Douglas Luiz remains on Arsenal’s radar after the Gunners failed in their pursuit of the Brazilian last summer. The Aston Villa star was heavily linked with a move to the Emirates Stadium in 2022, but Mikel Arteta’s side were unable to agree a deal and the proposed transfer didn’t materialise.

Bayern transfer news: Arsenal target Douglas Luiz is perfect for Thomas Tuchel

Douglas Luiz remains on Arsenal’s radar after the Gunners failed in their pursuit of the Brazilian last summer.The Aston Villa star was heavily linked with a move to the Emirates Stadium in 2022, but Mikel Arteta’s side were unable to agree a deal and the proposed transfer didn’t materialise.

Compared to Thomas-Asante, John Swift has a much higher valuation, mainly due to his experience and success in the EFL with the Baggies, Reading and Brentford. Swift has made a total of 273 appearances in the Championship and comes in at a valuation of €3.6 million, with a range of €2.7 million - €4.6 million.

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Newcastle could look to sign a replacement for Sandro Tonali if the midfielder is indeed banned for 18 months for betting breaches. Some serious allegations have been leveled at the Italian via reports in his home country - and he could face a seriously lengthy spell out on the sidelines.

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Last season, data analytics experts SciSports rated him as the sixth best striker in the Bundesliga based on hundreds of in-game data points. Moukoko rated above the likes of Christopher Nkunku, Marcus Thuram and Randal Kolo Muani, who all made high ...

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Jadon Sancho is facing an exit from Manchester United in January after being left out of the club’s team photo for the season, with the winger still yet to apologise for his recent misconduct.The 23-year-old last played for United in August before spending time away from the first team after a social media post calling out manager Erik ten Hag following his criticism of Sancho’s attitude in training.

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Kalvin Phillips has admitted he may need to leave Manchester City in the near future in search for more first team football after failing to break into Pep Guardiola’s team.

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As confirmed by Fabrizio Romano, a host of European giants are keeping tabs on the Bayern wonderkid's development, including Liverpool and Chelsea, while Spanish media report that Real Madrid are eyeing the 20-year-old with his good friend Jude Bellingham potentially being an ace up their sleeve.

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Moyes has sometimes deployed a back three with the Hammers and Maatsen would perfectly suit playing as a left-wing-back with former Chelsea man Emerson behind him.

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SciSports

scisports

Rock paper scissors is a popular game played using hand gestures. Two individuals make shapes with their hands, and each shape has a specific degree of power that decides the winner of the game. This article will teach you how to build a rock paper scissors game in Python, with the symbols representing the hand gestures made from ASCII art. Of course, rock paper scissors is an interactive game with user input and conditions to determine the winner and loser of each game. Getting Started This project will show you how to give users feedback through an interactive display in the terminal or command prompt and ensure that the program follows the structured pattern for a smooth, fun, and hitch-free experience. Creating the Game First, we will write the scripts for the Python rock paper scissors game. As with every Python project, create a new file, . game.py Copy and paste the following code: # game.py

import random

rock = '''
    _______
---'   ____)
      (_____)
      (_____)
      (____)
---.__(___)
'''

paper = '''
    _______
---'   ____)____
          ______)
          _______)
         _______)
---.__________)
'''

scissors = '''
    _______
---'   ____)____
          ______)
       __________)
      (____)
---.__(___)
'''

game_images = [rock, paper, scissors]

user_choice = int(
    input(
        "What do you choose? Type 0 for Rock, 1 for Paper or 2 for Scissors.\n"
    ))

if user_choice >= 3 or user_choice < 0:
    print("You typed an invalid number, you lose!")
else:
    print(game_images[user_choice])

    computer_choice = random.randint(0, 2)
    print(f"Computer chose: {computer_choice}")
    print(game_images[computer_choice])

    if user_choice >= 3 or user_choice < 0:
        print("You typed an invalid number, you lose!")
    elif user_choice == 0 and computer_choice == 2:
        print("You win!")
    elif computer_choice == 0 and user_choice == 2:
        print("You lose")
    elif computer_choice > user_choice:
        print("You lose")
    elif user_choice > computer_choice:
        print("You win!")
    elif computer_choice == user_choice:
        print("It's a draw") Let’s go over the code block above: Import the in-built Python module, , meant for making random numbers random Symbols representing each of the shapes assigned to variables, rock, paper, and scissors, respectively A list is created in the game_images variable, and each item is defined as an index An input to give a user the choice of selecting an integer in user_choice Next is the logic for the Python game in conditionals block. if-elif if user_choice >= 3 or user_choice < 0:
    print("You typed an invalid number, you lose!")
else:
    print(game_images[user_choice]) If a user types a number greater than or equal to 3, another less than 0, or a letter, the program notifies the user of invalid input in the code block above. Otherwise, in the else block, it prints out the symbol index from the variables, rock, paper, and scissors. computer_choice = random.randint(0, 2)
    print(f"Computer chose: {computer_choice}")
    print(game_images[computer_choice]) Here, the computer choice outputs a random number from a range of 0 and 2 with the method. As we know, an index in Python starts from 0, not 1. When the computer resolves the selected number, it prints out the image as either rock, paper, or scissors. .randint if user_choice >= 3 or user_choice < 0:
        print("You typed an invalid number, you lose!")
    elif user_choice == 0 and computer_choice == 2:
        print("You win!")
    elif computer_choice == 0 and user_choice == 2:
        print("You lose")
    elif computer_choice > user_choice:
        print("You lose")
    elif user_choice > computer_choice:
        print("You win!")
    elif computer_choice == user_choice:
        print("It's a draw") The code block above is the final validation for the conditions if specific user choice values are met. If the user choices meet the conditions, it prints out either a “You win”, “You lose”, or “It’s a draw” output. Conclusion This article taught you how to build a rock paper scissors game using Python. Would you try building or playing this Python game? Let me know your thoughts. Learn More Understand the concepts and official rules of the game. Check out to play the game**.** this guide

How to Build a Rock, Paper, Scissors Game in Python

TL;DR, if you’re just here for the source code, you can download it from my GitHub repository . Or go ahead and play the game online . Remember the Microsoft Kinect? That bulky sensor bar which was once and later famously had to be unbundled from the Xbox One package? the world’s fastest-selling consumer electronics device It didn’t get much love from game developers, but the Kinect was a pretty decent piece of hardware. Head tracking and body pose estimation worked very well, and it could even detect simple hand gestures like “pinch” and “fist”. At an affordable retail price of around 99 USD, it quickly became a favorite in and communities. hacker maker Sadly we haven’t seen a real successor to the 2014 “Kinect 2” model which was discontinued in 2018. The 2019 “Kinect Azure” does not fill this gap for multiple reasons: It is more expensive. You can find a used Kinect 2 for around 50 USD while the Azure development kits currently sell for prices north of 1,000 USD. The Kinect 2 is a self-contained device that works out of the box. much The Azure requires an additional Nvidia GPU (RTX 2060 or better) to work. Good luck finding one these days. Luckily, with all the recent advances in machine learning and computer vision, there are now some great alternatives for adding Kinect-like features to your project. Introducing TensorFlow.js Developed by the , TensorFlow is a popular machine learning (ML) library for the Python programming language. TensorFlow.js (TFJS) is its companion library for JavaScript. Quoting the : Google Brain Team official website TensorFlow.js is a library for machine learning in JavaScript. Develop ML models in JavaScript, and use ML directly in the browser or in Node.js. TensorFlow.js is not just an amazing piece of software, but it also gives you access to a , ready to use with your project. growing library of machine learning models In this tutorial, I will show you how to use a TFJS based machine learning model to create a “Rock, Paper, Scissors” game with gesture controls. The final game will be running in your web browser, using just HTML and JavaScript. Let’s make a game! The focus of this tutorial is on the hand gesture recognition part, not so much on game development. So to speed things up, . 👇👇 I have already prepared a simple game UI for you Still, to get a better idea of the game we’re building, let’s create a simple game design document. The game design document When developing a game, usually the best way to start is to describe the gameplay by creating a game design document. There are many ways to do this, for example by drawing a storyboard. For a simple game like “Rock, paper, scissors”, we will just verbally describe how the game should work: Game will load and show a “please wait” message during initialization Player and opponent are shown next to each other The first round of the game is started by the press of a key or button A new round starts with a countdown, asking the player to get ready Player should show a hand gesture (rock, paper, or scissors) Once a valid gesture is registered, it is compared to the computer gesture (which is still hidden at this point) The result is evaluated according to the rules of “Rock, paper, scissors” Winner is awarded one point, score display gets updated Start next round (go to item #4) With the UI out of the way, let’s get right to the good stuff. Building the hand gesture recognizer When building a Rock, Paper, Scissors game, the key challenge is to recognize the three hand gestures ✊🤚✌ inside a camera picture. Before we look into the actual implementation of things, let’s first take a step back and think about how a high-level process to detect hand gestures would look like: We are trying to determine hand gestures from a camera picture. Therefore, the first step is to detect whether a hand is actually inside the camera picture. If a hand is detected, we estimate the position of all finger joints to trace the hand skeleton. The hand skeleton detector returns 21 key points (also called “landmarks”): Four joints for each finger plus the wrist. This is our raw data which we will process further. Working with the key points The key points represent 2D coordinates, telling us the position of each skeleton point in the picture. This isn’t very useful to describe a hand gesture, as it is hard to compare two hand gestures based on the position of the joints. A hand can appear anywhere in the picture, it could be rotated, and people could be left- or right-handed. Let’s try to find a better representation by describing a hand gesture using natural language: Take the “Thumbs Up” gesture 👍 as an example: It can be described as “All four fingers fully curled and pointing to either the left or right. Thumb must not be curled and point upwards”. Curl and pointing directions are a much more concise way of describing a hand gesture. They are independent of the size and position of the hand in the camera picture, also both can easily be deduced from the raw 2D coordinates. This brings us to the next steps in our detection process: Using the key points, we describe the curl and pointing direction for each detected finger. Finally, we compare this description to a list of known hand gestures and check which one is the best match. Great, we figured out how to detect hand gestures — At least in theory. Now let’s see how TensorFlow.js can help us to implement it: Picking a suitable machine learning model As I mentioned in the introduction, TensorFlow.js gives you access to a library of which you can immediately use within your application. many useful machine learning models and offers “Hand pose detection”. The description reads: One of the models is called "HandPose" A palm detector and a hand-skeleton finger tracking model. It predicts 21 3D hand key points per detected hand. Sounds like this model can already cover steps (1) and (2) of our detection process and extract the raw data we need. Awesome! Let’s install it: Install HandPose First, we need to install the model itself: npm i --save @tensorflow-models/handpose Next, we install its TensorFlow.js dependencies: npm i --save @tensorflow/tfjs-core
npm i --save @tensorflow/tfjs-converter
npm i --save @tensorflow/tfjs-backend-webgl TensorFlow.js can use your computer’s GPU for additional performance. Almost any GPU (Nvidia, AMD, Intel) works as long as it supports WebGL. , so make sure to install the WebGL backend to get a massive speed boost for free. Yours most likely does Processing the raw data As I mentioned before, the raw data isn’t very useful for gesture detection. To work with the data, we need to transform it into “curl” and “pointing direction”. Luckily there is which will do just that. the "Fingerpose" library Install the Fingerpose library with the following command: npm i --save fingerpose Define the gestures Fingerpose expects you to define a hand gesture by describing the and for each finger. Our game uses three distinct hand gestures, so we need to create one for each gesture. direction curl GestureDescription Describe the rock gesture ✊: The rock gesture is just you making a fist: You bend your fingers into your palm, curling them under until the tip of each finger touches its corresponding base. Then you bend the thumb down so that it falls across the top halves of the index and middle fingers. This code describes a “rock” gesture as: All fingers fully curled Thumb must be half curled or not curled at all In case you wonder about the second condition: It is physically impossible for you to fully curl your thumb (unless you are Houdini). Also, some people, when making a fist will place their thumb next to their index finger, effectively stretching it out. So we tell Fingerpose that are acceptable and equally valid. both 🖐 Next, let’s look at the “paper” gesture : No surprises here. To make a “paper” gesture, you have to stretch out all of your fingers and your thumb. ✌️ Lastly, let’s have a look at “scissors” : The “scissors” gesture closely resembles a “victory” sign. Index and middle fingers are stretched out. Ring and pinky should be half or fully curled. We don’t care about the thumb, so we just omit it. In case you are wondering about the pointing direction of each finger: Unlike a “Thumbs up” gesture which has a completely different meaning when turned upside down, the gestures of our game do not change their meaning when mirrored or rotated. Therefore, the direction can be omitted to keep the descriptions simple. Putting it all together The implementation of the hand gesture recognizer consists of two parts: One-time Initialization of the model Process every video frame Let’s see some code for the initialization process: The code above will first create a Fingerpose instance. Simply pass the list of known gestures to its constructor, and it is ready to be used. GestureEstimator Afterward, the HandPose model will load and initialize. This may take some time as it will also download some files (the model weights) from the tfhub.dev website. The last step is optional but will greatly improve the user experience. After you load the model, I recommend you “warm up” the model by making one single prediction on a sample image. This is because the first prediction can take quite a bit of time, while subsequent predictions will usually be much faster. If you make the first (slow) prediction part of the initialization process, it will not slow down your gameplay later. Processing a video frame: Again, let’s see some code first: The code explained: We predict the 21 key points (landmarks) by calling the function of the HandPose model, passing the HTML video element as the first argument. The second parameter indicates whether the source video is horizontally flipped. estimateHands If key points were predicted, we pass them to Fingerpose together with a minimum required match score (0 to 10, 10 = perfect match). The match score tells Fingerpose to ignore possible matches with a lower score. Depending on your minimum match score, Fingerpose could return an array with multiple possible matches. This code will pick the gesture with the highest match score (confidence). The return value of this method will be the name of the gesture with the highest match score, or an empty string in case no gesture was detected. Increase the detection stability When you run the code above on a source video, you will notice that the predictions are occasionally unstable. In some frames, HandPose will detect “phantom hands” (false positive) or no hands at all (false negative). This can have an impact on gameplay. One simple solution is to create a low-pass filter by combining detections from several consecutive frames to a single result. For example, we could wait for three consecutive frames to be classified as “Rock” gesture before we emit the “Rock detected” event: Prevent blocking the game UI Running a machine learning model can be quite taxing on your CPU and GPU. While TensorFlow.js is incredibly fast (especially when running with the WebGL backend), it can still cause your game UI to become unresponsive. Especially when you run the model on each frame of a video stream. Again, there is a simple workaround to prevent the UI from locking up. You can wrap the function inside a call with a timeout of zero seconds. Check out to learn more about this workaround. predictGesture setTimeout this thread on StackOverflow Below is some example code how to create a non-blocking detection loop: Wrapping it up With the code above, we have implemented a fast and stable gesture detector. to learn how to integrate it in the final game. Check out the full source code This is the end of my tutorial. Feel free to use my source code as a base for your own game or application. If you have any comments, questions or suggestions please start a conversation in the comments. Thank you very much for reading ❤️

How to Make a 'Rock, Paper, Scissors' App with TensorFlow and Hand Gesture Recognition

Welcome to my tutorial! In this tutorial, we're gonna build a really simple game of Rock Paper Scissors Spock Lizard. Please check my GitHub account for the complete . source code We are gonna use vanilla JavaScript, HTML, CSS for this game. YouTube video Let's get started. First, we need to set up our project folder. Please create a folder for the game. Put an empty , , file in the folder. index.html index.css index.js Now you want to put some tags in . index.html <html> <title>GAME</title> <body> < < > head </ > head </ > body /html> Don't forget to save the file periodically. We can check that we doing fine by running this file in a browser. Okay, We can move forward. Now you want to add input elements for a user. YOUR CHOICE ⛰️ ✂️ 🧻 🖖 🦎 < > span </ > span < = > div id "user-options" < > div < = = = = > input type "radio" id "1" name "option" class "user-option" < = > label for "1" </ > label </ > div < > div < = = = = > input type "radio" id "2" name "option" class "user-option" < = > label for "2" </ > label </ > div < > div < = = = = > input type "radio" id "3" name "option" class "user-option" < = > label for "3" </ > label </ > div < > div < = = = = > input type "radio" id "4" name "option" class "user-option" < = > label for "4" </ > label </ > div < > div < = = = = > input type "radio" id "5" name "option" class "user-option" < = > label for "5" </ > label </ > div </ > div We want to add it at the end of body tag. index.html We need to add computer output, game result, button to play the game. The computer output should look next: COMPUTER CHOICE 💭 < > span </ > span < = > div id "computer-choice" </ > div You want to add it at the end of your body tag. index.html The play button is pretty simple: ▶️ < = > button id "play" </ > button You want to add it at the end of your `index.html` body tag. The game result should look next: < = > div id "output" </ > div You want to add it at the end of your body tag. index.html Now you want to link your and files. index.css index.html Please add < = = > script type "text/javascript" src "./index.js" </ > script at the bottom of the body. That's it. We finished our work with . index.html We just want to increase the font size to make emojis look better. You want to add this to your index.css: { : } html font-size 42px Let's flip over to our JavaScript file. We need a function to return a random number in range 1 to 5 for a computer choice. We would name it and it should look like this one: getComputerChoice { .floor(( .random() * ) + );
} ( ) function getComputerChoice return Math Math 5 1 Put it at the beginning of the file. index.js We want to add some consts that would help us later. Just put it at the end of your index.js ROCK = ; SCISSORS = ; PAPER = ; SPOCK = ; LIZARD = ; OPTIONS = { : ROCK, : SCISSORS, : PAPER, : SPOCK, : LIZARD
}; OPTIONS2EMOJI = { : , : , : , : , : }; const 'ROCK' const 'SCISSORS' const 'PAPER' const 'SPOCK' const 'LIZARD' const 1 2 3 4 5 const 1 '⛰️' 2 '✂️' 3 '🧻' 4 '🖖' 5 '🦎' Now we want to store user input somewhere. Let's add a variable for that. userChoiceID = ; let '' We want to add event listeners for user input when a page is loaded. To do that we should write our code inside the callback function. .onload = { } window => () // your code here We want to put it at the end of . index.js We need an element to output results. output = .querySelector( ); const document '#output' Put it at the beginning of function. onload We want to add event listeners to handle user input. First, we would select elements by class. Then we would add an event listener to each element. userOptions = .querySelectorAll( );

userOptions.forEach( el.addEventListener( , event => {
    userChoiceID = event.target.id;
})); const document '.user-option' => el 'click' Put it at the end of `onload` function. Now we want to add an event listener to the play button. Let's create a variable for it first. playButton = .querySelector( ); const document '#play' We can now add an event listener. playButton.addEventListener( , () => {
}) 'click' Let's collect all the information that we need to determine the winner. We need a computer and user choice. computerChoiceID = getComputerChoice(); computerChoice = OPTIONS[computerChoiceID]; computerChoiceElement = .querySelector( ); output = .querySelector( ); userChoice = OPTIONS[userChoiceID]; result = ; const const const document '#computer-choice' const document '#output' const let '' Now we can output computer choice. computerChoiceElement.innerHTML = OPTIONS2EMOJI[computerChoiceID]; Put it at the end of the play button click callback. Let's write logic to determine a winner. We would use a switch for that. Don't forget to add a default case. ( ) { : : : : :
        result = ; : : : : : : : : : :
        result = ; : : : : : : : : : :
        result = ; :
        result = } switch ` - ` ${computerChoice} ${userChoice} case ` - ` ${ROCK} ${ROCK} case ` - ` ${SCISSORS} ${SCISSORS} case ` - ` ${PAPER} ${PAPER} case ` - ` ${SPOCK} ${SPOCK} case ` - ` ${LIZARD} ${LIZARD} 'TIE 👔' break case ` - ` ${ROCK} ${SCISSORS} case ` - ` ${ROCK} ${LIZARD} case ` - ` ${SCISSORS} ${PAPER} case ` - ` ${SCISSORS} ${LIZARD} case ` - ` ${PAPER} ${ROCK} case ` - ` ${PAPER} ${SPOCK} case ` - ` ${SPOCK} ${ROCK} case ` - ` ${SPOCK} ${SCISSORS} case ` - ` ${LIZARD} ${PAPER} case ` - ` ${LIZARD} ${SPOCK} 'COMPUTER WIN 😔💔 🤖🥇' break case ` - ` ${ROCK} ${PAPER} case ` - ` ${ROCK} ${SPOCK} case ` - ` ${SCISSORS} ${ROCK} case ` - ` ${SCISSORS} ${SPOCK} case ` - ` ${PAPER} ${SCISSORS} case ` - ` ${PAPER} ${LIZARD} case ` - ` ${SPOCK} ${PAPER} case ` - ` ${SPOCK} ${LIZARD} case ` - ` ${LIZARD} ${ROCK} case ` - ` ${LIZARD} ${SCISSORS} 'YOU WIN ☺️🥇 🤖💔' break default 'SOMETHING WRONG. TRY AGAIN. 🐛' Put it at the end of the play button click callback. Now we are ready to output the result. output.innerHTML = result; Put it at the end of the play button click callback. There you have it you can now play against the computer. There are plenty of cool ways to improve on this simple pure JavaScript rock-paper-scissors-Spock-lizard including a score count Once again I hope you enjoyed my tutorial if you have any questions regarding the code please leave a comment. I'll make sure to get back to you with help. Also published on GitHub .

How to Create Rock Paper Scissors Spock Lizard in JavaScript

In the recent sweltering world heat wave, I was set a tech test the other day. In it I needed to write a function that would output zero to five depending on its 6 combinations. For this example I’ll say we wanna get the outcome of flipping a coin playing rock, paper, translated into a number ranging from 0 to 5. and scissors Seem simple? Maybe for some, and not so much for others. I try and refrain from calling things ‘easy’ or ‘simple’ because its just all a bit arbitrary. Things are simple for some and not so much for others. All that really does is discourage those who find it hard, and give a little ego boost to those who don’t. This is not helpful in trying to create a non-intimidating, no-questions-are-stupid culture, which will help get more people into . #GrindsMyGears. coding Write a Failing Test Let start by writing a test for it first. This is universally agreed upon of good practice to write tests first before writing code (aka TDD, Test Driven Development). It may seem strange, but this allows a developer to have a good process of thinking how they will write the code out before doing it. A well tested program will also give the code an assurance of quality and reliability, for when things are added or changed, the tests will give out visibility on where the problems are. Lets setup . For some strange reason their docs miss out the easiest version of their installation, which is to download a and add it to your folder. Once this is done, open it up in your favourite text editor. Jasmine zipped setup (Folder structure of Jasmine standalone. By default there are example files there.) The lib folder is where Jasmine is stored, so don’t worry about that. What we care about is the spec and src folder. The spec folder is where will will write our test, and the src folder is where our code will be. Then we will put both files in SpecRunner.html so that it will run the tests on your code in the browser by loading that up. (Opening up SpecRunner shows their default tests) Aight, lets create our own blank files for the test and the code and put them into the SpecRunner.html Follow the comments in the SpecRunner.html on where to put your files Lets write our test! describe( , () => {
    it( ,    () => { result = coinRPS( , );
        expect(result).toEqual( );
    });
}); '#coinRPS' 'Returns 0 if the coin input is "Heads" and RPS is "Rock"' let 'Heads' 'Rock' 0 Tests are written like this. The describe block is a function with the first parameter being a string describing the test. I typically just write #[function] to show which function it is talking about. The second parameter is another function it which does the same thing as the describe, but this time we write a description in more detail. The second parameter of the it function is another function which will contain our code and the steps to create the outcome we want. So for our function coinRPS we know that we wanna take in two parameters, one for the coin and one for the RPS which will be strings. We also know we want the outcome to return a number from 0 to 5. Our function coinRPS gets called and assigned to result. Then we compare result’s value and see if that is zero. It definitely is a super confusing structure with functions inside functions, but if you stick with it you’ll get used to it and hopefully it will be helpful! Lets check out our test in the browser. Go to SpecRunner and hit refresh. (Test fails because coinRPS function doesn’t exist yet!) Ok cool. Let write some code in. { ;
} ( ) function coinRPS coin, RPS return 0 This will pass. (First passing test!) This process of writing a failing test, then making it pass is what is done for TDD. The next step would be to write one for returning 1. Each small step you take towards your final goal. But for the sake of time, I’ll write a test for all the outcomes. describe( , () => {
    it( , () => { result = coinRPS( , );
        expect(result).toEqual( );
    });
    it( , () => { result = coinRPS( , );
        expect(result).toEqual( );
    });
    it( , () => { result = coinRPS( , );
        expect(result).toEqual( );
    });
    it( , () => { result = coinRPS( , );
        expect(result).toEqual( );
    });
    it( , () => { result = coinRPS( , );
        expect(result).toEqual( );
    });
    it( , () => { result = coinRPS( , );
        expect(result).toEqual( );
    });
}); '#coinRPS' 'Returns 0 if the coin input is "Heads" and RPS is "Rock"' let 'Heads' 'Rock' 0 'Returns 1 if the coin input is "Heads" and RPS is "Paper"' let 'Heads' 'Paper' 1 'Returns 2 if the coin input is "Heads" and RPS is "Scissors"' let 'Heads' 'Scissors' 2 'Returns 3 if the coin input is "Tails" and RPS is "Rock"' let 'Tails' 'Rock' 3 'Returns 4 if the coin input is "Tails" and RPS is "Paper"' let 'Tails' 'Paper' 4 'Returns 5 if the coin input is "Tails" and RPS is "Scissors"' let 'Tails' 'Scissors' 5 As you can see there’s quite a bit of repetition here. In programming its good practice to keep code ‘DRY’ (Do not repeat). But for testing its ok, as the aim is to write quality tests first and foremost. Lets check out some different ways of doing this; Six Solutions, The Good, The Bad and The Fugly! Probably the most common way of doing this is just going for 6 if statements straight up; { (coin === && RPS === ) { ;
    } (coin === && RPS === ) { ;
    } (coin === && RPS === ) { ;
    } (coin === && RPS === ) { ;
    } (coin === && RPS === ) { ;
    } (coin === && RPS === ) { ;
    }
} ( ) function coinRPS coin, RPS if 'Heads' 'Rock' return 0 if 'Heads' 'Paper' return 1 if 'Heads' 'Scissors' return 2 if 'Tails' 'Rock' return 3 if 'Tails' 'Paper' return 4 if 'Tails' 'Scissors' return 5 It passes, enjoy that dopamine hit by seeing this screen on your SpecRunner! (It kinda looks similar to a switch statement, lets try that.) { ( ) { coin === && RPS === : ; coin === && RPS === : ; coin === && RPS === : ; coin === && RPS === : ; coin === && RPS === : ; coin === && RPS === : ; :
    }
} ( ) function coinRPS coin, RPS switch true case 'Heads' 'Rock' return 0 case 'Heads' 'Paper' return 1 case 'Heads' 'Scissors' return 2 case 'Tails' 'Rock' return 3 case 'Tails' 'Paper' return 4 case 'Tails' 'Scissors' return 5 default Well, that doesn’t actually look like its saved any space at all. In fact it might need a break after each return, which seems like a lot more code. Hmmm that’s a lot of of repetition tho, how about using a kinda tree format? { (coin === ) { (RPS === ) { ;
        } (RPS === ) { ;
        } (RPS === ) { ;
        }
    } (coin === ) { (RPS === ) { ;
        } (RPS === ) { ;
        } (RPS === ) { ;
        }
    }
} ( ) function coinRPS coin, RPS if 'Heads' if 'Rock' return 0 if 'Paper' return 1 if 'Scissors' return 2 if 'Tails' if 'Rock' return 3 if 'Paper' return 4 if 'Scissors' return 5 This kinda loses * * repetition? But what we’ve lost in repetition we seemed to have increased in curly brackets :/ some Ok, I’ve heard ternary operators are good at losing brackets, lets try that? Ternaries have the format [conditional statement] ? [result if true] : [result if false] and I suspect that this will have to use nested ternaries which can be like [conditional statement] ? [result if true] : [another conditional statement if false] ? [result if false then true] : [result if false then false] Head hurting? Doesn’t look any less confusing… { coin === ? RPS === ? : RPS === ? : : RPS === ? : RPS === ? : ;
} ( ) function coinRPS coin, RPS return 'Heads' 'Rock' 0 'Paper' 1 2 'Rock' 3 'Paper' 4 5 But on the bright side there definitely is less brackets, so plenty of points for that! However, for readability I’d say its pretty low down the scale, and thank God I wrote that test to help me out! Ok, maybe a different approach. Why not write out the outcomes and then match that? #ThinkingOutsideTheBox { outcomes = { : , : , : , : , : , : ,
    }; input = coin + + RPS; result; .values(outcomes).forEach( { (value === input) {
            result = index;
        }
    }); result;
} ( ) function coinRPS coin, RPS let 0 'Heads Rock' 1 'Heads Paper' 2 'Heads Scissors' 3 'Tails Rock' 4 'Tails Paper' 5 'Tails Scissors' let ' ' let Object ( ) => value, index if return Ok so here we got a hash table of outcomes. The input grabs the string from coin and the string from RPS, and adds a space in between them, just like the strings in the hash values. Object.values(outcomes) loops through the values of our hash table outcomes, and if it matches with input it will assigns the index number to result, which is our number! We can do a bit of refactoring with some ES6 template strings, and ternary’ing it up! { outcomes = { : , : , : , : , : , : ,
    }; result; .values(outcomes).forEach( {
        value === ? (result = index) : ;
    }); result;
} ( ) function coinRPS coin, RPS let 0 'Heads Rock' 1 'Heads Paper' 2 'Heads Scissors' 3 'Tails Rock' 4 'Tails Paper' 5 'Tails Scissors' let Object ( ) => value, index ` ` ${coin} ${RPS} null return Template strings uses backticks ` ` and inside them you use ${} for variables, in this case we can use the parameters coin and RPS passed in. But wait! You know what? Why not save more precious screen space by using an array instead! { outcomes = [ , , , , , ,
    ]; outcomes.indexOf( );
} ( ) function coinRPS coin, RPS const 'Heads Rock' 'Heads Paper' 'Heads Scissors' 'Tails Rock' 'Tails Paper' 'Tails Scissors' return ` ` ${coin} ${RPS} is a method which loops through an array and if it finds a match returns the index position of it. Perfect for what we want to do here! indexOf I think one of the toughest things in writing code is to work out the best balance between readability and cleverness. You want it to be code which is able to be understood by the majority of developers, because nearly all coders are working in a team. People come and go, or maybe you might be returning to some of your own code that you wrote a year ago. I think the nested ternary solution is a good example as a clever solution, but really lacks in readability unless you work ternaries a lot, which probably isn’t the case with most developers. However its so hard to get this balance right, and different people have different opinions on where they believe this line should be. Anyways, I’m off to spend hours of fun flipping coins and playing Rock, Paper, Scissors (aka ), until next time happy coding peeps! Hearthstone

Conditional Coin Flips with Rock Paper Scissors

I decided to make a video tutorial to see in action how the basic concepts of React work together to build a simple React JS application from scratch. And to make it fun we will build a simple game, like the one below: React Js — Simple Game tutorial When starting with React or any other new framework or technology I always like to learn by doing stuff. By making some small apps that can be shown to a friend. Like a game, a contact list, a calculator or an interactive map. And always try to split a bigger problem into smaller pieces. If you are a beginner it’s intimidating to think about the complete application. Our React JS game will need to display some basic layout, react to user input, draw random elements, do animations, decide who won … just to name a few things. But what if, initially, we just have to show just a red circle and a blue one. This seems more doable. After this, just add a simple button that does nothing. With the button added let’s just make it show a basic alert when we press on it. And so on. Think a bit … if we are asked to build a very simple one room small house. At least we know how to put together some bricks. This for sure sounds way more achievable that being asked to make a full skyscraper. It’s the same with programming. In every part of the tutorial, we will add a few more bricks to our project. This React tutorial uses create-react-app and is made of 3 video screencasts: Part 1 : project setup, basic React components and using React inline styles We will start with the basic description of the starting Javascript files. By the end of this first part, our application will have a basic player card React component and will use the React inline styles to assign the blue & red colors to the player cards. Part 2: generating random numbers in React, adding the background images and using setState The next building blocks that we will add to our React example are the selection of some random elements and using the setState to update the component status. Also towards the end, we will use again the inline styles of React to add the background images. Part 3: using setInterval with React to make animations and deciding the game winner The last part is also the most complex one. We will see how to play with the old setInterval function from Javascript to build the shuffling animations and how to set the React state in order to show who won the game. If you want to download the complete code for every part of the tutorial you can to it from . Aso the tutorial is using . If you need it you can find on how to set it up. here create-react-app here a short tutorial Additional Exercises So if you want to expand on this tutorial? You can try by adding new features like: setting names for the players making one player to be controlled by the human user and be able to select from the keyboard what symbol to play adding avatar pictures for the players Interested in learning more about React and Javascript? Sign up for my email list so I can share with you the next screencasts and tutorials! Cheers and happy coding!

Video course: Learn React — how to build a simple Rock Paper Scissors game

The assignment was to create a Rock, Paper, and Scissors game using JavaScript in HTML. Presented on March 20, 2017 Leap 1- Understand and Define My engineering class teacher had assigned my class a project to create a Rock, Paper, and Scissors game using JavaScript in HTML that the user verse the computer. The computer would have to generate a random character to verse with the choice of the user. To make the game fair, one computer choice can not come up more than the rest. My game definition (Product Description) The javascript game will consist of three characters (Rock, Paper and Scissors). Each character will have different number ranges which allow them to verse each other, allowing them win or lose. One computer choice can not come up more than the rest. There will be a welcome screen with the game title and legend and white background. The user then will be instructed to move on to the next section, to choose their character. The user will have three options to choose from (Rock, Paper or Scissors). Once the user chooses its character, they will click “ok” to show their character’s image on one side “VS.” the character’s image that the computer will choose randomly. The result will be displayed at the bottom of the same page. Once the result is displayed, the user will have the choice to restart. The following legend shows how the results were determined. The user can also run a test to see how many times the computer picks each choice over a repetition of 10,000x. Leap 2- List steps (Algorithm) 1. When a user makes a choice (Rock, Paper or Scissors), computer makes a random choice. 2. The computer makes its choice by: • Generating a number from 0 to 9. • Then, corresponding the number with the ranges of the characters. • For example, if the computer chose .33, it will then compare that number to the range that it falls into and show its choice (Rock). 3. The computer will then compare its choice with the user’s choice by: • Using the rules defined by the legend. 4. Once the program is done comparing, it will then prompt a message letting the user know whether the computer or the user won. Leap 3- Expand steps (Flowchart) Leap 4- Establish test plan In order to test my program, I will first make sure that the elements(i.e. Images, texts, background) load properly. Then I will check to make sure that the content of each page are loading in the proper sequence. Then I will make sure that the function of each page is in working order. I will specifically check to make sure that the computer is able to randomize and “fairly” make its choice. I will also check to make sure that the program is able to compare the user’s choice to the computer’s choice and display a result according to the legend. Leap 5- Execute test (Code) the Rock, Paper, and Scissors program that I coded. Click to see

Rock Paper Scissors

Will You Face Superhuman Opponents at the Next Olympics?

Laziness isn’t "sitting around doing nothing." As long as you’re alive, you’re always doing something. The question is whether you control what you do or not. Your energy will go whether you like it or not—you either use it well or waste it. You will always breathe; you can only control how. You will always learn; you can only control what. Laziness is not about inactivity but about misdirected activity. It’s the inability to take control of your efforts. Laziness is passivity. It’s the habit of letting life happen to you rather than shaping your reality. It sweeps you away from the present moment into illusions of the virtual, the past, and the future. It’s living on autopilot without being mindful of your actions. Consider the laziest person you know. They may spend 12+ hours a day playing video games or binge-watching Netflix. That takes effort, but it offers little to no return on investment (ROI). Laziness is not when you spend less energy than someone productive; Laziness is spending that energy on the wrong things. It’s playing the wrong games. Reframing Work Work isn’t "force times distance." It’s not about how many hours you spend on a screen or how long you stay at a job. Work is about getting a job done. If mere effort was all it took to excel: • Everyone would be an expert at speaking. • Nobody will have bad handwriting after years of writing. • I can pick up a guitar and pluck the strings 10,000 times and then I'm a master. Mastery doesn’t come from 10,000 hours of passive activity. It comes from focused iterations of the activity. How to Outwork Everyone If you want to be more productive, forget about hard work. It's such an overused term that's not holistic enough. Embrace diligence instead. Diligence is not about lifting 500 lbs—that’s strength. It’s not about focusing for long—that’s discipline. It’s not even about relentless perseverance—that’s endurance. Diligence is the ability to get a job done well and fast. It requires two key pillars: 1. Doing it Well: The first step to diligence is identifying the right task. You can only play the right game when you know what the right game is. What you work on is more important than how much effort you put in. Planning is half the battle. Working without a plan is laziness masquerading as grinding. You Cannot Multitask: You can only focus on one thing at a time; if you don't believe me, try thinking about two things at once right now. Multitasking as a human is a myth. What you call multitasking is rapid context-switching. In doing so, you lose the compound interest of sustained focus. Sometimes, the compound interest is cheap; other times it's expensive. Embrace boredom. It’s essential for clarity and creativity. 2. Doing it Fast: Speed matters, but not at the expense of quality. Efficiency is about doing the right things fast. This is where leverage becomes your best friend. Look for tasks that, when completed, yield significant benefits or free up more of your time. 1. Leverage Tools: Tools are multipliers. They help you do more with less. • Software that automates repetitive tasks • Frameworks that streamline your work process • Mental models that help you make faster decisions, etc. Tools amplify your efforts. For instance, compare using scissors to cut grass or using a lawnmower. Capital or money can also be a tool for Leverage. 2. Leverage Processes: Systems and routines reduce the cognitive load of decision-making. When you have a process in place, you don’t waste time figuring out the next step. You execute. It is important to reflect and optimize your systems as much as possible to avoid passivity. 3. Leverage Knowledge: Knowledge is the ultimate leverage. The more you know, the faster you can execute. Not only formal education—it includes practical experience, skills, and even your network. When you leverage your knowledge, you avoid mistakes that slow you down. You spot opportunities faster and make decisions with confidence. I define difficulty as the amount of knowledge you don't have yet about a subject. The more knowledge you have, the more the task becomes easy. If X is difficult, it's because you don't know enough about X. Everything that you think is difficult is a knowledge gap. 4. Leverage Relationships: Collaboration can reduce the time needed to complete a task. Why struggle to solve a problem when you can ask someone who’s already been through it? Leverage your connections to move faster and smarter. Leveraging tools, people, and systems allows you to work better, not harder. Trying to Be Fast is Slowing You Down In our fast-paced world, there's a common misconception that speed equals productivity. “You waste years by not being able to waste hours.” ~ Amos Tversky Rushing through tasks without reflection can cause more mistakes, rework, and wasted time. The irony is that in trying to be fast, you can actually slow yourself down. Not taking time to visit the doctor for preventive care, can result in surgery for larger issues. Conclusion Laziness isn’t about doing nothing—it’s about doing the wrong things. Work isn’t about spending more time—it’s about getting the right things done well and fast. Feel free to share this article with lazy people you know. Also grab my FREE productivity planner here: selar.co/99f392 It's based on the best principles I know. It is a combination of systems, tools, and knowledge leverage. To help you with more productive creativity, without burning out. If you enjoyed this article, you'll love this one: https://hackernoon.com/creathievity-can-your-ideas-be-stolen-and-what-to-do Enjoy the rest of your day. Laziness isn’t "sitting around doing nothing." As long as you’re alive, you’re always doing something. The question is whether you control what you do or not. Your energy will go whether you like it or not—you either use it well or waste it. You will always breathe; you can only control how. You will always learn; you can only control what. Laziness is not about inactivity but about misdirected activity. It’s the inability to take control of your efforts. Laziness is passivity. It’s the habit of letting life happen to you rather than shaping your reality. It sweeps you away from the present moment into illusions of the virtual, the past, and the future. It’s living on autopilot without being mindful of your actions. Consider the laziest person you know. They may spend 12+ hours a day playing video games or binge-watching Netflix. That takes effort, but it offers little to no return on investment (ROI). Laziness is not when you spend less energy than someone productive; Laziness is spending that energy on the wrong things. It’s playing the wrong games. Reframing Work Reframing Work Work isn’t "force times distance." It’s not about how many hours you spend on a screen or how long you stay at a job. Work is about getting a job done. If mere effort was all it took to excel: • Everyone would be an expert at speaking. • Nobody will have bad handwriting after years of writing. • I can pick up a guitar and pluck the strings 10,000 times and then I'm a master. Mastery doesn’t come from 10,000 hours of passive activity. It comes from focused iterations of the activity. How to Outwork Everyone How to Outwork Everyone If you want to be more productive, forget about hard work. It's such an overused term that's not holistic enough. Embrace diligence instead. Diligence is not about lifting 500 lbs—that’s strength. It’s not about focusing for long—that’s discipline. It’s not even about relentless perseverance—that’s endurance. Diligence is the ability to get a job done well and fast. It requires two key pillars: 1. Doing it Well: Doing it Well: The first step to diligence is identifying the right task. You can only play the right game when you know what the right game is. What you work on is more important than how much effort you put in. Planning is half the battle. Working without a plan is laziness masquerading as grinding. You Cannot Multitask: You Cannot Multitask: You can only focus on one thing at a time; if you don't believe me, try thinking about two things at once right now. Multitasking as a human is a myth. What you call multitasking is rapid context-switching. In doing so, you lose the compound interest of sustained focus. Sometimes, the compound interest is cheap; other times it's expensive. Embrace boredom. It’s essential for clarity and creativity. 2. Doing it Fast: Doing it Fast: Speed matters, but not at the expense of quality. Efficiency is about doing the right things fast. This is where leverage becomes your best friend. Look for tasks that, when completed, yield significant benefits or free up more of your time. 1. Leverage Tools : Tools are multipliers. They help you do more with less. Leverage Tools • Software that automates repetitive tasks • Frameworks that streamline your work process • Mental models that help you make faster decisions, etc. Tools amplify your efforts. For instance, compare using scissors to cut grass or using a lawnmower. Capital or money can also be a tool for Leverage. 2. Leverage Processes: Systems and routines reduce the cognitive load of decision-making. When you have a process in place, you don’t waste time figuring out the next step. You execute. Leverage Processes: It is important to reflect and optimize your systems as much as possible to avoid passivity. 3. Leverage Knowledge : Knowledge is the ultimate leverage. The more you know, the faster you can execute. Leverage Knowledge Not only formal education—it includes practical experience, skills, and even your network. When you leverage your knowledge, you avoid mistakes that slow you down. You spot opportunities faster and make decisions with confidence. I define difficulty as the amount of knowledge you don't have yet about a subject. The more knowledge you have, the more the task becomes easy. If X is difficult, it's because you don't know enough about X. Everything that you think is difficult is a knowledge gap. 4. Leverage Relationships : Collaboration can reduce the time needed to complete a task. Leverage Relationships Why struggle to solve a problem when you can ask someone who’s already been through it? Leverage your connections to move faster and smarter. Leveraging tools, people, and systems allows you to work better, not harder. Trying to Be Fast is Slowing You Down In our fast-paced world, there's a common misconception that speed equals productivity. “You waste years by not being able to waste hours.” ~ Amos Tversky “You waste years by not being able to waste hours.” ~ Amos Tversky “You waste years by not being able to waste hours.” ~ Amos Tversky Rushing through tasks without reflection can cause more mistakes, rework, and wasted time. The irony is that in trying to be fast, you can actually slow yourself down. Not taking time to visit the doctor for preventive care, can result in surgery for larger issues. Conclusion Conclusion Laziness isn’t about doing nothing—it’s about doing the wrong things. Work isn’t about spending more time—it’s about getting the right things done well and fast. Feel free to share this article with lazy people you know. Also grab my FREE productivity planner here: selar.co/99f392 It's based on the best principles I know. It is a combination of systems, tools, and knowledge leverage. To help you with more productive creativity, without burning out. If you enjoyed this article, you'll love this one: https://hackernoon.com/creathievity-can-your-ideas-be-stolen-and-what-to-do Enjoy the rest of your day.

Speed Is Slowing You Down: How to Outperform Everyone With Effortless Effort (and Overcome Laziness)

On January 22, 2024, I didn’t know how to write a line of code in JavaScript on my own. It was the day when I started my first lesson in the Foundation course by The Odin Project. This was the best thing I could find on my coding journey. The Odin Project saved me from tutorial hell, and all the projects you’ll see below were done on my own without any help from ChatGPT or other tools—just the knowledge I gained from The Odin Project. After exactly 440 hours and 20 minutes of learning over 111 days, from January 22, 2024, to May 11, 2024, I was able to complete the Foundations course and create the final project on my own, which was a calculator. Here are some additional statistics about the time I spent on this, as I know some people are curious about how long it takes. How can you copy the process? Let’s dive in. Reviewing the Data Let’s start by looking at this data to see how accurate it really is. I learned every single day for at least one hour. To calculate the study sessions, I used a Pomodoro timer set for 25 minutes each, with a 5-minute break in between. So, I assume that 2 Pomodoros equal a 1-hour study session. Tools I Used for Note-Taking What do I use to document everything? Obsidian notes. I began using it just before starting Odin because I knew this journey would be quite long, and I would need some nice notes to store my ideas. Then, actually, for fun, I decided to count all these hours to see how long it would really take. Many people asked, and only a few answered. It seems like most people just don’t bother to count the time, and I don’t blame them. (However, I saw some people claim it took them 3 months, while others needed a year). And I am talking only about the Foundations part here. My Study Routine But here’s how I did it, without skipping a single day, cheating, or omitting any resources. I read everything, sometimes including additional resources. This, however, depends on the information included or the blog quality. If I like it or see it would benefit me to save it as a bookmark for future use, I read it and save it; if not, I just skip and move further. But I would highly recommend you always open all additional resource links and at least poke around. For reference, you can have a look at all the projects I have done so far and get an idea of what you will be able to accomplish after the Foundation part of The Odin Project: RECIPES BOOK (yup, it’s ugly but as I remember, it was one of the first projects ;)
LANDING PAGE
ROCK-PAPER-SCISSORS
ETCH A SKETCH (this one wasn’t easy, believe me!)
CALCULATOR Weekdays My daily routine looks like this: I go to work from Monday to Friday, from 7:30 to 16:00. I’m home around 16:30, then I take a shower, eat a quick supper, and usually by 17:00, I’m ready to start. I spend one hour working on my other blogs that are not related to Odin. If sometimes it takes me only 30 minutes, then I start learning Odin at 17:30; if not, then at 18:00. I learn until 19:00 and then work out for about 30 minutes in my room. By 19:30, I go for a walk and come back around 21:00. Sometimes, I study for 15-30 minutes more, but not very often So usually, it’s 1 to 1.5 hours a day. I’d like to mention that I don’t have kids, so I don’t need to pick them up from school, etc. I live alone, which helps me manage distractions and stick to my plan. But even so, one hour is not a lot, and I think that everybody can do it. Weekends Weekends look a bit different though. I wake up around 6:30, do some stretching, and start working on Odin at 7:00. I am able to complete 4 Pomodoros by 10:00. Then I go tidy up my room, make breakfast, drink coffee, and am back to learning at 11:30. On Saturday, I take a rest from working out and study until 14:00, then go to make dinner. If it’s Sunday, however, I work out from 13:30 to 14:00, and then the rest looks the same as Saturday. After my walk, especially on Saturday, I go get groceries, and I’m back home around 17:00, which allows me to do 2-3 more Pomodoros. Altogether, I can complete around 20 Pomodoros during a whole weekend, which is like 10 hours. Sometimes it’s more, sometimes it’s less. If there are any days off, I treat them as if it were a weekend. The Power of the Pomodoro Technique A big part of my learning process was the Pomodoro Technique I already mentioned. It’s all about working in focused 25-minute bursts, called Pomodoros, with a 5-minute break in between. After four Pomodoros, you get a longer break of 15-30 minutes. This method helps you stay focused and avoid burnout. Barbara Oakley’s course on Coursera, “Learning How to Learn,” dives into how our brains work when we’re learning. She talks about the Pomodoro Technique as a great way to break study sessions into smaller chunks, making it easier for the brain to process and remember stuff. If you’re curious about the science behind effective learning, you should definitely check out this course. I think it’s still free. At least, it used to be when I was told about it when I was starting. The Odin Project’s curriculum uses similar principles. They suggest structured study sessions like Pomodoros, which align with proven learning methods. Following their directions and instructions helps you not only learn the material but also build strong study habits that will benefit you in the long run. Balancing Workouts and Learning If I didn’t work out, I would be able to learn more and faster, especially on weekdays, but it wouldn’t be too healthy, I bet. Tips for Staying Focused I also have some tips that worked out for me pretty well. Remember, you are going to face a lot of time-fighting procrastination between sessions. It’s very good to: Turn on flight mode on your phone, and put the device as far from you as you can. Don’t use your phone during the 5-minute break between Pomodoros. Stretch instead, walk around the room, and look through the window. If you are tired and feeling sleepy, get a standing desk or use drawers or some other furniture. Overcoming Challenges There will be days when you are tired or have many negative thoughts running through your head telling you to stop, that it’s not worth it, that you might be too stupid, or that AI will be coding in the future anyway. If all these happen during your Pomodoro sessions, DON’T WORRY AND DON’T GIVE UP. I also had loads of these thoughts, and it’s normal. Some days are worse than others, but I noticed that even the days when I was looking at the screen trying to read boring documentation 5 times helped me to at least stay consistent and build a habit. Finding Enjoyment in the Process At some point, you will realize that you like the process you are going through (if you haven’t liked it yet), and you will notice that all negative thoughts start to fade away, and your motivation goes up day after day, regardless of the level of difficulty. I wrote more about this in my blog post about the calculator project. Happy learning! What challenges have you faced in your learning journey? Share your best productivity tips in the comments! Follow me on Twitter for more tips and insights on coding and productivity. On January 22, 2024, I didn’t know how to write a line of code in JavaScript on my own. It was the day when I started my first lesson in the Foundation course by The Odin Project . This was the best thing I could find on my coding journey. The Odin Project saved me from tutorial hell , and all the projects you’ll see below were done on my own without any help from ChatGPT or other tools—just the knowledge I gained from The Odin Project. The Odin Project The Odin Project saved me from tutorial hell After exactly 440 hours and 20 minutes of learning over 111 days , from January 22, 2024, to May 11, 2024, I was able to complete the Foundations course and create the final project on my own, which was a calculator . 440 hours and 20 minutes 111 days calculator Here are some additional statistics about the time I spent on this, as I know some people are curious about how long it takes. How can you copy the process? Let’s dive in. Reviewing the Data Let’s start by looking at this data to see how accurate it really is. I learned every single day for at least one hour . To calculate the study sessions, I used a Pomodoro timer set for 25 minutes each, with a 5-minute break in between. every single day for at least one hour Pomodoro timer So, I assume that 2 Pomodoros equal a 1-hour study session. Tools I Used for Note-Taking What do I use to document everything? Obsidian notes . Obsidian notes I began using it just before starting Odin because I knew this journey would be quite long, and I would need some nice notes to store my ideas. Then, actually, for fun, I decided to count all these hours to see how long it would really take. Many people asked, and only a few answered. It seems like most people just don’t bother to count the time, and I don’t blame them. (However, I saw some people claim it took them 3 months, while others needed a year). And I am talking only about the Foundations part here. My Study Routine But here’s how I did it, without skipping a single day, cheating, or omitting any resources . without skipping a single day, cheating, or omitting any resources I read everything, sometimes including additional resources. This, however, depends on the information included or the blog quality. If I like it or see it would benefit me to save it as a bookmark for future use, I read it and save it; if not, I just skip and move further. But I would highly recommend you always open all additional resource links and at least poke around. always open all additional resource links For reference, you can have a look at all the projects I have done so far and get an idea of what you will be able to accomplish after the Foundation part of The Odin Project: RECIPES BOOK (yup, it’s ugly but as I remember, it was one of the first projects ;) LANDING PAGE ROCK-PAPER-SCISSORS ETCH A SKETCH (this one wasn’t easy, believe me!) CALCULATOR RECIPES BOOK (yup, it’s ugly but as I remember, it was one of the first projects ;) RECIPES BOOK LANDING PAGE LANDING PAGE ROCK-PAPER-SCISSORS ROCK-PAPER-SCISSORS ETCH A SKETCH (this one wasn’t easy, believe me!) ETCH A SKETCH CALCULATOR CALCULATOR Weekdays My daily routine looks like this: I go to work from Monday to Friday, from 7:30 to 16:00. I’m home around 16:30, then I take a shower, eat a quick supper, and usually by 17:00, I’m ready to start. I spend one hour working on my other blogs that are not related to Odin. If sometimes it takes me only 30 minutes, then I start learning Odin at 17:30; if not, then at 18:00. I learn until 19:00 and then work out for about 30 minutes in my room. By 19:30, I go for a walk and come back around 21:00. Sometimes, I study for 15-30 minutes more, but not very often So usually, it’s 1 to 1.5 hours a day. I’d like to mention that I don’t have kids , so I don’t need to pick them up from school, etc. I live alone , which helps me manage distractions and stick to my plan. I don’t have kids I live alone But even so, one hour is not a lot, and I think that everybody can do it. Weekends Weekends look a bit different though. I wake up around 6:30, do some stretching, and start working on Odin at 7:00. I am able to complete 4 Pomodoros by 10:00. Then I go tidy up my room, make breakfast, drink coffee, and am back to learning at 11:30. On Saturday, I take a rest from working out and study until 14:00, then go to make dinner. If it’s Sunday, however, I work out from 13:30 to 14:00, and then the rest looks the same as Saturday. After my walk, especially on Saturday, I go get groceries, and I’m back home around 17:00, which allows me to do 2-3 more Pomodoros. Altogether, I can complete around 20 Pomodoros during a whole weekend, which is like 10 hours. Sometimes it’s more, sometimes it’s less. If there are any days off, I treat them as if it were a weekend. The Power of the Pomodoro Technique A big part of my learning process was the Pomodoro Technique I already mentioned. It’s all about working in focused 25-minute bursts, called Pomodoros, with a 5-minute break in between. After four Pomodoros, you get a longer break of 15-30 minutes. This method helps you stay focused and avoid burnout. Barbara Oakley’s course on Coursera, “Learning How to Learn,” dives into how our brains work when we’re learning. She talks about the Pomodoro Technique as a great way to break study sessions into smaller chunks, making it easier for the brain to process and remember stuff. Barbara Oakley’s course on Coursera, “Learning How to Learn,” If you’re curious about the science behind effective learning, you should definitely check out this course. I think it’s still free . At least, it used to be when I was told about it when I was starting. I think it’s still free The Odin Project’s curriculum uses similar principles. They suggest structured study sessions like Pomodoros, which align with proven learning methods. Following their directions and instructions helps you not only learn the material but also build strong study habits that will benefit you in the long run . The Odin Project’s build strong study habits that will benefit you in the long run Balancing Workouts and Learning If I didn’t work out, I would be able to learn more and faster, especially on weekdays, but it wouldn’t be too healthy, I bet. Tips for Staying Focused I also have some tips that worked out for me pretty well. Remember, you are going to face a lot of time-fighting procrastination between sessions. It’s very good to: Turn on flight mode on your phone, and put the device as far from you as you can. Turn on flight mode on your phone, and put the device as far from you as you can. Turn on flight mode Don’t use your phone during the 5-minute break between Pomodoros. Stretch instead, walk around the room, and look through the window. Don’t use your phone during the 5-minute break between Pomodoros. Stretch instead, walk around the room, and look through the window. Don’t use your phone If you are tired and feeling sleepy, get a standing desk or use drawers or some other furniture. If you are tired and feeling sleepy, get a standing desk or use drawers or some other furniture. get a standing desk Overcoming Challenges There will be days when you are tired or have many negative thoughts running through your head telling you to stop, that it’s not worth it, that you might be too stupid, or that AI will be coding in the future anyway. If all these happen during your Pomodoro sessions, DON’T WORRY AND DON’T GIVE UP . DON’T WORRY AND DON’T GIVE UP I also had loads of these thoughts, and it’s normal. Some days are worse than others, but I noticed that even the days when I was looking at the screen trying to read boring documentation 5 times helped me to at least stay consistent and build a habit. Finding Enjoyment in the Process At some point, you will realize that you like the process you are going through (if you haven’t liked it yet), and you will notice that all negative thoughts start to fade away, and your motivation goes up day after day, regardless of the level of difficulty. I wrote more about this in my blog post about the calculator project . Happy learning! the calculator project What challenges have you faced in your learning journey? Share your best productivity tips in the comments! Follow me on Twitter for more tips and insights on coding and productivity. Follow me on Twitter

The Odin Project: My 111-Day Experience With It

ওডিন প্রজেক্ট: এটির সাথে আমার 111-দিনের অভিজ্ঞতা

Das Odin-Projekt: Meine 111-tägige Erfahrung damit

El Proyecto Odin: Mi experiencia de 111 días con él

Le projet Odin : mon expérience de 111 jours avec celui-ci

ओडिन परियोजना: इसके साथ मेरा 111-दिवसीय अनुभव

オーディン プロジェクト: 111 日間の体験

오딘 프로젝트: 나의 111일간의 경험

O Projeto Odin: Minha experiência de 111 dias com ele

Проект Odin: мой 111-дневный опыт работы с ним

Odin Projesi: 111 Günlük Deneyimim

Dự án Odin: Trải nghiệm 111 ngày của tôi với nó

奥丁计划：我的 111 天经历

Google's AI Overviews shake up the search landscape, sparking debate on content quality and SEO impact. While some hail them as a boon, others worry AI Overviews might steal content and reduce website traffic. The article explores these concerns and the potential impact on creators, consumers, and the future of search. It's been over two weeks since Google launched AI Overviews for its US-based users (with plans to roll out globally by the end of this year), and they have already become a hot topic in the media. While some experts consider them a boon for ethical website owners and white-hat marketers, believing they will dramatically change the search industry in the coming months, others are less optimistic, accusing Google of stealing their content and violating its own spam policies. On social media, thousands of users are dunking on the inaccuracies and bizarre responses from AI Overviews, such as the claim that a dog played in the NHL (confused by a charity event for rescue pups) or that several US Presidents graduated from UW-Madison (confused by a webpage referencing students with the same names as US Presidents), and even the suggestion that running with scissors is good for health. But jokes aside, some people’s firsthand experiences with how AI Overviews have already impacted their unique content and website traffic raise more questions than answers. According to travel writer David Leiter, whenever someone searched for "Best Slot Canyons Near Las Vegas," his article in the travel blog was always at the top of the search results page. However, after the launch of AI Overviews, the same search brought up an AI-generated response at the top of the page instead. The answer was completely wrong, as AI couldn't differentiate a slot canyon from a regular canyon. Although the AI Overview did include a link to Leiter's article, it was pushed to the very bottom of the results and took time to see. As a result, David believes the potential consequences are especially problematic because he feels "Google's AI is outright stealing content" from creators like himself. He doesn't think "he'll get more traffic than he used to as the top search result." This and other stories I encountered in the media motivated me to research the topic more deeply and seek answers to the questions: How will AI Overviews and other AI-powered enhancements eventually affect search, and who will benefit the most from them? Impact on the SEO Ecosystem Google's AI Overviews are poised to transform the search landscape significantly. One of their most notable capabilities is multi-step reasoning, allowing users to ask complex questions in a single query and receive comprehensive, customized results. For instance, a query about finding the best barbershop or Yoga studio in NYC now yields a detailed results page that previously would have required multiple searches and visits to different websites. These advancements reduce the need for multiple search queries and directly impact how users interact with search engines. Users who find the information they need directly in the AI overview are less likely to visit your website. This can lead to a decrease in your website's traffic and harm your search engine optimization efforts. Lower traffic means fewer opportunities for user engagement, ad impressions, and conversions, directly affecting your site's revenue and growth. Furthermore, reduced traffic can negatively impact your website's search engine rankings over time, creating a vicious cycle where decreased visibility leads to even lower traffic. Moreover, only a few link cards are shown in AI Overviews, making it a "winner takes all" scenario where smaller publishers might struggle if sites with greater authority dominate these spots. This could threaten the web traffic of "millions of marketers, creators, and publishers" who rely on Google's search traffic. Rather than a diverse, user-created internet, the result could be a system where just a handful of large companies provide information. Centralizing information within Google's ecosystem could reduce content diversity and the number of voices available online. This monopolization of information flow is a significant concern for the web. As Google becomes more adept at providing comprehensive answers, user reliance on its services will likely increase. This growing dependence could stifle competition and innovation. The extensive data collection required for personalized AI features raises significant privacy issues. Ensuring user consent and data security will be paramount as AI evolves. However, according to BrightEdge, Google significantly reduced the number of search results showing the SGE in April by 40%, from 65% at the start of the month to around 25% by the end. Additionally, the height of the SGE element was reduced by about 15%, from an average of 1200 pixels to 1050 pixels. As such, Google may be attempting to optimize the user interface and search experience while ensuring that traditional ads still have prominence and visibility. This indicates a nuanced approach to integrating AI overviews rather than prioritizing them over other elements. Impact on Content Creators and Consumers If users increasingly consume AI-generated content in search results, the demand for "human" content decreases. The shift to AI-generated summaries can undermine the value of unique, high-quality content produced by humans, making it harder for content creators to monetize their work through ad revenue, subscriptions, or sponsorships. Additionally, human authors' creative and nuanced perspectives may be undervalued, leading to a homogenized content landscape dominated by AI outputs. As mentioned above, AI can't yet boast of providing truly high-quality information. It still regularly "hallucinates" and provides unreliable information that needs to be verified manually. This poses a significant risk to content consumers who rely on AI overviews for accurate and trustworthy information. Misinformation can have severe consequences in critical areas such as health, finance, and legal advice. For instance, erroneous AI Overviews have been found for some YMYL (Your Money, Your Life) queries, including searches related to health, mental health, finances, and well-being—crucial information that can significantly impact users' lives. Consumers may need to develop new habits of cross-checking AI-provided information with reliable sources, which could be time-consuming and counterproductive. Moreover, over-reliance on AI-generated content could diminish critical thinking skills as consumers might start accepting AI responses at face value without questioning their accuracy. This shift in behavior presents a significant opportunity for innovation. Startups can capitalize on this demand by creating AI-based products that specialize in verifying AI-generated information. Such tools could be invaluable across various sectors, particularly in media, academia, scientific research, R&D, and other domains that rely heavily on accurate information. By developing applications that ensure the reliability of AI content, these startups could address a crucial need in both B2C and B2B markets, fostering greater trust and dependability in AI-driven insights. For marketers, this shift raises questions about traffic impact. However, there is a silver lining: according to Hema Bhuttaraju, the senior director of the AI Overviews project, link cards within AI Overviews generate a higher click-through rate than traditional web search results. Moreover, Google has announced that impressions and clicks from AI overviews will be tracked in the Search Console, providing marketers with data on their performance in this new search paradigm. Mark Traphagen, VP of Product Marketing and Training for seoClarity, states, "Most AI responses target long-tail, low search volume queries, which are generally unlikely to significantly impact most sites." He also found that AI Overviews primarily appear for informational queries—when users want to do something, learn steps, or complete a task. However, the number of queries that deserve summaries (QDS) for AI Overviews has significantly decreased compared to the SGE for informational queries. This suggests that while AI overviews are used for specific types of queries, their overall presence and relevance have diminished compared to other informational tools like SGE. Conclusion In conclusion, while AI Overviews present both challenges and opportunities, their overall impact on high-traffic websites and critical SEO strategies may be limited. The immediate threat is more significant for smaller publishers and content creators, who may see their visibility and traffic decrease. However, businesses and content creators can continue to thrive by focusing on high-quality, unique content that addresses more complex and high-volume queries. As AI technology evolves, all stakeholders must adapt and find ways to coexist with AI-generated content, ensuring a balanced and diverse digital landscape. BTW, Hackernoon’s poll on AI Overviews is still open. You’re welcome to share your input and see the interim results! Google's AI Overviews shake up the search landscape, sparking debate on content quality and SEO impact. While some hail them as a boon, others worry AI Overviews might steal content and reduce website traffic. The article explores these concerns and the potential impact on creators, consumers, and the future of search. Google's AI Overviews shake up the search landscape, sparking debate on content quality and SEO impact. While some hail them as a boon, others worry AI Overviews might steal content and reduce website traffic. The article explores these concerns and the potential impact on creators, consumers, and the future of search. It's been over two weeks since Google launched AI Overviews for its US-based users (with plans to roll out globally by the end of this year), and they have already become a hot topic in the media. While some experts consider them a boon for ethical website owners and white-hat marketers, believing they will dramatically change the search industry in the coming months, others are less optimistic, accusing Google of stealing their content and violating its own spam policies. On social media, thousands of users are dunking on the inaccuracies and bizarre responses from AI Overviews, such as the claim that a dog played in the NHL (confused by a charity event for rescue pups) or that several US Presidents graduated from UW-Madison (confused by a webpage referencing students with the same names as US Presidents), and even the suggestion that running with scissors is good for health. dunking on But jokes aside, some people’s firsthand experiences with how AI Overviews have already impacted their unique content and website traffic raise more questions than answers. According to travel writer David Leiter , whenever someone searched for "Best Slot Canyons Near Las Vegas," his article in the travel blog was always at the top of the search results page. However, after the launch of AI Overviews, the same search brought up an AI-generated response at the top of the page instead. The answer was completely wrong, as AI couldn't differentiate a slot canyon from a regular canyon. Although the AI Overview did include a link to Leiter's article, it was pushed to the very bottom of the results and took time to see. As a result, David believes the potential consequences are especially problematic because he feels "Google's AI is outright stealing content" from creators like himself. He doesn't think "he'll get more traffic than he used to as the top search result." David Leiter This and other stories I encountered in the media motivated me to research the topic more deeply and seek answers to the questions: How will AI Overviews and other AI-powered enhancements eventually affect search, and who will benefit the most from them? How will AI Overviews and other AI-powered enhancements eventually affect search, and who will benefit the most from them? Impact on the SEO Ecosystem Impact on the SEO Ecosystem Google's AI Overviews are poised to transform the search landscape significantly. One of their most notable capabilities is multi-step reasoning, allowing users to ask complex questions in a single query and receive comprehensive, customized results. For instance, a query about finding the best barbershop or Yoga studio in NYC now yields a detailed results page that previously would have required multiple searches and visits to different websites. These advancements reduce the need for multiple search queries and directly impact how users interact with search engines. Users who find the information they need directly in the AI overview are less likely to visit your website. This can lead to a decrease in your website's traffic and harm your search engine optimization efforts. Lower traffic means fewer opportunities for user engagement, ad impressions, and conversions, directly affecting your site's revenue and growth. Furthermore, reduced traffic can negatively impact your website's search engine rankings over time, creating a vicious cycle where decreased visibility leads to even lower traffic. Moreover, only a few link cards are shown in AI Overviews, making it a "winner takes all" scenario where smaller publishers might struggle if sites with greater authority dominate these spots. This could threaten the web traffic of "millions of marketers, creators, and publishers" who rely on Google's search traffic. Rather than a diverse, user-created internet, the result could be a system where just a handful of large companies provide information. Centralizing information within Google's ecosystem could reduce content diversity and the number of voices available online. This monopolization of information flow is a significant concern for the web. As Google becomes more adept at providing comprehensive answers, user reliance on its services will likely increase. This growing dependence could stifle competition and innovation. The extensive data collection required for personalized AI features raises significant privacy issues. Ensuring user consent and data security will be paramount as AI evolves . AI evolves However, according to BrightEdge , Google significantly reduced the number of search results showing the SGE in April by 40%, from 65% at the start of the month to around 25% by the end. Additionally, the height of the SGE element was reduced by about 15%, from an average of 1200 pixels to 1050 pixels. As such, Google may be attempting to optimize the user interface and search experience while ensuring that traditional ads still have prominence and visibility. This indicates a nuanced approach to integrating AI overviews rather than prioritizing them over other elements. BrightEdge Impact on Content Creators and Consumers Impact on Content Creators and Consumers If users increasingly consume AI-generated content in search results, the demand for "human" content decreases. The shift to AI-generated summaries can undermine the value of unique, high-quality content produced by humans, making it harder for content creators to monetize their work through ad revenue, subscriptions, or sponsorships. Additionally, human authors' creative and nuanced perspectives may be undervalued, leading to a homogenized content landscape dominated by AI outputs. human authors' creative and nuanced perspectives may be undervalued, leading to a homogenized content landscape dominated by AI outputs. As mentioned above, AI can't yet boast of providing truly high-quality information. It still regularly "hallucinates" and provides unreliable information that needs to be verified manually. This poses a significant risk to content consumers who rely on AI overviews for accurate and trustworthy information. Misinformation can have severe consequences in critical areas such as health, finance, and legal advice. For instance, erroneous AI Overviews have been found for some YMYL (Your Money, Your Life) queries, including searches related to health, mental health, finances, and well-being—crucial information that can significantly impact users' lives. Consumers may need to develop new habits of cross-checking AI-provided information with reliable sources, which could be time-consuming and counterproductive. Moreover, over-reliance on AI-generated content could diminish critical thinking skills as consumers might start accepting AI responses at face value without questioning their accuracy. This shift in behavior presents a significant opportunity for innovation. Startups can capitalize on this demand by creating AI-based products that specialize in verifying AI-generated information. Startups can capitalize on this demand by creating AI-based products that specialize in verifying AI-generated information. Such tools could be invaluable across various sectors, particularly in media, academia, scientific research, R&D, and other domains that rely heavily on accurate information. By developing applications that ensure the reliability of AI content, these startups could address a crucial need in both B2C and B2B markets, fostering greater trust and dependability in AI-driven insights. For marketers, this shift raises questions about traffic impact. However, there is a silver lining: according to Hema Bhuttaraju , the senior director of the AI Overviews project, link cards within AI Overviews generate a higher click-through rate than traditional web search results. Moreover, Google has announced that impressions and clicks from AI overviews will be tracked in the Search Console, providing marketers with data on their performance in this new search paradigm. Hema Bhuttaraju Mark Traphagen , VP of Product Marketing and Training for seoClarity, states, "Most AI responses target long-tail, low search volume queries, which are generally unlikely to significantly impact most sites." He also found that AI Overviews primarily appear for informational queries—when users want to do something, learn steps, or complete a task. However, the number of queries that deserve summaries (QDS) for AI Overviews has significantly decreased compared to the SGE for informational queries. This suggests that while AI overviews are used for specific types of queries, their overall presence and relevance have diminished compared to other informational tools like SGE. Mark Traphagen Conclusion Conclusion In conclusion, while AI Overviews present both challenges and opportunities, their overall impact on high-traffic websites and critical SEO strategies may be limited. The immediate threat is more significant for smaller publishers and content creators, who may see their visibility and traffic decrease. However, businesses and content creators can continue to thrive by focusing on high-quality, unique content that addresses more complex and high-volume queries. As AI technology evolves, all stakeholders must adapt and find ways to coexist with AI-generated content, ensuring a balanced and diverse digital landscape. BTW, Hackernoon’s poll on AI Overviews is still open. You’re welcome to share your input and see the interim results! BTW, Hackernoon’s poll on AI Overviews is still open . You’re welcome to share your input and see the interim results! Hackernoon’s poll on AI Overviews is still open

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