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  1. DZone
  2. Coding
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  4. Embracing Asynchrony in Java, Python, JavaScript, and Go

Embracing Asynchrony in Java, Python, JavaScript, and Go

The article discusses asynchrony in four languages, emphasizing its role in creating efficient, responsive applications.

By 
Andrei Tetka user avatar
Andrei Tetka
·
Apr. 07, 23 · Review
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As a software developer with years of experience working primarily with Java, I found myself intrigued when I recently switched to Python for a new project. The transition prompted me to explore the world of asynchronous programming in various languages, including Java, Python, JavaScript, and Golang. This article is a result of my exploration and personal experience with these languages, aiming to provide insight into asynchronous programming techniques and examples.

Asynchronous Programming in Java

When I first started programming in Java, I quickly became familiar with the concept of threads. Over time, I found that the Executor framework and CompletableFuture class offered more powerful and flexible ways to handle asynchronous operations.

For example, I used the Executor framework to build a web scraper that fetched data from multiple websites concurrently. By using a fixed thread pool, I was able to limit the number of simultaneous connections while efficiently managing resources:

Java
 
ExecutorService executor = Executors.newFixedThreadPool(10);
for (String url : urls) {
    executor.submit(() -> {
        // Fetch data from the URL and process it
    });
}
executor.shutdown();
executor.awaitTermination(Long.MAX_VALUE, TimeUnit.MILLISECONDS);


Asynchronous Programming in Python

Switching to Python, I was initially challenged by the different approaches to asynchronous programming. However, after learning about the asyncio library and the async/await syntax, I found it to be a powerful and elegant solution.

I once implemented a Python-based microservice that needed to make multiple API calls. By leveraging asyncio and async/await, I was able to execute these calls concurrently and significantly reduce the overall response time:

Python
 
import aiohttp
import asyncio

async def fetch(url):
    async with aiohttp.ClientSession() as session:
        async with session.get(url) as response:
            return await response.text()

async def main():
    urls = [...]  # List of URLs
    tasks = [fetch(url) for url in urls]
    responses = await asyncio.gather(*tasks)

asyncio.run(main())


Asynchronous Programming in JavaScript

When working with JavaScript, I appreciated its innate support for asynchronous programming. As a result, I have used callbacks, promises, and async/await extensively in various web applications.

For example, I once built a Node.js application that required data from multiple RESTful APIs. By using promises and async/await, I was able to simplify the code and handle errors more gracefully:

JavaScript
 
const axios = require("axios");

async function fetchData(urls) {
    const promises = urls.map(url => axios.get(url));
    const results = await Promise.all(promises);
    // Process the results
}

const urls = [...]  // List of URLs
fetchData(urls);


Asynchronous Programming in Golang

During my exploration of Golang, I was fascinated by its native support for concurrency and asynchronous programming, thanks to goroutines and channels.

For example, while working on a project that required real-time processing of data from multiple sources, I utilized goroutines and channels to manage resources effectively and synchronize the flow of data:

Go
 
package main

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

func processSource(url string, ch chan<- string) {
    resp, err := http.Get(url)
    if err != nil {
        ch <- fmt.Sprintf("Error fetching data from %s: %v", url, err)
        return
    }
    defer resp.Body.Close()
    body, err := ioutil.ReadAll(resp.Body)
    // Process the fetched data
    ch <- fmt.Sprintf("Processed data from %s", url)
}

func main() {
    sources := [...]  // List of data sources
    ch := make(chan string, len(sources))

    for _, url := range sources {
        go processSource(url, ch)
    }

    for range sources {
        fmt.Println(<-ch)
    }
}


Conclusion

Asynchronous programming is a crucial aspect of modern application development, and having a deep understanding of its implementation across various languages is invaluable. My experiences with Java, Python, JavaScript, and Golang have taught me that each language has its unique and powerful features for managing asynchronous tasks. By sharing these experiences and examples, I aim to encourage others to embrace asynchrony in their projects, ultimately leading to more efficient and responsive applications.

Golang JavaScript Software developer Data (computing) Java (programming language) Python (language)

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  • An Overview of Programming Languages
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