Charles Cooper

Charles Cooper

1600695659

JSON and Rust: Why serde_json is The Top Choice

JSON support is very much production-ready and arguably best in class compared to other mainstream languages.

JSON has become one of the most common data exchange formats on the web, so it’s critical that server-side languages have good support for it. Fortunately, dealing with JSON is an area where Rust shines, thanks in large part to the serde and serde_json crates. These are among the most battle-tested crates in the Rust ecosystem and serve as great examples of ways to exploit Rust’s high-level abstractions while maintaining low-level control.

While there are plenty of other JSON crates available, serde_json is by far the most popular. The large ecosystem built around serde makes it the top choice for web servers written in Rust.

In this tutorial, we’ll explore serde_json and demonstrate how to use Rust’s type system to express JSON data.

Getting started

To get started with serde_json, you must first implement the Serialize and Deserialize traits on your types. Thanks to derive macros, this is really trivial for most types. To use derive macros, make sure you enable the “derive” feature flag for serde in your dependencies.

## cargo.toml

[dependencies]
serde = { version = "1", features = ["derive"] }
serde_json = "1"

Now we can use them like any other derive macro.

use serde::{Deserialize, Serialize};

#[derive(Debug, Deserialize, Serialize)]
struct Person {
    name: String,
    age: usize,
    verified: bool,
}

That’s all you need to do to make Person serializable and deserializable into any data format with a crate that supports serde. Debug is optional, but we’ll use it for demonstration purposes. Converting a JSON string into an instance of Person is now as simple as calling serde_json::from_str.

fn main() {
    let json = r#"
        {
          "name": "George",
          "age": 27,
          "verified": false
        }
    "#;

    let person: Person = serde_json::from_str(json).unwrap();

    println!("{:?}", person);
}

There are a couple of things to point out here, the first being the explicit Person type annotation. In this example, there is no way for the compiler to infer the type of person; it could potentially be any type that implements Deserialize. In more complete examples it would be inferred from things like function argument types when passing around person.

The other thing to note is the call to unwrap(). Deserialization can fail in a number of ways, so serde_json::from_str returns a Result to let us handle those failures. Errors from serde_json are quite rich and give us enough information to pin down exactly what went wrong. For example, running the same code as above with the age field removed triggers the following error message.

Error("missing field `age`", line: 5, column: 9)

You would get a similar message if there were syntax errors in the JSON. Instead of using unwrap, you can extract the same information seen above by using the methods provided by serde_json::Error and handle the error gracefully whenever possible.

One of my favorite things about using JSON in Rust is that it provides complete type checking with zero boilerplate code and error handling that is enforced at compile time thanks to the Result type. The places where you use JSON are almost always at system boundaries where you can receive all kinds of unexpected inputs. Having first-class, consistent support for error handling makes dealing with these system boundaries much more enjoyable and reliable.

#rust #json #javascript #programming #developer

What is GEEK

Buddha Community

JSON and Rust: Why serde_json is The Top Choice
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!

Need some new tech gadgets or a new charger? Buy from my Amazon Storefront https://www.amazon.com/shop/blondiebytes

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https://chrome.google.com/webstore/detail/json-formatter/bcjindcccaagfpapjjmafapmmgkkhgoa?hl=en

Endpoint Example
http://maps.googleapis.com/maps/api/geocode/json?address=13+East+60th+Street+New+York,+NY

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

Charles Cooper

Charles Cooper

1600695659

JSON and Rust: Why serde_json is The Top Choice

JSON support is very much production-ready and arguably best in class compared to other mainstream languages.

JSON has become one of the most common data exchange formats on the web, so it’s critical that server-side languages have good support for it. Fortunately, dealing with JSON is an area where Rust shines, thanks in large part to the serde and serde_json crates. These are among the most battle-tested crates in the Rust ecosystem and serve as great examples of ways to exploit Rust’s high-level abstractions while maintaining low-level control.

While there are plenty of other JSON crates available, serde_json is by far the most popular. The large ecosystem built around serde makes it the top choice for web servers written in Rust.

In this tutorial, we’ll explore serde_json and demonstrate how to use Rust’s type system to express JSON data.

Getting started

To get started with serde_json, you must first implement the Serialize and Deserialize traits on your types. Thanks to derive macros, this is really trivial for most types. To use derive macros, make sure you enable the “derive” feature flag for serde in your dependencies.

## cargo.toml

[dependencies]
serde = { version = "1", features = ["derive"] }
serde_json = "1"

Now we can use them like any other derive macro.

use serde::{Deserialize, Serialize};

#[derive(Debug, Deserialize, Serialize)]
struct Person {
    name: String,
    age: usize,
    verified: bool,
}

That’s all you need to do to make Person serializable and deserializable into any data format with a crate that supports serde. Debug is optional, but we’ll use it for demonstration purposes. Converting a JSON string into an instance of Person is now as simple as calling serde_json::from_str.

fn main() {
    let json = r#"
        {
          "name": "George",
          "age": 27,
          "verified": false
        }
    "#;

    let person: Person = serde_json::from_str(json).unwrap();

    println!("{:?}", person);
}

There are a couple of things to point out here, the first being the explicit Person type annotation. In this example, there is no way for the compiler to infer the type of person; it could potentially be any type that implements Deserialize. In more complete examples it would be inferred from things like function argument types when passing around person.

The other thing to note is the call to unwrap(). Deserialization can fail in a number of ways, so serde_json::from_str returns a Result to let us handle those failures. Errors from serde_json are quite rich and give us enough information to pin down exactly what went wrong. For example, running the same code as above with the age field removed triggers the following error message.

Error("missing field `age`", line: 5, column: 9)

You would get a similar message if there were syntax errors in the JSON. Instead of using unwrap, you can extract the same information seen above by using the methods provided by serde_json::Error and handle the error gracefully whenever possible.

One of my favorite things about using JSON in Rust is that it provides complete type checking with zero boilerplate code and error handling that is enforced at compile time thanks to the Result type. The places where you use JSON are almost always at system boundaries where you can receive all kinds of unexpected inputs. Having first-class, consistent support for error handling makes dealing with these system boundaries much more enjoyable and reliable.

#rust #json #javascript #programming #developer

Lokesh Kumar

1603438098

Top 10 Trending Technologies Must Learn in 2021 | igmGuru

Technology has taken a place of more productiveness and give the best to the world. In the current situation, everything is done through the technical process, you don’t have to bother about doing task, everything will be done automatically.This is an article which has some important technologies which are new in the market are explained according to the career preferences. So let’s have a look into the top trending technologies followed in 2021 and its impression in the coming future in the world.

  1. Data Science
    First in the list of newest technologies is surprisingly Data Science. Data Science is the automation that helps to be reasonable for complicated data. The data is produces in a very large amount every day by several companies which comprise sales data, customer profile information, server data, business data, and financial structures. Almost all of the data which is in the form of big data is very indeterminate. The character of a data scientist is to convert the indeterminate datasets into determinate datasets. Then these structured data will examine to recognize trends and patterns. These trends and patterns are beneficial to understand the company’s business performance, customer retention, and how they can be enhanced.

  2. DevOps
    Next one is DevOps, This technology is a mixture of two different things and they are development (Dev) and operations (Ops). This process and technology provide value to their customers in a continuous manner. This technology plays an important role in different aspects and they can be- IT operations, development, security, quality, and engineering to synchronize and cooperate to develop the best and more definitive products. By embracing a culture of DevOps with creative tools and techniques, because through that company will gain the capacity to preferable comeback to consumer requirement, expand the confidence in the request they construct, and accomplish business goals faster. This makes DevOps come into the top 10 trending technologies.

  3. Machine learning
    Next one is Machine learning which is constantly established in all the categories of companies or industries, generating a high command for skilled professionals. The machine learning retailing business is looking forward to enlarging to $8.81 billion by 2022. Machine learning practices is basically use for data mining, data analytics, and pattern recognition. In today’s scenario, Machine learning has its own reputed place in the industry. This makes machine learning come into the top 10 trending technologies. Get the best machine learning course and make yourself future-ready.

To want to know more click on Top 10 Trending Technologies in 2021

You may also read more blogs mentioned below

How to Become a Salesforce Developer

Python VS R Programming

The Scope of Hadoop and Big Data in 2021

#top trending technologies #top 10 trending technologies #top 10 trending technologies in 2021 #top trending technologies in 2021 #top 5 trending technologies in 2021 #top 5 trending technologies

Rust Lang Course For Beginner In 2021: Guessing Game

 What we learn in this chapter:
- Rust number types and their default
- First exposure to #Rust modules and the std::io module to read input from the terminal
- Rust Variable Shadowing
- Rust Loop keyword
- Rust if/else
- First exposure to #Rust match keyword

=== Content:
00:00 - Intro & Setup
02:11 - The Plan
03:04 - Variable Secret
04:03 - Number Types
05:45 - Mutability recap
06:22 - Ask the user
07:45 - First intro to module std::io
08:29 - Rust naming conventions
09:22 - Read user input io:stdin().read_line(&mut guess)
12:46 - Break & Understand
14:20 - Parse string to number
17:10 - Variable Shadowing
18:46 - If / Else - You Win, You Loose
19:28 - Loop
20:38 - Match
23:19 - Random with rand
26:35 - Run it all
27:09 - Conclusion and next episode

#rust 

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