and JMESPath to parse complex JSON output and transform the results into a more usable format by using a key filter and zipping two JSON lists.


For this example, I am using OpenStack Heat to create an 8 node (3 MON nodes and 5 OSD nodes) Ceph cluster that will have Ceph installed using ceph-ansible. Since I am in the development and testing phase of this project, I am frequently creating and destroying the clusters. OpenStack Heat and Ansible do a good job on automating most of the creation and destroying steps, however there was still a manual step where I had to copy the hostnames and ip addresses for the nodes created by OpenStack Heat into Ansible’s inventory file. In order to fully automate the process, I had to capture the output from OpenStack Heat in Ansible so I could automatically generate the inventory file using an Ansible template.

To make the inventory file it mean converting this JSON:

{
    "stack_create.stack.outputs": [
        {
            "description": "Ceph osd management addresses",
            "output_key": "ceph_osd_management_addresses",
            "output_value": [
                "192.168.0.95",
                "192.168.0.101",
                "192.168.0.155",
                "192.168.0.161",
                "192.168.0.23"
            ]
        },
        {
            "description": "Ceph osd server names",
            "output_key": "ceph_osd_server_names",
            "output_value": [
                "ceph-osd-0",
                "ceph-osd-1",
                "ceph-osd-2",
                "ceph-osd-3",
                "ceph-osd-4"
            ]
        },
        {
            "description": "Ceph mon management addresses",
            "output_key": "ceph_mon_management_addresses",
            "output_value": [
                "192.168.0.117",
                "192.168.0.240",
                "192.168.0.44"
            ]
        },
        {
            "description": "Ceph mon server names",
            "output_key": "ceph_mon_server_names",
            "output_value": [
                "ceph-mon-0",
                "ceph-mon-1",
                "ceph-mon-2"
            ]
        }
    ]
}

Into the following inventory file:

[mons]
ceph-mon-0 ansible_host=192.168.0.117 
ceph-mon-1 ansible_host=192.168.0.240 
ceph-mon-2 ansible_host=192.168.0.44
[osds]
ceph-osd-0 ansible_host=192.168.0.95 
ceph-osd-1 ansible_host=192.168.0.101 
ceph-osd-2 ansible_host=192.168.0.155
ceph-osd-3 ansible_host=192.168.0.161
ceph-osd-4 ansible_host=192.168.0.23

In general, Ansible has good native parsing of JSON, however Ansible’s native JSON parsing cannot handle the case, like above, when you need to filter a list of JSON objects based on the value of a key that is in one of the JSON objects. For example, in the above JSON output, I want the list of ip address in the key output_value where output_key = ceph_mon_management_addresses. The best that can be done with Ansible’s native JSON parsing is stack_create.stack.outputs[2].output_value , but that would require the ceph_mon_management_addresses to always be the 3rd item in the list, which cannot be guaranteed.

Here is where Ansible’s json_query filter comes in. With JMESPath we can search a list of objects for a key value pair but return the value of another key in the same object. In practical terms for this example, we can search the list of objects for the object where output_key = ceph_mon_management_addresses and return the value of output_value. Here is the Ansible set_fact task using a JMESPath query to get the result:

- name: Create a list of mon ip addresses
  set_fact:
     mon_ips: "{{ stack_create | json_query(\"stack.outputs[?output_key == ‘ceph_mon_management_addresses’].output_value\") }}"

In this example, the search for the object that contains output_key == ‘ceph_mon_management_addresses’ is done using the JMESPath filter projection (?) with the statement from above. Then we append .output_value to return the value of the output_value key. The results will look like:

[
  [
    "192.168.0.117",
    "192.168.0.240",
    "192.168.0.44"
  ]
]

Since JMESPath is preserving the original format of the JSON, there are two nested lists, the list of objects and the list of ip addresses. We only want a list of ip addresses, therefore we can apply the JMESPath flatten projection to get the output we want. Simply add [] to the end of the statement like so:

- name: Create a list of mon ip addresses
  set_fact:
     mon_ips: "{{ stack_create | json_query(\"stack.outputs[?output_key == ‘ceph_mon_management_addresses’].output_value[]\") }}"

#parse #json #ansible #jmespath #parsing

Hollie  Ratke

Hollie Ratke

1596823200

# Google's Flutter Tutorial- Easily Parse Complex JSON, Create JSON Model Classes.

Welcome to Flutter tutorial

This demo helps you to easily parse any complex JSON data in to Dart Model classe easily.
Proper Error Handling in Flutter
https://www.youtube.com/watch?v=yA_BI

Visit http://coderzheaven.com for more tutorials.

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Please leave your valuable comments in the comment section below.
Thanks for watching.

#json #create-json #json-data #flutter

Giles  Goodwin

Giles Goodwin

1600044000

Creating your own simplified implementation of JSON.stringify()

You may already be familiar with the function JSON.stringify, which can be useful when comparing objects, implementing RESTFUL APIs or simply deep cloning a javascript object (although, it’s not recommended).

In this article, we are going to talk about how to create our own simplified version of this method, and learn how to improve its implementation step by step, covering more and more cases as we progress.

Image for post

If you are not familiar with this function, let’s take a look at what MDN has to say about it:

The **_JSON.stringify()_** method converts a JavaScript object or value to a JSON string, optionally replacing values if a replacer function is specified or optionally including only the specified properties if a replacer array is specified.

Its syntax can be written like this:

JSON.stringify(value[, replacer[, space]])

Where “value” is the object or value we want to convert to a string. We can leave out the other 2 parameters for this article to make it easier.


Testing data

Consider this case:

const sampleObj = {
   "name": "Juan",
   "age": 29,
   "address": {
      "street": "Street 1",
      "number": 3
   }
}

If we apply the origin JSON.stringify() function to that object, this is what we get:

{"name":"Juan","age":29,"address":{"street":"Street 1","number":3}}

As you can see, it’s fairly easy. It adds double quotes to the attributes, and if the value is a string it adds them too. For this particular example, we’ll only tackle those 3 data types: Number, String and Object. We’ll leave out Function, dates, undefined values and so, just to keep it simple, although, I recommend you read the documentation of JSON.stringify to see how it behaves with those types and others.

#js #recursion #javascript #json #json-stringify