Trending December 2023 # How To Throw An Error In An Async Generator Function In Javascript # Suggested January 2024 # Top 21 Popular

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The code often throws an error, and handling errors is more important. JavaScript also allows users to throw a custom error using the ‘throw’ keyword. We can catch the errors in the catch block.

We can use the try-catch syntax to catch errors thrown by normal functions. Let’s understand it by the example below.

Example 1 (Throw Errors in Regular Function)

In the example below, we have created the throwError() regular function, which uses the throw keyword to throw an error with the custom error message. We have executed the function inside the try block. If the function throws any error, controls go to the catch block, and that’s how we can detect the error.

let content = document.getElementById(‘content’); function throwError() { throw new Error(‘Error from normal function’); } try { throwError(); } catch (e) { content.innerHTML = e; }

If we make the throwError() function asynchronous, it will generate another error, as we can handle the errors thrown by the synchronous function using the try-catch block.

To solve the problem, users must use the then-catch block syntax to resolve the promises.

Syntax

Users can follow the syntax below to resolve the errors the async function throws.

// print content })

In the above syntax, throwError() is a function that returns the promises, which we solve using the then and catch block.

Example 2 (Throw Error From Async Function)

In the example below, the throwError() function is an asynchronous function, as we have added the ‘async’ keyword before the function keyword. We have thrown the error from the async function as we throw from the regular function.

After that, we handled the promise using the then and catch block. In the output, users can observe that as the async function throws an error, control goes to the catch block.

let content = document.getElementById(‘content’); async function throwError() { throw new Error(‘Error from Async function’); } content.innerHTML = res; content.innerHTML = err; }) Example 3 (Throw Error by Rejecting Promise in Async Function)

We can return the promises from the async function. The rejecting promise in the async function works like throwing the error. We have used the reject() method inside the callback function to reject the promise.

The ‘then-catch’ block is used to resolve the promise returned by function, and users can see that controls go to the catch block.

let content = document.getElementById(‘content’); async function throwError() { reject(“This promise is rejected from the async function.” ); }); } content.innerHTML = res; content.innerHTML = err; })

Users learned to throw an error from the asynchronous function. Users can use the ‘throw’ keyword like the regular function to throw an error. Users need to handle the error using the ‘then-catch’ block as the async function returns the promise rather than handling using the try-catch block.

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How To Use An Iterating Function In Power Bi

This tutorial will teach you about different iterating functions and how to efficiently use them in your calculations.

I often discuss how calculated columns are not required when making some calculations. This is because of iterators.

Iterators or iterating functions can help you do a calculation without physically putting the results in the table.

This technique can help you save up on the memory needed to load your Power BI data model. In the next sections, I’ll show you how to optimize your calculations using iterators.

To get started, create a new measure for Total Costs. Make sure to select the measure group where you want this new measure to land.

Press Shift and Enter to move down a line before you put the first iterating function, which is SUMX.

In the formula bar of Power BI, you can already see exactly what you need to put after the function as suggested by IntelliSense. For SUMX, you need to add a table after it.

The SUMX formula will run the logic at every single row of the given table. This is why iterators are associated with row context. Within the measure, iterators can turn the formula into a row context.

You will need to reference the Sales table after the SUMX function. To calculate the total costs, you have to multiply Order Quantity by Total Unit Cost.

We don’t need to reference the new column that was created at all. The Total Costs is a measure and I can bring it into my table to evaluate our total costs.

Now, drag the measure inside the table to see the results. Make sure that you selected an initial context from the City filter.

The Total Costs works in a similar way in terms of the initial context. The initial context gets applied to the Sales table, but then within each of these individual results, we’re calculating the Order Quantity multiplied by the Total Unit Cost.

Behind the scenes in our data model, we have turned on our filter and we have context coming in from our Regions table and another context coming in from our Date table. These flow down to our Sales table, which is filtered by the iterating function SUMX.

Since the SUMX function evaluates every single row of the Sales table virtually, there’s no need for a physical column for the results.

After the initial context, SUMX gets the product of Order Quantity and Total Unit Cost for every single row. Lastly, it evaluates all the calculated results from all the rows.

If you noticed, the original Costs column was created through a calculated column. As I’ve said, it’s unnecessary since iterators can already do its work. You can delete it because it can take up unnecessary memory in your model.

Iterating formulas run evaluations at every single row, while aggregating formulas do not.

A lot of this information is covered in-depth in the Mastering DAX course, but this is just to show you the the beginnings of iterating functions and how to start using them when it’s appropriate.

If you feel the need to create a calculated column inside your fact table, I can almost guarantee that an iterating function will do the work for you.

Now, I’ll show you another example of how iterators can do wonders on your calculation. This time, let’s work out the average cost.

Just copy the Total Costs formula and paste it into a new measure. You just have to change the name to Average Costs and then use AVERAGEX instead of SUMX.

The new formula runs a similar logic because it evaluates every single row of the Sales table. Additionally, you still need to get the product of Order Quantity and Total Unit Cost. The only difference here is instead of sum, the formula calculates the average.

Now, if you bring the Average Costs measure to the table, you can see how it compares to the Total Costs measure.

It’s amazing how you can run a similar logic just by changing the iterating function.

To optimize your table, you can delete redundant information like the Total Revenue column.

Since you can readily achieve the average costs, you won’t need the Total Revenue column in your table anymore. As long as you have the Unit Price and the Total Unit Cost columns, everything’s fine.

Now, you can create a new measure instead for Total Sales (Iteration) by using the SUMX function. You just have to reference the Sales table then get the product of Order Quantity and Unit Price.

After that, you can compare the results in the Total Sales and Total Sales (Iteration) columns. They both have the same results, right?

In terms of performance, there’s not much of a difference between using calculated columns and iterators. But when it comes to the data model, an iterator function can get rid of an entire column and save you hundreds of rows of data.

Additionally, you can delete redundant columns because iterators can calculate the necessary results virtually. This practice will make your table a lot thinner and your model a lot faster. Make sure you apply this optimization technique in your own calculations.

To sum up, an iterating function evaluates every single row while aggregators don’t.

The letter X on the end of the function makes it easier to identify iterators. Examples include the SUMX, AVERAGEX, MAXX, MINX functions and more.

Using iterating functions won’t create additional physical tables. This can help you save memory in Power BI.

All the best!

Sam

Javascript Convert An Array To Json

An array is a special object in JavaScript, that stores multiple types of values which means that it can store an integer value, string value, or float value simultaneously. There are various ways to create an array in JavaScript, following is the syntax to do so −

var array = [value1, value2, value3,…]; or var array = new Array(size); or var array = new Array(element1, element2,…);

Where the value is the elements of the array so it can be of any type.

The JSON is an object notation in JavaScript that is used to represent structured data based on the JavaScript object syntax. It is commonly used to transmit data in web applications. Let’s say if we send any data from the server to the client then it will be displayed on the web page and vice-versa.

Note − The JSON can’t be called or constructed.

In the article we will look at how to convert an array into JSON.

Using JSON.stringify() method

The JSON.stringify() method is used to convert a JavaScript value to a JSON string. Or we say that it is used to convert a JavaScript object into a string.

As we know that in JavaScript an array is an object so we can pass an array object as an argument in this method as shown below −

JSON.stringify(array); Example

Following is the program to convert an array into JSON −

let

array

new

Array

(

)

;

array

[

]

;

array

[

]

;

array

[

]

;

array

[

]

;

array

[

]

;

let

len

array

length

;

document

write

(

“An array elements are: “

)

;

for

(

let

;

len

;

)

{

document

write

(

array

[

]

” “

)

;

}

In the above program, firstly, we declare an array with a fixed size and then we initialize the value. And by using for loop we print the array elements.

We then used JSON.stringify(array) method to convert an array to JSON and pass an array as an argument of the method. Using the document.write() method we print the output.

Let’s use HTML and CSS with JavaScript −

HTML file(index.html)

This is the HTML file, and the file must be saved with a .html extension, through the HTML we will build the structure of the content page, and we will create a button, heading, paragraphs, span tag, etc.

index.html

CSS file(style.css)

By using CSS we will manage the styling of the whole HTML page. All the HTML elements within the page are styled by customizing the size, colors, positions etc.

Following is the snippet of code to connect the CSS file with the HTML file −

chúng tôi

button

{

width

150

;

height

;

cursor

pointer

;

}

span

{

position

relative

;

top

;

color

green

;

font

size

;

}

JavaScript file(index.js)

Following is the snippet of code to connect the JavaScript file with the HTML file −

chúng tôi

let

colors

[

"red"

"black"

"green"

"yellow"

]

;

let

res

document

getElementById

(

'result'

)

;

res

innerHTML

"An array elements are: "

colors

;

let

btn

document

querySelector

(

'#btn'

)

;

{

}

Example

On Executing above program HTML, CSS, and JavaScript

button

{

width

150

;

height

;

cursor

pointer

;

}

span

{

position

relative

;

top

;

color

green

;

font

–

size

;

}

let

colors

[

“red”

“black”

“green”

“yellow”

]

;

let

res

document

getElementById

(

‘result’

)

;

res

innerHTML

“An array elements are: “

colors

;

let

btn

document

querySelector

(

‘#btn’

)

;

{

}

In the above program, we have used HTML, CSS, and JavaScript. In HTML we have created buttons, heading, paragraphs, span tags, etc. and in CSS we wrote a code that will style the HTML buttons, headings, paragraphs, etc.

Haskell Program To Pass An Array To The Function

In Haskell, we will pass an array to the function by using user-defined functions. In all the examples, we are going to pass an array to the user-defined functions to perform the certain tasks. These functions can be sumArray, maxArray, minArray, countEvens, etc.

In this method, the user-defined functions are created that will contain the function definition with some returning value and is being called by passing an array as argument to it.

Algorithm

Step 1 − The user defined function is defined by writing its definition with a return value.

Step 2 − Program execution will be started from main function. The main() function has whole control of the program. It is written as main = do. In the main function, the user defined function is being called by passing an array as argument to it.

Step 3 − The result is printed to the console, after the function is being called.

Example 1

In this example, the sumArray function takes an array of Int values as an argument and returns the sum of all elements in the array. The main function demonstrates the usage of the sumArray function by passing an array [1, 2, 3, 4, 5] and printing the result.

sumArray xs = sum xs

main :: IO () main = do putStrLn “Sum of all elements in an array:” let xs = [1, 2, 3, 4, 5] let arrSum = sumArray xs putStrLn (show xs ++ ” has a sum of ” ++ show arrSum)

Output Sum of all elements in an array: [1,2,3,4,5] has a sum of 15 Example 2

In this example, the maxArray function takes an array of integers xs as an argument and returns the maximum element using the maximum function. The main function creates an array xs, calculates the maximum element using the maxArray function and prints the result.

maxArray xs = maximum xs

main :: IO () main = do putStrLn “Maximum element in an array:” let xs = [1, 2, 3, 4, 5] let arrMax = maxArray xs putStrLn (show xs ++ ” has a maximum element of ” ++ show arrMax)

Output Maximum element in an array: [1,2,3,4,5] has a maximum element of 5 Example 3

In this example, the minArray function takes an array of integers xs as an argument and returns the minimum element using the minimum function. The main function creates an array xs, calculates the minimum element using the minArray function and prints the result.

minArray xs = minimum xs

main :: IO () main = do putStrLn “Minimum element in an array:” let xs = [1, 2, 3, 4, 5] let arrMin = minArray xs putStrLn (show xs ++ ” has a minimum element of ” ++ show arrMin)

Output Minimum element in an array: [1,2,3,4,5] has a minimum element of 1 Example 4

In this example, the countEvens function takes an array of integers xs as an argument and returns the number of even elements in the array by filtering the even elements with the filter function and returning the length of the resulting list. The main function creates an array xs, calculates the number of even elements using the countEvens function and prints the result.

countEvens xs = length (filter even xs)

main :: IO () main = do putStrLn “Number of even elements in an array:” let xs = [1, 2, 3, 4, 5] let count = countEvens xs putStrLn (show xs ++ ” has ” ++ show count ++ ” even elements”)

Output Number of even elements in an array: [1,2,3,4,5] has 2 even elements Example 5

In this example, the reverseArray function takes an array of integers xs as an argument and returns the reversed array using the reverse function. The main function creates an array xs, calculates the reversed array using the reverseArray function and prints the result.

reverseArray xs = reverse xs

main :: IO () main = do putStrLn “Reversed array:” let xs = [1, 2, 3, 4, 5] let reversed = reverseArray xs putStrLn (show xs ++ ” reversed is ” ++ show reversed)

Output Reversed array: [1,2,3,4,5] reversed is [5,4,3,2,1] Conclusion

In Haskell, an array is a collection of values of the same type, stored in contiguous memory locations. An array can be thought of as a sequence of values, where each value is associated with an index. Arrays in Haskell are represented using the [a] type, where a is the type of elements in the array.

The user-defined functions are functions that are created by the programmer to perform specific operations. The users can define functions as per their need by passing any desired arguments and returning some value in the function definition. The arguments passed can be integers, strings or any array of the values.

Async In Js: How Does It Work

In JavaScript, code execution is single-threaded, which means that only one thing can happen at a time. The JavaScript engine executes code in a sequential and synchronized manner, one line at a time.

This means that if there is a time-consuming task in the code, such as an API call or a long loop, the execution of the entire code will be blocked until the task is completed. During this time, the application will not be able to respond to any user input or execute any other code.

The problem with synchronous code

Synchronous code is easy to understand and follow, as it executes exactly as written, one line after the other.

console.log('one') console.log('two') console.log('three')

We can further illustrate this using the delay() function:

function printDelay() { console.log('Phew!') } delay(5000) printDelay()

In the example above, the code requires a delay of 5 seconds before printing a greeting message to the console. However, the delay function is synchronous, which means that the execution of the entire code is blocked for 5 seconds until the delay function is completed. During this time, the JavaScript engine cannot execute any other code, making the application unresponsive.

Therefore, to avoid blocking the execution of code, developers use asynchronous programming techniques such as callbacks, promises, and async/await to handle long-running tasks in a non-blocking manner.

Async

Asynchronous code, on the other hand, is executed in a non-sequential manner, meaning that the execution of the next line does not wait for the completion of the previous line. Instead, it continues to execute the remaining code while performing other tasks in the background.

Here’s an example of asynchronous code that uses the same setTimeout function to delay the execution of the code for two seconds:

console.log('Start'); console.log('End');

In this example, the setTimeout function is called with a delay of two seconds, but the execution of the code continues without waiting for it.

Therefore, the ‘End’ message is printed immediately after the ‘Start’ message, and the ‘Inside Timeout’ message is printed after two seconds.

Asynchronous code is useful when dealing with time-consuming tasks, such as network requests, file operations, or user interactions. By executing these tasks asynchronously, the rest of the code can continue to execute without being blocked, improving the overall performance and responsiveness of the application.

The call stack

In JavaScript, the call stack is a mechanism used by the interpreter to keep track of the current execution context during code execution. It is essentially a data structure that stores the execution context of a program in a stack-like manner.

Whenever a function is called, the interpreter pushes the function call onto the top of the call stack, along with its associated arguments and variables. The interpreter then executes the function, and when it finishes executing, it pops the function call off the top of the call stack and continues executing the code from where it left off.

This process continues for each function call in the program, with the call stack growing and shrinking as functions are called and returned.

For example, consider the following code:

function foo() { function bar() { console.log('Hello!') } bar() } foo()

In this code, there are three nested functions, foo, bar, and a console.log function that logs the message ‘Hello!’. The foo function calls the bar function, which in turn calls the chúng tôi function.

When the code is executed, the foo function is called first, and the interpreter pushes the foo function call onto the top of the call stack. Within the foo function, the bar function is called, and the interpreter pushes the bar function call onto the top of the call stack, above the foo function call.

When the bar function is called, it executes the chúng tôi function, which logs the message ‘Hello!’ to the console. Once the function is executed, the interpreter pops the function off the top of the call stack and continues executing the bar function.

After the bar function finishes executing, the interpreter pops it off the call stack, and control returns to the foo function, which finishes executing and is then popped off the call stack as well.

Therefore, the call stack would look something like this during execution:

| console.log() | | bar() | | foo() |

After executing the entire block, the stack will become empty.

The entire chain of function calls is stored on the call stack in synchronous code. When a function calls itself repeatedly without any condition to stop, it is called recursion without a base case. This can cause a stack overflow, as each recursive call adds a new function call to the top of the stack, and if the recursion continues indefinitely, the stack will eventually run out of memory, and the program will crash.

Let’s see how the call stack works with asynchronous code:

function main() { setTimeout(function welcome() { console.log('Welcome!') }, 3000) console.log('Goodbye!') } main()

Calling the main() function, the call stack is:

main();

Calling the setTimeout() function, the call stack is:

setTimeout(); main();

setTimeout has finished, it exits the stack:

main();

Calling console.log('Goodbye!'):

console.log('Goodbye!'); main();

The task is complete, exiting the stack:

main();

The main() call is also finished, and the stack becomes empty.

After 3 seconds, the welcome() function is called, and it goes on the stack:

welcome();

This will call console.log('Welcome!'):

console.log('Welcome!'); welcome();

After it is done, it leaves the stack.

welcome();

After executing the entire block, the stack becomes empty again.

One thing you might not have noticed right away is that setTimeout() was terminated immediately, even though the callback function wasn’t yet executed, it wasn’t even called!

This has to do with a mechanism known as the event loop, so let’s move on to that!

Event Loop

In JavaScript, setTimeout() is a function that allows developers to schedule a callback function to be executed after a specified delay. However, setTimeout() is not actually part of the JavaScript language itself.

It is a Web API, which means it is a functionality provided by the browser environment rather than the JavaScript engine.

Web APIs are additional features provided by the browser environment that allow JavaScript to interact with the browser and its features, such as timers, intervals, and event handlers. When we use setTimeout(), it interacts with the Web API to schedule the callback function to be executed after the specified delay.

The event loop is a mechanism that is responsible for executing code, collecting and handling events, and executing subtasks from the queue. When an asynchronous event is triggered, such as a setTimeout() callback, it is added to the event queue. The event loop continuously checks the event queue for new events, and when it finds an event, it dequeues it and executes the associated callback function.

Therefore, when we use setTimeout(), it is not executed immediately, but instead scheduled to be executed in the future by the Web API. The event loop is responsible for managing the execution of the callback function by dequeuing it from the event queue and executing it when it is the appropriate time.

It is the event loop that is responsible for setTimeout() missing from the stack in the last example. Now, let’s take the previous example we examined and draw a clear picture of what is happening:

function main() { setTimeout(function welcome() { console.log('Welcome!') }, 3000) console.log('Goodbye!') } main()

To best illustrate how this works, let’s include not only the stack but also the Web API and the task queue that the Web API uses to store what needs to be executed.

Calling: main()

StackWeb APITask Queuemain()

Web API and task queue are empty for now.

Calling: setTimeout()

When setTimeout() disappears from the stack, it enters Web API visibility, where the interpreter understands that there is a welcome() function inside it to be executed after 3 seconds:

StackWeb APITask Queuemain()setTimeout(welcome)

This is followed by a console.log('Goodbye!') call. The setTimeout(welcome) function remains in the Web API. It will be there until 3 seconds have elapsed:

The console.log() has been processed, the main() call ends:

StackWeb APITask Queuemain()setTimeout(welcome)

The main() call has ended, so the stack is emptied, but because 3 seconds haven’t passed yet, the setTimeout(welcome) function is still inside the Web API:

StackWeb APITask QueuesetTimeout(welcome)

Finally, 3 seconds have passed – the welcome() function moves to the task queue:

StackWeb APITask Queuewelcome()

The event loop now moves the welcome() function from the task list to the call stack:

StackWeb APITask Queuewelcome()

This then calls console.log('Welcome!'):

The stack is now empty.

In JavaScript, the call stack and the task queue are two key components of the event loop. The call stack is a last in, first out (LIFO) data structure that tracks the current position of code execution. The task queue, also known as the event queue, is a first in, first out (FIFO) data structure that holds callback functions waiting to be executed.

The call stack and the task queue are named stack and queue because they work on LIFO and FIFO principles, respectively. This means that the most recently added function to the stack is the first to be executed (LIFO), while the first added function to the queue is the first to be executed (FIFO).

This is Loupe, a tool built by Philip Roberts. It is designed to help developers understand how JavaScript’s call stack/event loop/callback queue interact with each other.

Callbacks

In the context of the setTimeout() example, the callback function is the welcome() function, which is executed after a 3-second delay. When the timer expires, the setTimeout() function invokes the welcome() function as a callback.

Initially, callbacks were the only way to handle asynchronous code in JavaScript, and many chúng tôi APIs were designed specifically to work with callbacks. The mental model of callbacks is simple: “execute this function when this event happens.”

However, callbacks can lead to a phenomenon called “callback hell,” which occurs when multiple nested callbacks are used, making the code difficult to read and maintain. This can result in code that is hard to debug and prone to errors.

⇢ Callback Hell

Suppose we have a number of asynchronous tasks that depend on each other: that is, the first task starts a second task when completed, the second task starts a third, etc.

In this example, we have three asynchronous tasks (task1, task2, and task3) that depend on each other. Each task takes a callback function as an argument, which is executed when the task is completed. As you can see, the code becomes deeply nested and harder to read as we chain these tasks together.

The answer to this problem? Promises.

Promises

A Promise is a wrapper object for asynchronous code that represents the eventual completion or failure of a single asynchronous operation.

A Promise has three states:

pending – The initial state, neither fulfilled nor rejected.

fulfilled – The operation completed successfully, resulting in a value.

rejected – The operation failed, resulting in an error.

In terms of the event loop, a Promise is similar to a callback. The function to be executed (either resolve or reject) is in the Web API environment, and when the event occurs, it goes to the task queue, from where it goes to the call stack for execution.

Promises introduce a division between macro-tasks and micro-tasks.

A Promise’s then method is a micro-task, which means it is executed before any macro-tasks such as setTimeout. Micro-tasks are added to the micro-task queue, while macro-tasks are added to the macro-task queue.

Here’s an example that demonstrates the use of both resolve and reject in Promises. In this example, we’ll simulate the process of fetching user data based on a user ID. If the user is found, we’ll resolve the Promise, otherwise, we’ll reject it.

In this example, getUserData returns a Promise that simulates an asynchronous operation to fetch user data. After a 1-second delay, the Promise is either fulfilled with the user data (using resolve()) or rejected with an error message (using reject()).

We call getUserData() with two different user IDs: 1 and 3. For user ID 1, the Promise is resolved and the user data is logged. For user ID 3, the Promise is rejected and the error message is logged. We use the then() method to handle the fulfilled Promise and the catch() method to handle the rejected Promise.

Here’s a comparison between the callback-based code and the Promise-based code:

Callback-based code:

console.log(“All tasks completed”); }); }); });

Promise-based code:

task1() return task2(); }) return task3(); }) console.log("All tasks completed"); });

Code conciseness – Although Promises improve code readability compared to callbacks, they can still result in more verbose code than desired, especially when dealing with multiple chained operations.

Debugging limitations – When using arrow functions and chaining Promises, you might face difficulties in setting breakpoints for debugging since there is no function body. To overcome this limitation, you would need to expose the function, which makes the code less concise.

Error stack – When an error occurs within a Promise chain, the error stack may contain several then() calls, making it harder to pinpoint the exact location of the error.

Nested conditions – Handling complex conditional logic within Promises can lead to nested structures, increasing the amount of code and reducing readability.

To address these issues, JavaScript introduced async/await, a more concise and readable syntax for working with Promises. With async/await, you can write asynchronous code that looks and behaves like synchronous code, making it easier to read, debug, and maintain.

Asynchronous functions

In short, asynchronous functions are functions that return promises.

An asynchronous function is marked with a special keyword async:

async function request() {} class MainClass { async request() {} }

They always return a Promise. Even if we didn’t explicitly specify it, as in the examples above, they would still return a Promise when called.

async function request() {}

However, asynchronous functions can be handled without then().

Bundling async/await

Within asynchronous functions, you can call other asynchronous functions without using then() or callbacks, but with the help of the await keyword.

async function loadUsers() { const response = await fetch('/api/users/') const data = await response.json() return data }

In the example above, we use the fetch() method inside the loadUsers() function.

We call all asynchronous functions inside with await - that way, the Promise function returns are automatically expanded, and we get the value that was inside the Promise.

The pros of async/await

Async/await provides several benefits over using Promises with then() chains when working with asynchronous code:

Cleaner and shorter code - Async/await helps you write cleaner and shorter code by eliminating the need for chaining then() methods. It flattens the structure, making it more readable and resembling synchronous code.

Improved handling of conditions and nested constructs - With async/await, it becomes easier to work with conditional statements and nested constructs, as you can use familiar constructs like if, else, and loops in conjunction with await. This improves the readability of the code and simplifies its structure.

Familiar error handling with try-catch - Async/await allows you to handle errors using try-catch blocks, similar to how you would handle errors in synchronous code. This brings consistency in error handling and makes it easier to reason about the flow of the code when an error occurs.

Here's an example demonstrating the benefits of async/await:

async function fetchData(id) { const data = { 1: "Success", 2: "Error", }; if (data[id] === "Success") { resolve(data[id]); } else { reject(new Error("Fetch error")); } }, 1000); }); } async function main() { try { const id = 1; const result = await fetchData(id); if (result === "Success") { console.log("Data fetched successfully"); } else { console.log("Data fetch failed"); } } catch (error) { console.error("Error:", error); } } main();

In this example, we have an async function fetchData() that simulates an asynchronous operation. The main() function uses async/await to call fetchData(). We use a try-catch block for error handling and a simple if statement to check the result of the data fetch.

The code structure is clear, flat, and easy to read, showcasing the benefits of async/await over Promise chaining.

Summary

In conclusion, asynchronous programming is an essential aspect of JavaScript, as it enables handling tasks such as network requests, file I/O, and timers without blocking the main thread. Throughout the years, various techniques have been introduced to manage asynchronous code in JavaScript, including callbacks, Promises, and async/await.

Callbacks were the initial approach, but they led to issues like callback hell, where deeply nested and hard-to-read code structures emerged. To address these problems, Promises were introduced, providing a more manageable way to work with asynchronous operations. Promises led to cleaner, more readable code and improved error handling. However, they still had some drawbacks, such as verbosity and difficulty in handling complex nested conditions.

To further simplify asynchronous code, JavaScript introduced async/await, a syntax that allows writing asynchronous code resembling synchronous code. This approach offers several benefits, including cleaner and shorter code, better handling of conditions and nested constructs, and familiar error handling with try-catch blocks.

By understanding the evolution of asynchronous programming in JavaScript and how each technique works, you can learn to write more efficient, maintainable, and readable code. Embracing async/await can significantly improve the overall experience of working with asynchronous operations in JavaScript applications.

How To Easily Kill An Unresponsive Application In Ubuntu

Using the System Monitor

1. Open the System Monitor app. In the Processes tab, scroll down the list until you find the unresponsive app.

Once confirmed, this will kill the unresponsive application.

Using a keyboard shortcut

You can assign a custom keyboard shortcut to kill an application when it becomes unresponsive.

That’s it.

Damien

Damien Oh started writing tech articles since 2007 and has over 10 years of experience in the tech industry. He is proficient in Windows, Linux, Mac, Android and iOS, and worked as a part time WordPress Developer. He is currently the owner and Editor-in-Chief of Make Tech Easier.

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