How Rust and Go Work

It’s interesting how both Go and Rust fall into the same category but are so fundamentally different in design, philosophy, and execution.

Here are some insights from using both for quite a while.

#rust 

What is GEEK

Buddha Community

Serde Rust: Serialization Framework for Rust

Serde

*Serde is a framework for serializing and deserializing Rust data structures efficiently and generically.*

You may be looking for:

• An overview of Serde
• Data formats supported by Serde
• Setting up #[derive(Serialize, Deserialize)]
• Examples
• API documentation
• Release notes

Serde in action

Click to show Cargo.toml. Run this code in the playground.

[dependencies]

# The core APIs, including the Serialize and Deserialize traits. Always
# required when using Serde. The "derive" feature is only required when
# using #[derive(Serialize, Deserialize)] to make Serde work with structs
# and enums defined in your crate.
serde = { version = "1.0", features = ["derive"] }

# Each data format lives in its own crate; the sample code below uses JSON
# but you may be using a different one.
serde_json = "1.0"

 

use serde::{Serialize, Deserialize};

#[derive(Serialize, Deserialize, Debug)]
struct Point {
    x: i32,
    y: i32,
}

fn main() {
    let point = Point { x: 1, y: 2 };

    // Convert the Point to a JSON string.
    let serialized = serde_json::to_string(&point).unwrap();

    // Prints serialized = {"x":1,"y":2}
    println!("serialized = {}", serialized);

    // Convert the JSON string back to a Point.
    let deserialized: Point = serde_json::from_str(&serialized).unwrap();

    // Prints deserialized = Point { x: 1, y: 2 }
    println!("deserialized = {:?}", deserialized);
}

Getting help

Serde is one of the most widely used Rust libraries so any place that Rustaceans congregate will be able to help you out. For chat, consider trying the #rust-questions or #rust-beginners channels of the unofficial community Discord (invite: https://discord.gg/rust-lang-community), the #rust-usage or #beginners channels of the official Rust Project Discord (invite: https://discord.gg/rust-lang), or the #general stream in Zulip. For asynchronous, consider the [rust] tag on StackOverflow, the /r/rust subreddit which has a pinned weekly easy questions post, or the Rust Discourse forum. It's acceptable to file a support issue in this repo but they tend not to get as many eyes as any of the above and may get closed without a response after some time.

Download Details:
Author: serde-rs
Source Code: https://github.com/serde-rs/serde
License: View license

#rust  #rustlang 

What's new in the go 1.15

Go announced Go 1.15 version on 11 Aug 2020. Highlighted updates and features include Substantial improvements to the Go linker, Improved allocation for small objects at high core counts, X.509 CommonName deprecation, GOPROXY supports skipping proxies that return errors, New embedded tzdata package, Several Core Library improvements and more.

As Go promise for maintaining backward compatibility. After upgrading to the latest Go 1.15 version, almost all existing Golang applications or programs continue to compile and run as older Golang version.

#go #golang #go 1.15 #go features #go improvement #go package #go new features

Rust vs Go - Which Is More Popular?

Go and Rust are two of the hottest compiled programming languages. I develop in Go full-time and love it, and I’m learning more about Rust recently – its an exciting language. Let’s explore some differences between the two and look at which is growing faster in the popularity polls.

#Engineering #Golang #Programming #Rust #comparison #go #popular #rust

Serde JSON: JSON Support for Serde Framework

Serde JSON

Serde is a framework for serializing and deserializing Rust data structures efficiently and generically.

[dependencies]
serde_json = "1.0"

You may be looking for:

• JSON API documentation
• Serde API documentation
• Detailed documentation about Serde
• Setting up #[derive(Serialize, Deserialize)]
• Release notes

JSON is a ubiquitous open-standard format that uses human-readable text to transmit data objects consisting of key-value pairs.

{
    "name": "John Doe",
    "age": 43,
    "address": {
        "street": "10 Downing Street",
        "city": "London"
    },
    "phones": [
        "+44 1234567",
        "+44 2345678"
    ]
}

There are three common ways that you might find yourself needing to work with JSON data in Rust.

• As text data. An unprocessed string of JSON data that you receive on an HTTP endpoint, read from a file, or prepare to send to a remote server.
• As an untyped or loosely typed representation. Maybe you want to check that some JSON data is valid before passing it on, but without knowing the structure of what it contains. Or you want to do very basic manipulations like insert a key in a particular spot.
• As a strongly typed Rust data structure. When you expect all or most of your data to conform to a particular structure and want to get real work done without JSON's loosey-goosey nature tripping you up.

Serde JSON provides efficient, flexible, safe ways of converting data between each of these representations.

Operating on untyped JSON values

Any valid JSON data can be manipulated in the following recursive enum representation. This data structure is serde_json::Value.

enum Value {
    Null,
    Bool(bool),
    Number(Number),
    String(String),
    Array(Vec<Value>),
    Object(Map<String, Value>),
}

A string of JSON data can be parsed into a serde_json::Value by the serde_json::from_str function. There is also from_slice for parsing from a byte slice &[u8] and from_reader for parsing from any io::Read like a File or a TCP stream.

use serde_json::{Result, Value};

fn untyped_example() -> Result<()> {
    // Some JSON input data as a &str. Maybe this comes from the user.
    let data = r#"
        {
            "name": "John Doe",
            "age": 43,
            "phones": [
                "+44 1234567",
                "+44 2345678"
            ]
        }"#;

    // Parse the string of data into serde_json::Value.
    let v: Value = serde_json::from_str(data)?;

    // Access parts of the data by indexing with square brackets.
    println!("Please call {} at the number {}", v["name"], v["phones"][0]);

    Ok(())
}

The result of square bracket indexing like v["name"] is a borrow of the data at that index, so the type is &Value. A JSON map can be indexed with string keys, while a JSON array can be indexed with integer keys. If the type of the data is not right for the type with which it is being indexed, or if a map does not contain the key being indexed, or if the index into a vector is out of bounds, the returned element is Value::Null.

When a Value is printed, it is printed as a JSON string. So in the code above, the output looks like Please call "John Doe" at the number "+44 1234567". The quotation marks appear because v["name"] is a &Value containing a JSON string and its JSON representation is "John Doe". Printing as a plain string without quotation marks involves converting from a JSON string to a Rust string with as_str() or avoiding the use of Value as described in the following section.

The Value representation is sufficient for very basic tasks but can be tedious to work with for anything more significant. Error handling is verbose to implement correctly, for example imagine trying to detect the presence of unrecognized fields in the input data. The compiler is powerless to help you when you make a mistake, for example imagine typoing v["name"] as v["nmae"] in one of the dozens of places it is used in your code.

Parsing JSON as strongly typed data structures

Serde provides a powerful way of mapping JSON data into Rust data structures largely automatically.

use serde::{Deserialize, Serialize};
use serde_json::Result;

#[derive(Serialize, Deserialize)]
struct Person {
    name: String,
    age: u8,
    phones: Vec<String>,
}

fn typed_example() -> Result<()> {
    // Some JSON input data as a &str. Maybe this comes from the user.
    let data = r#"
        {
            "name": "John Doe",
            "age": 43,
            "phones": [
                "+44 1234567",
                "+44 2345678"
            ]
        }"#;

    // Parse the string of data into a Person object. This is exactly the
    // same function as the one that produced serde_json::Value above, but
    // now we are asking it for a Person as output.
    let p: Person = serde_json::from_str(data)?;

    // Do things just like with any other Rust data structure.
    println!("Please call {} at the number {}", p.name, p.phones[0]);

    Ok(())
}

This is the same serde_json::from_str function as before, but this time we assign the return value to a variable of type Person so Serde will automatically interpret the input data as a Person and produce informative error messages if the layout does not conform to what a Person is expected to look like.

Any type that implements Serde's Deserialize trait can be deserialized this way. This includes built-in Rust standard library types like Vec<T> and HashMap<K, V>, as well as any structs or enums annotated with #[derive(Deserialize)].

Once we have p of type Person, our IDE and the Rust compiler can help us use it correctly like they do for any other Rust code. The IDE can autocomplete field names to prevent typos, which was impossible in the serde_json::Value representation. And the Rust compiler can check that when we write p.phones[0], then p.phones is guaranteed to be a Vec<String> so indexing into it makes sense and produces a String.

The necessary setup for using Serde's derive macros is explained on the Using derive page of the Serde site.

Constructing JSON values

Serde JSON provides a json! macro to build serde_json::Value objects with very natural JSON syntax.

use serde_json::json;

fn main() {
    // The type of `john` is `serde_json::Value`
    let john = json!({
        "name": "John Doe",
        "age": 43,
        "phones": [
            "+44 1234567",
            "+44 2345678"
        ]
    });

    println!("first phone number: {}", john["phones"][0]);

    // Convert to a string of JSON and print it out
    println!("{}", john.to_string());
}

The Value::to_string() function converts a serde_json::Value into a String of JSON text.

One neat thing about the json! macro is that variables and expressions can be interpolated directly into the JSON value as you are building it. Serde will check at compile time that the value you are interpolating is able to be represented as JSON.

let full_name = "John Doe";
let age_last_year = 42;

// The type of `john` is `serde_json::Value`
let john = json!({
    "name": full_name,
    "age": age_last_year + 1,
    "phones": [
        format!("+44 {}", random_phone())
    ]
});

This is amazingly convenient, but we have the problem we had before with Value: the IDE and Rust compiler cannot help us if we get it wrong. Serde JSON provides a better way of serializing strongly-typed data structures into JSON text.

Creating JSON by serializing data structures

A data structure can be converted to a JSON string by serde_json::to_string. There is also serde_json::to_vec which serializes to a Vec<u8> and serde_json::to_writer which serializes to any io::Write such as a File or a TCP stream.

use serde::{Deserialize, Serialize};
use serde_json::Result;

#[derive(Serialize, Deserialize)]
struct Address {
    street: String,
    city: String,
}

fn print_an_address() -> Result<()> {
    // Some data structure.
    let address = Address {
        street: "10 Downing Street".to_owned(),
        city: "London".to_owned(),
    };

    // Serialize it to a JSON string.
    let j = serde_json::to_string(&address)?;

    // Print, write to a file, or send to an HTTP server.
    println!("{}", j);

    Ok(())
}

Any type that implements Serde's Serialize trait can be serialized this way. This includes built-in Rust standard library types like Vec<T> and HashMap<K, V>, as well as any structs or enums annotated with #[derive(Serialize)].

Performance

It is fast. You should expect in the ballpark of 500 to 1000 megabytes per second deserialization and 600 to 900 megabytes per second serialization, depending on the characteristics of your data. This is competitive with the fastest C and C++ JSON libraries or even 30% faster for many use cases. Benchmarks live in the serde-rs/json-benchmark repo.

Getting help

Serde is one of the most widely used Rust libraries, so any place that Rustaceans congregate will be able to help you out. For chat, consider trying the #rust-questions or #rust-beginners channels of the unofficial community Discord (invite: https://discord.gg/rust-lang-community), the #rust-usage or #beginners channels of the official Rust Project Discord (invite: https://discord.gg/rust-lang), or the #general stream in Zulip. For asynchronous, consider the [rust] tag on StackOverflow, the /r/rust subreddit which has a pinned weekly easy questions post, or the Rust Discourse forum. It's acceptable to file a support issue in this repo, but they tend not to get as many eyes as any of the above and may get closed without a response after some time.

No-std support

As long as there is a memory allocator, it is possible to use serde_json without the rest of the Rust standard library. This is supported on Rust 1.36+. Disable the default "std" feature and enable the "alloc" feature:

[dependencies]
serde_json = { version = "1.0", default-features = false, features = ["alloc"] }

For JSON support in Serde without a memory allocator, please see the serde-json-core crate.

Link: https://crates.io/crates/serde_json

#rust  #rustlang  #encode   #json 

Rust vs. Go: Should I Rust, or Should I Go

“Should I stay, or should I go?” Great song by the band The Clash. I’m listening to it, right now, while I’m writing this article. The song debuted back in 1982, a long time ago. Back then, I was just a kid exploring a new hobby — programming my Atari 2600. The first video game I ever wrote was written using 6502 Assembly for that console. The compiler for it cost about $65, if I recall, which at the time equated to mowing ~13 or so lawns.

The game was simple: using the joystick, maneuver your spaceship through a randomly generated scrolling cave. The cave walls were sinusoidal, scrolling vertically on the left and right sides of the screen, and you had to make sure your craft didn’t crash into them. I know, I know: Not that sophisticated. But I was only ten or eleven years old at the time.

Despite the “power” of the processor, computing sine values at run-time was simply too much for it. So, using my handy Texas Instruments calculator, I pre-calculated a bunch of the sine values, carefully writing them down on paper, and then entering them in as constants for the game. This greatly enhanced the performance of the game, and made it usable.

So what’s my point? What’s any of this got to do with Rust or Go?

Today’s languages are far more advanced than 6502 Assembly, which make it easier to write complex programs. It took a lot of my time to write that game, and I could do it much faster today, with less code than I did back then. But which language today provides that magic combination of simplicity and power?

Well both Rust and Go provide amazing performance. They both compile to machine code, the Holy Grail of performance. And with today’s processing power, developers can do amazing things with either of these languages. So the question is: Should you write you’re next big thing with Rust or with Go?

With a quick search, you can easily find several articles that go into detail about the differences between the two languages. But the focus of this article is the bang for the buck, that magic combination of performance per line of code.

To put it another way, where is that sweet spot of simple code and top-end performance? And in this case, is it Rust, or is it Go?
There really isn’t any argument: Rust is faster than Go. In the benchmarks above, Rust was faster, and in some cases, an order of magnitude faster.

But before you run off choosing to write everything in Rust, consider that Go wasn’t that far behind it in many of those benchmarks, and it’s still much faster than the likes of Java, C#, JavaScript, Python and so on. So in other words, it’s almost a wash between Rust and Go on the axis of performance. Now, if what you’re building needs to wring out every last ounce of performance, then by all means, choose Rust. But if what you need is top-of-the-line performance, then you’ll be ahead of the game choosing either of these two languages.

So then we’re down to the complexity of the code. This is where things can be muddy since this can be more subjective than performance benchmarks. Let’s look at a simple exercise: building a small web server that prints out “Hello World” when it receives an HTTP request. To do this in Rust, it looks something like this:

use std::net::{TcpStream, TcpListener};
use std::io::{Read, Write};
use std::thread;


fn handle_read(mut stream: &TcpStream) {
    let mut buf = [0u8; 4096];
    match stream.read(&mut buf) {
        Ok(_) => {
            let req_str = String::from_utf8_lossy(&buf);
            println!("{}", req_str);
            },
        Err(e) => println!("Unable to read stream: {}", e),
    }
}

fn handle_write(mut stream: TcpStream) {
    let response = b"HTTP/1.1 200 OK\r\nContent-Type: text/html; charset=UTF-8\r\n\r\n<html><body>Hello world</body></html>\r\n";
    match stream.write(response) {
        Ok(n) => println!("Response sent: {} bytes", n),
        Err(e) => println!("Failed sending response: {}", e),
    }
}

fn handle_client(stream: TcpStream) {
    handle_read(&stream);
    handle_write(stream);
}

fn main() {
    let port = "8080";
    let listener = TcpListener::bind(format!("127.0.0.1:{}", port)).unwrap();
    println!("Listening for connections on port {}", port);

    for stream in listener.incoming() {
        match stream {
            Ok(stream) => {
                thread::spawn(|| {
                    handle_client(stream)
                });
            }
            Err(e) => {
                println!("Unable to connect: {}", e);
            }
        }
    }
}

Something pretty similar in Go looks like this:

package main

import (
	"fmt"
	"io"
	"log"
	"net/http"
)

type handler struct{}

func (theHandler *handler) ServeHTTP(writer http.ResponseWriter, request *http.Request) {
	log.Printf("Received request: %s\n", request.URL)
	log.Printf("%v\n", request)
	io.WriteString(writer, "Hello world!")
}

const port = "8080"

func main() {
	server := http.Server{
		Addr:    fmt.Sprintf(":%s", port),
		Handler: &handler{},
	}

	server.ListenAndServe()
}

Now, they are not 100% exactly the same, but they are close enough. The difference between them is ~20 lines of code. Rust definitely forces the developer to consider more, and thus write more code than Go.

Another example: Consider one of the more difficult aspects of software development: multi-threading. When tackling something like this, as you undoubtedly would when building an HTTP server, there’s a lot to think about:

• You need to ensure everything you design is thread safe (locks)
• You need to handle communication between threads (channels)
• You have to design with concurrency and parallelism in mind (threads and routines)

Both Rust and Go handle these hurdles really efficiently, but Go requires less effort. With Rust, you have way more options, and thus more power, when spawning threads. Just look at some of the documentation on this. Here’s just one way to spawn a thread in Rust:

use std::thread;

let handler = thread::spawn(|| {
    // thread code
});

handler.join().unwrap();

On the other hand, here’s how to create something similar using Go:

go someFunction(args)

Another crucial part of writing code is handling errors. Here I think Rust and Go are quite similar. Rust enables the developer to handle errors cases through the use of the enum return types: Option<T>and Result<T, E>. The Option<T> will return either None or Some(T) whereas Result<T, E> will return either Ok(T) or Err(T). Given that most of Rust’s own libraries, as well as other third-party libraries, return one of these types, the developer will usually have to handle the case where nothing is returned, or where an error is returned.

Here’s a simple example of the Result type being returned by a function in Rust:

fn foo_divide(a: f32, b: f32) -> Result<f32, &'static str> {
    if b == 0.0 {
        Err("divide by zero error!")
    } else {
        Ok(a / b)
    }
}fn main() {
    match foo_divide(5.0, 4.0) {
        Err(err) => println!("{}", err),
        Ok(result) => println!("5 / 4 = {}", result),
    }
}

Notice that the Err case must be handled within the match statement.

Go, on the other hand, leaves this more up to the developer, since errors can be ignored using the _. However, idiomatic Go strongly recommends returning an error, especially since functions in Go can return multiple values. Therefore, it’s easy to have functions return their intended value along with an error, if there is one.

Here is the corresponding example from above done in Go:

func fooDivide(a float32, b float32) (float32, error) {
    if b == 0 {
        return 0, errors.New("divide by zero error!")
    }    return a / b, nil
}func main() {
    result, err := fooDivide(5, 4)
    if err != nil {
       log.Printf("an error occurred: %v", err)
    } else {
       log.Printf("The answer is: 5 / 4 = %f", result)
    }
}

Notice that this line:

result, err := fooDivide(5, 4)

could have been written as

result, _ := fooDivide(5, 4)

In the latter case, the error returned would have been ignored.

Honestly, they’re both pretty similar, except for Rust forcing error checking. Otherwise, there’s little difference, and it’s difficult to find an advantage one has over the other. To my eyes, this is a draw.

I could keep going, digging deeper into other language differences. But the bottom line, from threads, to channels, to generics, Rust provides the developer with more options. In this respect, Rust is closer to C++ than Go. Does this make Rust inherently more complex?

I think so, yes.

So here are my recommendations:

• Either. If you’re building a web service that handles high load, that you want to be able to scale both vertically and horizontally, either language will suit you perfectly.
• Go. But if you want to write it faster, perhaps because you have many different services to write, or you have a large team of developers, then Go is your language of choice. Go gives you concurrency as a first-class citizen, and does not tolerate unsafe memory access (neither does Rust), but without forcing you to manage every last detail. Go is fast and powerful, but it avoids bogging the developer down, focusing instead on simplicity and uniformity.
• Rust. If on the other hand, wringing out every last ounce of performance is a necessity, then Rust should be your choice. Rust is more of a competitor to C++ than it is with Go. Having battled with C++, Rust feels just as powerful but with many happy improvements. Rust empowers developers to have control over every last detail of how their threads behave with the rest of the system, how errors should be handled, and even the lifetime of their variables!
• Rust. Rust was designed to interoperate with C. Go can as well, but gives up a lot to achieve this goal, and it’s not really its focus.
• Go. If readability is a requirement, go with Go. It’s far too easy to make your code hard for others to grok with Rust.

I hope you enjoyed reading this!

#go #rust #webdev