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If you are here, you are interested in topics such as DevOps , Continuous Processes , and Infrastructures , at least I hope so! This article aims to provide a high-level, simple and practical explanation of what it is Vagrant and how you can use it to improve your workflow. 👨‍💻_@_ 👨‍🏫_at the_ 🖥_, a_ masters level course of the “Master Degree in Information Systems and Computer Engineering” and “Master Degree in Telecommunications and Informatics Engineering” . I’m currently a teacher assistant Técnico Lisboa , and I’m working closely with Dr. Professor Rui Cruz It Infrastructure Management and Administration @ Técnico Lisboa main responsible for the “ ” and “ ” sections. The contribution from Dr. Professor Rui Cruz to this article is enormous, being him the main responsible Setting Up The Experiment So, what is Vagrant? In a very simple way, Vagrant is that is used for building and distributing virtual environments. This means, essentially, that it allows you to manage and share pre-configured virtual machines. an open source project 🔭 Use case #1: Focusing on your task As a developer, have you already spent too much time setting your environment? Vagrant makes it really easy to manage virtual boxes. An already all-in-one virtual machine with all the software and dependencies installed is a great way to make developers focused on their tasks. One just needs to create an optimal virtual box, once, and then it can be distributed to collaborators. No need for setting up the environment, as it should be already set up! In short, you just need to run the machine and focus on the task on hands. 📈 Use case #2: Improving the workflow As a developer, have you already spent too much time fixing bugs that happen on production, but not in the development environment? Firstly, one should follow good workflow practices, such as the ones referenced by , by . Secondly, we can take the next step in our automation process: having the exact same environment, both in development and production (and the intermediary ones). If this is accomplished, the probability of the production app crashing due to an error that was not spot on the development environment is very little, because the environments are the same. this insightful article Peter Murray In short, you can develop without being afraid of errors coming from dependencies and installed software. ⭐️ Use case #3: Distribution Have you spent some time writing extensive documentation on how to do a setup of a project? Sometimes it can be frustrating, as there may be lots of aspects to take care: environment variables, software, and specific configurations. If you have the need for a pre-configured environment, this tool will help you. By packing everything you need on a virtual machine and distributing it, you have done work that others don’t need to (uselessly) replicate. How does it work? According to : Vagrant Environments managed by Vagrant can run on local virtualized platforms such as VirtualBox or VMware, in the cloud via AWS or OpenStack, or in containers such as with Docker. Vagrant provides the framework and configuration format to create and manage complete portable development environments. These development environments can live on your computer or in the cloud, and are portable between Windows, Mac OS X, and Linux. In a nutshell, Vagrant manages the environments, and uses, for example, VirtualBox to provide (launch) the machines. Scripts that run after the machines are launched can be configured through several provisioners such as the , , and . Provisioners are meant to leverage provisioning (installing dependencies), automation, configuration management, and orchestration. This meets the DevOps way of thinking and working. shell Terraform Chef Ansible The following scheme helps us visualize how vagrant works and how it works. Source: https://www.softqubes.com/blog/introduction-of-vagrant-development/ The user creates a Vagrantfile, which is a declarative file (written in Ruby) that describes the type of machine needed, as well as how to configure and provision that machine. The user uses Vagrant to execute the Vagrantfile. Vagrant uses VirtualBox as a provider. It can also use other providers. The machine is up. Vagrant invokes a provisioner to configure the machine. The provisioner provisions the machine. It can be a simple shell script or Ansible, for example. One can access the deployed machine by ssh. That’s it. You can manage and launch virtual machines with a few commands. And its complexity is as much as you want. Enough theory, let’s do it! Let’s get to work, ladies and gentleman. For demonstration purposes, I will follow the first Lab Guide of First, we need to install the required tools to run Vagrant. After that, we will launch a machine. Mininet allows us to create virtual networks, running real kernel and application code. It Infrastructure Management and Administration course, by Professor Rui Cruz. Mininet Setting Up In this section, we are going to perform the setup for Windows, Linux and mac OS. Windows The recommended Package Manager for Microsoft Windows is . Chocolatey To install Chocolatey, open a privileged (i.e. administrative) Windows Command Prompt (cmd.exe) and execute: @"%SystemRoot%\System32\WindowsPowerShell\v1.0\powershell.exe" -NoProfile -InputFormat None -ExecutionPolicy Bypass -Command "iex ((New-Object System.Net.WebClient).DownloadString('https://chocolatey.org/install.ps1'))" && SET "PATH=%PATH%;%ALLUSERSPROFILE%\chocolatey\bin" Now, install the following dependencies through Chocolatey: C:\> choco install wget C:\> choco install git -params “ /GitAndUnixToolsOnPath “ C:\> choco install virtualbox C:\> choco install vagrant C:\> choco install xming Make sure that git executable file path is on the . PATH environment variable In order for xming (an XWindows server) to work, as we are going to need it later, add the environment variable called , with the value . DISPLAY localhost:0.0 Apple macOS The recommended Package Manager for macOS is Homebrew, similar the Linux aptget or yum http://brew.sh. If you do not have XCode installed then open Terminal and at the shell prompt type the following: :~$ xcode -select -- install To install , at the shell prompt paste the script (starting at the ruby invocation) and press ENTER: Homebrew :~$ /usr/bin/ ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)" When it’s done, the shell prompt will say that the installation was successful, and ask you to run brew doctor. Do as it suggests: :~$ brew doctor This will make Homebrew inspect your system and make sure that everything is set up correctly. :~$ brew install wget :~$ brew install git :~$ brew cask install virtualbox :~$ brew cask install vagrant :~$ brew cask install xquartz Linux To install the other packages open a Terminal and issue the following commands. :~$ sudo apt -get install git Please note that for latest distributions of Ubuntu, a careful install of VirtualBox is required as the package architecture has to match the Linux kernel architecture. Additionally, the VirtualBox package in Ubuntu may have some issues when running in RAM-constrained environments. For that purpose, you need to ensure that you have the adequate sources referenced for your kernel architecture. Start by editing the sources list issuing the following command: :~$ sudo nano/etc/apt/sources.list Add the following line to the list (exemplified for 16.04 ’Xenial’ kernel): deb http://download.virtualbox.org/virtualbox/debian xenial contrib According to your distribution, replace ’xenial’ by ’vivid’, ’utopic’, ’trusty’, etc. You also need to add and register the Oracle public key (combined command): :~$ wget -q https://www.virtualbox.org/download/ oracle_vbox_2016.asc -O- | sudo apt-key add - :~$ wget -q https://www.virtualbox.org/download/ oracle_vbox.asc -O- | sudo apt-key add - Now you can add Virtualbox: :~$ sudo apt -get update:~$ sudo apt -get install virtualbox -5.2 For Vagrant, there is still an issue and we need to get the latest version (not in Ubuntu repository) by downloading the package from the and then issuing the following command (from the downloads folder, adapt to your version): Vagrant website :~$ wget https://releases.hashicorp.com/vagrant/2.1.5/ vagrant_2.1.5_x86_64.deb:~$ dpkg -i vagrant_2.1.5_x86_64.deb The Experiment: Create a folder called mininet and enter it, as we are using the . mininet box :~$ vagrant box add mininet ktr/ This will create a box with the downloaded image from vagrant.org. Now, let’s create a Vagrantfile containing our box: :~$ vagrant init ktr/mininet The above command will fetch an already prepared Mininet system in an Ubuntu OS. Without the comments, this is the Vagrantfile created: $script = <<-SCRIPT

SCRIPT Vagrant.configure("2") do |config|config.vm.box = "ktr/mininet" end config.vm.provision "shell", inline: $script Vagrant.configure sets the Vagrantfile version, while config.vm.box sets the box to be used (the one we downloaded). The script is going to run after the machine is launched. Congratulations! You are almost there. Now, we launch the machine: :~$ vagrant up --provider virtualbox --provision This phase may take up a few minutes, depending on the speed of the host system, with an output similar to the following: Bringing machine 'default ' up with 'virtualbox ' provider ... ==> default : Checking if box 'ktr / mininet ' is up to date ... ==> default : Clearing any previously set forwarded ports ... ==> default : Clearing any previously set network interfaces ... ==> default : Preparing network interfaces based on configuration ... default : Adapter 1: nat ==> default : Forwarding ports ... default : 22 => 2222 ( adapter 1) ==> default : Booting VM ... ==> default : Waiting for machine to boot . This may take a few minutes ... default : SSH address : 127.0.0.1:2222 default : SSH username : vagrant default : SSH auth method : private key ==> default : Machine booted and ready ! ==> default : Checking for guest additions in VM ... default : Guest Additions Version : 4.3.10 default : VirtualBox Version : 5.0 ==> default : Mounting shared folders ... Also, you will see the log coming from the provision script. Next, we will establish a session with the system using the following command: :~$ vagrant ssh The session is established and we will get the machine prompt similar to the following: Welcome to Ubuntu 14.04.4 LTS (GNU / Linux 3.13.0 -87 - generic x86_64 ) Last login : Sun Sep 20 22:50:28 2017 from 10.0.2.2 vagrant@mininet :~$ A very simple test can then be performed to verify that all is working correctly by issuing the command ’ ’ at the mininet shell prompt, to create a simple network topology of two hosts (h1, h2) and a switch (s1): sudo mn vagrant@mininet :~$ sudo mn *** Creating network *** Adding controller *** Adding hosts : h1 h2 *** Adding switches : s1 *** Adding links : (h1 , s1) (h2 , s1) *** Configuring hosts h1 h2 *** Starting controller c0 *** Starting 1 switches s1 ... *** Starting CLI: mininet > From this point we can issue the command ’ ’ to verify if we have connectivity between the hosts: pingall mininet > pingall *** Ping : testing ping reachability h1 -> h2 h2 -> h1 *** Results : 0% dropped (2/2 received ) With the command ’ ’ we can verify how the nodes are connected, i.e., host1 is connected by its eth0 port to the switch1 on eth1 port, etc.: net mininet > net h1 h1 - eth0 :s1 - eth1 h2 h2 - eth0 :s1 - eth2 s1 lo: s1 - eth1 :h1 - eth0 s1 - eth2 :h2 - eth0 c0 Issuing the command ’ ’ we can see the IP addresses of the hosts (10.0.0.1 and 10.0.0.2): dump mininet > dump <Host h1: h1 - eth0 :10.0.0.1 pid =1708 > <Host h2: h2 - eth0 :10.0.0.2 pid =1712 > <OVSSwitch s1: lo :127.0.0.1 , s1 - eth1 :None ,s1 - eth2 : None pid =1717 > <Controller c0: 127.0.0.1:6633 pid =1701 > To end the Mininet emulation we use the command ’exit’. mininet > exit We can now exit the session: vagrant@mininet :~$ exit logout Connection to 127.0.0.1 closed . In order to stop the Virtual Machine and to verify the global state of all active Vagrant environments on the system, we can issue the following commands: :~$ vagrant halt ==> default : Attempting graceful shutdown of VM ... :~$ vagrant global-status Confirm that the status of the VM is . powered off Wrapping up You know understand what Vagrant is, how to set up a simple Vagrant file, how to launch a machine and how to use it. 💯 Congratulations! You reached the end! 🦄 Next steps: Cheers, Keep Rocking 💪If you enjoyed this article, please subscribe to my mailing list.Here 👇. It would mean a lot.

DevOps101 — Improve Your Workflow! First Steps on Vagrant

Blockchain gaming has grown in popularity over the past two years and blockchain technology has opened up new gameplay elements for players as well as a way to earn an income through Play-to-Earn systems. One game has taken the trading card game (TCG) style and blended it with a point-and-shoot or pinball style battle system. It’s also created a system for players to convert their cards into blockchain assets. is a trading card game with a pinball-style battle system for mobile devices. Players can collect different hero cards of varying rarity, with some heroes having special abilities. Hero cards can also be fused to enable more powerful abilities in combat. Spells of Genesis Players can also fuse multiple cards and level them up to create blockchain versions of their heroes that can be withdrawn to their wallets. This game seems to be focused on gameplay with an emphasis on fusing and leveling cards to make them stronger before they can be converted to blockchain assets. Now, let’s get straight into how the game works. Gameplay Elements Whilst Spells of Genesis is a trading card game, the battles use a point-and-shoot system that is similar to pinball. Players choose their heroes from their deck of cards, then they can equip them with spells and arrange them on the battlefield. There are three different game modes in Spells of Genesis: There's the campaign mode where players engage in Player-vs-Environment (PvE) battles with over 30 different campaigns and 700 levels to fight through. In return for completing each level, the player receives gold which can be used to buy new in-game cards. The game also has a "Raid" mode where players can engage in Player-vs-Player (PvP) combat with other players based on their rank. Players also receive gold for winning PvP battles. Lastly, there's the "Challenge" mode which is an endless survival mode. Basically, the player has to survive as long as they can whilst taking on endless waves of enemies. Once players have selected their team of up to four cards, they'll be taken to the battle screen where they'll face their opponent. Here players can battle it out by shooting fireballs at their opponent's heroes which can be seen inside their own orbs. The attacks take the form of a fireball which can bounce off of other enemy heroes and ricochet off walls to build up powerful combination attacks. Again, this is where battle style shows a major resemblance to a pinball game. Each attack has a certain damage level and once an enemy hero's health drops down to zero, that hero is destroyed. The enemy hero's health is represented by the size of the orbs they're pictured in. The smaller the orb gets after every successful attack, the lower their health. Enemy orbs also have numbers which are a cool-down counter that you know when that enemy will attack again. Certain heroes come with special abilities, known as spells which include fire, healing, poison, shielding, and targeting buffs. There are six spell elements in the game, with each spell having different effects based on its element: Water - Heals the closest hero to the caster Fire - Shoots a fireball at the closest enemy hero Light - Provides a power buff to the closest player hero Earth - Prevents and reduces damage dealt to the player's team by enemy heroes Ice - Freezes and slows down the closest enemy hero Darkness - Hero cards with this element can cast a targeting spell to increase damage and a poison spell to damage enemy heroes over time These spells can be seen on the battle screen as icons related to the spell type, for example, you will see ember icons for fire spells. To use these spells, players need to hit the spell icons with their fireball shots once they're visible. Blockchain Asset Conversion The game also has a “Blockchainization” feature that allows players to convert in-game cards into blockchain-based cards that can be withdrawn and stored in their wallets. This process works by fusing different cards and leveling them to their max level. The maxed-out card can then be transformed into a blockchain asset, however, a player needs to add their wallet to their account first. Once an in-game card has been converted to a blockchain card, the in-game version is removed and replaced by the blockchain copy which is sent to the player's wallet. This enables players to own their cards which I think is an interesting feature, especially since players have to fully level up and fuse their cards before this is possible. This shows a gameplay-first approach to gaming since players have to work towards owning a blockchain-based card instead of simply paying for it. Conclusion Spells of Genesis is a trading card-style mobile game with pinball-inspired battles. The game takes a gameplay-first approach to mobile blockchain gaming with its focus on battles, fusions, and leveling. True ownership is another interesting feature of the game, with players being able to convert their cards into blockchain assets, only after they have maxed them out.

An Intro to Spells of Genesis: Trading Card Game with Pinball-Style Battles

Craft ropes that dance, limbs that sway, and fish that splash with the magic of physics and images in Phaser. Learn how to effortlessly create a rope-like mesh from an image, connecting it with physics boxes to infuse your game graphics with captivating animation and character. Breathing Life into Game Graphics: A Guide to Animated Mesh Distortion with Phaser As I was playing a handful of entries for yet another game jam, I found myself impressed with this game about dead fish mixed with pinball. Despite being dead, the fish looked so lifelike, but I had no idea how it was possible. I asked the developer how he did it. Intriguingly, he explained, "The fishes are 5 different sized circles connected by revolution joints with a set limit. I used the PixiJS Rope Mesh to draw the fish graphic along the bones ( )." Ref gamedevjs-2022 game jam This sounded too difficult, so I didn't even try to create it. Then, 2 years later, the itch to understand it lingered, and I decided to give it a try myself. In this blog post, I'll take you on the same journey that started with a simple question during a game jam and led to the exploration of animated mesh distortion with Phaser. We'll learn a simple yet powerful technique to add animation to our game graphics. We'll be using Phaser and MatterJs (the physics engine bundled with Phaser) to achieve this. Before we dive into the implementation, it's a good idea to understand 2 main topics: Mesh (image) distortion Physics and constraints It will be easier to go through the implementation when we understand the concept of these two topics. I won't cover all the nitty gritty details and low-level implementation. Rather, I’ll give an easy-to-understand explanation and more info on how we can effectively use them. Mesh distortion A mesh is essentially an image, but we separate the image into sections, with each segment controlling a portion of the image. The mesh is connected with triangles (or quads), each with its set of coordinates. This may sound more confusing than it is, and the following image can help clarify what I mean. I've separated the image into 4 different regions (with 10 control points.) This is our mesh. When we move the control points, the image will be distorted, and change its shape. This is mesh distortion in action. It may be easier to understand if you've worked with photo editing tools, such as Photo Shop or Affinity Photo. The tools have filters to distort the image, e.g. "Perspective" or "Mesh Warp". The principle is the same. We adjust the mesh to shape the image. I used Affinity Photo for the above image. is useful because you can have 1 image and use it for animations. By manipulating the mesh, you can simulate natural movements, deformations, and reactions to different forces, providing a more lifelike appearance to objects or characters. Mesh distortion Physics and constraints In we have a physics engine. The default is called "Arcade," and the second is called "matter," (or "MatterJS".) We'll be using "matter" in this blog post. With this engine, we can create several boxes and connect them using constraints. A constraint is a rule that tell how objects are connected. Phaser, We don't have to care about the implementation details of this, we just need to know how to use them. That's the beauty of a physics engine. All the difficult calculations and collisions are handled for us. Here's an example of how we can connect two boxes The pink line between the boxes is a constraint. The constraint can have spring-like qualities, or be stiff as a bone. The physics engine will make sure to follow the rules, keeping the boxes connected while respecting the other rules of physics, such as gravity and collisions. Connect the mesh to the boxes Once we understand how we can manipulate an image with a mesh, and connect boxes, we'll be able to create something with life. Phaser has some convenient functions to make this easier for us, but before we dive into the implementation, let me quickly go through what we will do. Create a rope mesh with Phaser Create physics boxes and connect them Each box is responsible for distorting portions of the image Update the rope mesh to align with the boxes All we've done is connect the mesh to the boxes. Phaser handles everything else for us. If we drag the boxes around, the image changes too. The implementation The complete code example is available on , and can also be found at the end of this blog post. I'll go through each part in this blog post. CodePen Creating the mesh Phaser has a built in Rope function we can use to create the mesh for us. The rope will help us distort the image correctly. createRope.js // Use Phaser's built in Rope to create a mesh from the image.
  createRope() {
    this.rope = this.add.rope(0, 0, "example");
    this.rope.setPoints(40); // a number that indicates how many segments to split the texture frame into.
  } Creating the physics We'll create boxes, and connect them together. For this example, I like to think of each box as a bone. Each bone is connected together which will create a skeleton, similar to a spine. Create two functions: which creates a list of bones createSkeleton, , which connects the bones together using constraints createSpine createSkeleton.js // Create the physics boxes
createSkeleton() {
  this.skeleton = []; // global variable. We'll use it in another function

  // Create the bones, our physics boxes.
  for (let i = 0; i < 18; i++) {
    const bone = this.matter.add.rectangle(180, 150, 20, 55, {
      friction: 1,
      restitution: 0.06
    });
    this.skeleton.push(bone);
  }
}

// Connect the bones to form our skeleton (spine)
createSpine() {
  const spinePoints = [];
  // Connect each bone with a constraint to create a spine
  // Think of the spine as the curve that goes through the center of each box
  for (let i = 0; i < this.skeleton.length - 1; i++) {
    const boneA = this.skeleton[i];
    const boneB = this.skeleton[i + 1];
    // the points are used to offset the connection betweem the boxes
    const pointA = { x: 10, y: 0 };
    const pointB = { x: -10, y: 0 };
    this.matter.add.constraint(boneA, boneB, 0.1, 1, {
      pointA,
      pointB
    });
    spinePoints.push(...[0, 0]);
  }
  // Creates a smooth line that goes through the center of our bones.
  // A spline will create a smooth curve between each point.
  this.spineCurve = new Phaser.Curves.Spline([0, 0, ...spinePoints]);
} Updating the mesh The final piece of the puzzle is to update the position of the points in our rope mesh according to the position of our skeleton. updateMesh.js updateMesh() {
    // Used for Phaser to know that we must re-render the mesh
    this.rope.setDirty(); 
    let ropePoints = this.rope.points;
    this.spinePoints = this.spineCurve.points;

  // Update the position of the points in our spline curve to the center position of each bone in our skeleton.
  // We do this to make sure we get a smooth curvature and not straight lines between each bone.
    for (let i = 0; i < this.spinePoints.length; i++) {
      this.spinePoints[i].x = this.skeleton[i].position.x;
      this.spinePoints[i].y = this.skeleton[i].position.y;
    }

    // Get a distribution of points along the curve (with the same number of points as our rope mesh.)
    const spinePoints = this.spineCurve.getPoints(ropePoints.length);
  
    // Update the points in our rope mesh according to the curve.
    for (let i = 0; i < ropePoints.length; i++) {
      ropePoints[i].x = spinePoints[i].x;
      ropePoints[i].y = spinePoints[i].y;
    }
  } With this, we've connected our boxes to an image. This technique can be used in different creative ways. Slingshot that stretches like a rubber band Wooden Bridge Fish physics Snake or larva physics Actual ropes or chains I've used the same technique in my (work in progress) game, Fins of Fury. Fish physics The fish connected to a skeleton of physics boxes with different heights. The skeleton is shaped like the fish itself. This will make collisions look real, and the fish will look and feel like an actual fish. Tentacle physics The tentacle will be used as a slingshot in the game. Each bone can be connected with a spring constraint, which helps us stretch the tentacle like a rubber band. The more we stretch the "slingshot" the more tension will be added. Complete code example Here's the complete code example, which you can find on as well. CodePen completeExample.js class Level extends Phaser.Scene {
  rope; // the rope that help us with drawing the mesh
  graphics;
  spineCurve; // the curve that goes from start to end, in the center of each bone
  graphics; // used to draw the spline (curve) that goes through the spine
  spinePoints;
  skeleton;

  preload() {
    this.load.image("example", "assets/sprites/phaser3-logo.png");
  }

  create() {
    this.createRope();
    this.createSkeleton();
    this.createSpine();
    this.createFloor();

    this.graphics = this.add.graphics();
    this.matter.world.setBounds();
    this.matter.add.mouseSpring();
  }

  update() {
    this.updateMesh();
    // this.renderRopeCenterLine();
  }

  // Use Phaser's built in Rope to create a mesh from the image.
  createRope() {
    this.rope = this.add.rope(0, 0, "example");
    this.rope.setPoints(40);
  }

  // Create the physics boxes
  createSkeleton() {
    this.skeleton = [];

    for (let i = 0; i < 18; i++) {
      const bone = this.matter.add.rectangle(180, 150, 20, 55, {
        friction: 1,
        restitution: 0.06
      });
      this.skeleton.push(bone);
    }
  }

  // Connect the bones to form our skeleton (spine)
  createSpine() {
    const spinePoints = [];
    // connect each bone with a constraint to create a spine
    for (let i = 0; i < this.skeleton.length - 1; i++) {
      const boneA = this.skeleton[i];
      const boneB = this.skeleton[i + 1];
      const pointA = { x: 10, y: 0 };
      const pointB = { x: -10, y: 0 };
      this.matter.add.constraint(boneA, boneB, 0.1, 1, {
        pointA,
        pointB
      });
      spinePoints.push(...[0, 0]);
    }
    // Creates a smooth line that goes through the center of our bones (physics rectangles)
    this.spineCurve = new Phaser.Curves.Spline([0, 0, ...spinePoints]);
  }

  updateMesh() {
    this.rope.setDirty();
    let ropePoints = this.rope.points;
    this.spinePoints = this.spineCurve.points;

    for (let i = 0; i < this.spinePoints.length; i++) {
      this.spinePoints[i].x = this.skeleton[i].position.x;
      this.spinePoints[i].y = this.skeleton[i].position.y;
    }
    const spinePoints = this.spineCurve.getPoints(ropePoints.length);
    for (let i = 0; i < ropePoints.length; i++) {
      ropePoints[i].x = spinePoints[i].x;
      ropePoints[i].y = spinePoints[i].y;
    }
  }

  createFloor() {
    const floor = this.matter.add.rectangle(0, 350, 900 * 2, 100, {
      isStatic: true
    });
  }

  renderRopeCenterLine() {
    this.graphics.clear();
    this.graphics.lineStyle(8, 0xffffff, 1);
    this.graphics.fillStyle(0xffff00, 1);
    this.spineCurve.draw(this.graphics, 64);
  }
}

const game = new Phaser.Game({
  type: Phaser.WEBGL,
  width: 900,
  height: 400,
  backgroundColor: "#ffffff",
  scale: {
    mode: Phaser.Scale.FIT
  },
  physics: {
    default: "matter",
    matter: {
      debug: false,
      gravity: { x: 0, y: 2 }
    }
  },
  loader: {
    baseURL: "https://labs.phaser.io",
    crossOrigin: "anonymous"
  }
});

game.scene.add("Level", Level, true); Final words While I initially struggled with programming, I've come to appreciate the value of learning through trial and error. It's important to maintain a determined mindset when tackling new challenges. If connecting the mesh to the boxes seems challenging, try focusing on manipulating the mesh or connecting the physics boxes separately at first. The learning process is a journey, and growth accompanies each step. If you enjoyed this blog post, you may find my other posts about game development in Phaser interesting: Fun with cloth physics and meshes Vector VS Image in your game Also published here.

Supercharging Game Graphics with Physics in Phaser

181 Stories To Learn About Megafansesports

Dedicated to Chapters/Indigo, the national Canadian megachain

As the leading fulfilment platform for digital commerce in India, Delhivery fulfils a million packages a day, 365 days a year. Its 24 automated sort centres, 101 hubs, 3,100+ direct delivery centres, 1000+ partner centres, 11,000+ fleet, and 60,000+ team members run smoothly thanks to a vast network of IoT devices. Thousands of data events and messages are coming in and going out of our pipelines each second. This amounts to a massive daily data volume in terabytes, which makes operational visibility crucial for us and our stakeholders. Recognising the requirements, we decided to build data marts—centralised, eventually consistent databases that offer users quick access to pre-aggregated business data. This allows our stakeholders to quickly access business insights without searching through an entire data warehouse. However, with this daunting scale, one of the major challenges was to maintain data integrity and low latency while providing the capacity for analytical workloads. In this blog, I am going to unpack all of my leanings while migrating our data marts from Amazon Aurora to TiDB, a Hybrid Transactional/Analytical Processing (HTAP), distributed SQL database. Hopefully, this post can provide insights to data engineering leaders, database administrators, or data architects who are considering a similar migration to TiDB or any other HTAP database. OLTP, OLAP, and HTAP To better understand the real-time data marts case at Delhivery, let’s first get familiar with three concepts that are at the core of our use case: OLTP, OLAP & HTAP: Online Transaction Processing (OLTP) systems are designed for transaction-oriented applications, ensuring data integrity through ACID (Atomicity, Consistency, Isolation, Durability) properties. OLTP: Online Analytical Processing (OLAP) systems enable high-speed, multidimensional analysis of large data volumes, aiding in data-driven decision-making. OLAP: Hybrid Transaction/Analytical Processing (HTAP) combines OLTP and OLAP functionalities, permitting real-time analytics on transactional data. HTAP: Real-Time Data Marts Use Case at Delhivery Real-time data marts differ from traditional data marts in that they ingest data in real time, not at specific intervals. These data marts are critical for ground operational decision-making at Delhivery because we can't afford any delay in synchronising these events. Our real-time data mart journey began in 2020 when we identified a need for centralised dashboards—specifically the EYE dashboard. This dashboard's purpose was to provide real-time operational visibility to ground operations, enabling decision-making based on up-to-the-minute data. Examples of usages include: Real-time monitoring of incoming and outgoing connection schedules for Delhivery hubs. Vehicle planning & visibility: Continuous performance tracking of Delhivery's facilities. Performance tracking: Providing the central team with precise information on ground blockers to take appropriate actions. These could be due to various factors such as a dip in center performance, shipment aging, or congestion in incoming and outgoing connections. Centralised control visibility: Tracking of put and pick compliance metrics Compliances: Initial implementation and the challenges We thought of solving our use cases using data warehouse tools like Redshift, and Snowflake but none of these solutions worked for us considering the design pattern and requirement for real-time data ingestion along with merge. Thus, we initially chose Aurora (PostgreSQL) to serve our data mart use case. The data ingestion process around Aurora We architected our real-time data marts using Spark Streaming and Aurora. Our steaming pipeline was very simple--reading data from Kafka, processing data in Spark micro batches, and performing upsert operations in Aurora. Our database was modelled using a multi-layered architecture, which consists of a raw layer, a partitioned layer, and a data marts layer. Users did not have access to view or modify data in the raw layer. The partitioned layer is kept to maintain all partitioned tables (dimension tables generally). Below is a simple schema design of our database: Challenges we faced with Aurora The system initially performed well, until it had to handle a throughput beyond 3K messages per second. This marked the onset of several challenges: As we exceeded a throughput of 3K messages per second, Aurora's Input/Output Operations Per Second (IOPS) limitations became a bottleneck. The scalability constraint had started impacting our operations. Scalability limitation: Every record update led to the creation of a new record and a dead tuple (previous version of the record). When the production rate of these dead tuples outpaced the cleanup process, bloating occurred. Since VACUUM FULL was not able to claim the storage, the disk usage continuously increased. For roughly 5 TB of data, Aurora was using 30+ TB of storage. Bloating issue: The bloating issue is directly tied to our maintenance challenges. With over 70 pipelines and a total write QPS surpassing 5k messages/second, we found PostgreSQL's auto cleanup process, Auto Vacuum, failed to keep pace with the rate of dead tuple generation. Therefore, manually running VACUUM or VACUUM FULL is required to recover the database. Our attempts with PostgreSQL tools like pg_repack and pgcompacttable also proved unsuccessful. Maintenance burden: Consequently, maintenance became increasingly complex and time-consuming. To accommodate the read & write workload, we had to scale to the highest available nodes (24XLarge). This led to an expenditure of approximately $100,000 per month for a three-node Aurora cluster. With this scale, Aurora turned out to be expensive because of IOPS auto-scaling. Cost: Searching for alternatives To resolve Aurora’s limitations, we set out to find a better alternative that met the following requirements: The database should support at least 10k+ write QPS and is horizontally scalable. Scalable with high write QPS: The database should be able to provide high-speed or real-time OLAP capabilities Real-time analytics: The database should be distributed across multiple sites to provide high availability and fault tolerance. Fully distributed: The database should maintain strong consistency, ensuring that all users see the same data. Strong consistency: Considering all the above requirements, we initially explored many PostgreSQL alternatives including Spanner and Yugabyte because we wanted to keep our change management minimal. Spanner Spanner is  a distributed SQL database management and storage service offered by Google.  It is fully managed on the Google Cloud Platform (GCP). However, we found that Spanner might not be a good use case for our architecture due to the following reasons: Spanner does not support schemas. We did not find the proper tools to load historical data. We explored Harbourbridge, an open-source tool for Spanner evaluation and migration. However, it had limitations around 100 GB of data loading. Yugabyte YugabyteDB is a high-performance transactional distributed SQL database for cloud-native applications, developed by Yugabyte. This database is very close to our use case because it was fully PostgreSQL compliant, horizontally scalable, and fully distributed. Unfortunately, it didn’t work as well because of its limitation with scalability, Our success criteria demanded 7k+ transactions per second but Yugabyte was only able to scale up to 5k. We also looked into other possible candidates like BigQuery, but none of them served our requirements well. Landing with TiDB After the above PostgreSQL alternatives, we decided to add HTAP to our requirements, which led us to TiDB. It supports out-of-the-box scalability, consistency, availability, multi-site deployment topology, and many more features. As a distributed database, TiDB has multiple components that communicate with each other and form a complete TiDB system. It is the stateless SQL processing component that provides the client-facing endpoint to the user. It locates the correct TiKV node to connect from PD to get the data. TiDB: It is a distributed transactional key-value data store that keeps the data in the left-closed-right-open range. Data is kept in shards with multiple replicas. TiKV uses the Raft protocol for replication. TiKV: The placement driver (PD) keeps the metadata of the cluster such as shard replica locations, and it’s also responsible for scheduling the shards across TiKV nodes. PD leader handles such tasks while other nodes maintain high availability. PD: The columnar storage extension that uses the Multi-Raft Learner protocol to replicate data from TiKV in real-time, ensuring consistent data between the TiKV row-based storage engine. TiFlash: The following features of TiDB  addressed our key challenges and met our operational requirements: Easy scaling The TiDB architecture design separates computing from storage, letting you scale out or scale in the computing or storage capacity online as needed. The scaling process is transparent to application operations and maintenance staff. ACID compliant TiDB is MySQL-compliant and supports transactions out of the box.  It supports both optimistic & pessimistic types of transactions. This makes it unique from other databases. Highly available TiKV stores data in multiple replicas and uses the Multi-Raft protocol to obtain the transaction log. A transaction can only be committed when the data has been successfully written into the majority of replicas. This guarantees strong consistency and high availability when a minority of replicas go down. Real-time HTAP TiDB combines both row storage (TiKV) and columnar storage (TiFlash) in the same architecture, forming a streamlined tech stack that makes it easier to produce real-time analytics on operational data. Our TiDB Infrastructure Our TiDB infrastructure is deployed over the VMs of leading cloud service providers.   We  use TiUP,  TiDB’s package manager, to manage the cluster and all the administrative operations. Our cluster is deployed over 3 available zones (AZs). Our cluster configurations are as follows: The PD layer has 3 nodes split across Multi-AZs. PD leader handles such tasks while other nodes maintain high availability. PD: The TiDB layer has 9 nodes of the n2-highmem-8 family. These nodes were chosen based on the memory requirements, with 64 GB RAM & 8 Core CPUs allocated for each TiDB node. TiDB: The  TiKV layer has 15 nodes of the n2-highmem-16 family which has 128 GB RAM & 16 vCORE CPUs. TiKV: By deploying our TiDB cluster across multiple AZs and carefully selecting node types to meet our processing and memory needs, we've created a robust, highly available infrastructure capable of handling our high data throughput requirements. Tuning TiDB for Our Case To make it work for our use case, we worked closely with the PingCAP team to tune the database. Here are some of the critical adjustments we made: Index Optimisation Set the following parameters before starting the index. SET @@global.tidb_ddl_reorg_worker_cnt = 16;
SET @@global.tidb_ddl_reorg_batch_size = 4096; Reset to default values after index creation. SET @@global.tidb_ddl_reorg_worker_cnt = 4;
SET @@global.tidb_ddl_reorg_batch_size = 256; Partition Pruning This is mainly important for partitioned tables. It analyses the filter conditions in query statements and eliminates (prunes) partitions  when they do not contain any required data. SET @@session.tidb_partition_prune_mode = 'dynamic'; Tuning analyse Sometimes the auto analyser in TiDB fails if a high volume of data is ingested. In that case, all the queries might use the wrong execution plan and end up scanning the full table. To avoid such a situation we made the following changes in TiDB configurations: set global tidb_max_auto_analyze_time = 86400;
set global tidb_enable_pseudo_for_outdated_stats = off;
set global tidb_sysproc_scan_concurrency = 15; If you are working with partitioned tables,   we suggest you run analyze table operations manually for one partition at a time to avoid analyzing failures. Through adjustments like these, we were able to effectively streamline our use of TiDB, so that we can achieve an optimal performance for our real-time data mart. Our Experience With TiDB Improved queries performance We have bench-marked 400+ queries and found that all the queries are running within SLA. We have even seen a 15-20% performance gain of P95 queries. Easy migration We used the TiDB Lighting tool to migrate all of our table's historical data from Postgres to TiDB. This tool is very easy to use and very fast. We were able to load terabytes of data within roughly 2-3 hours. However, it’s worth noting that there is a lot of tuning required before loading such huge data. Strong support We went through a couple of hiccups during the production infrastructure setup but the PingCAP support team played a very crucial role and helped us tune the cluster for the nature of the workload. Conclusion In this post, we have explored the challenges of using Aurora with our use case of real-time data marts and the migration journey to TiDB. We also discussed how Delhivery is using TiDB at scale. Despite our success with TiDB, we acknowledge that no solution is perfect, and effectiveness can vary depending on the use case. In TiDB, we noted a couple of areas for improvement, including the lack of out-of-the-box support for materialized views and native quota management. However, with appropriate workarounds and adjustments, we have managed to address these limitations effectively. So far, we have deployed TiDB in our production environment. Based on our benchmarks, TiDB enables us to handle over thousands of requests per second with less than 100ms latency. Moving forward, we will continue to explore more use cases that require a robust, consistently distributed database. References https://docs.pingcap.com/tidb/stable/tidb-lightning-overview https://reorg.github.io/pg_repack/ https://github.com/dataegret/pgcompacttable https://cloud.google.com/spanner https://www.yugabyte.com/yugabytedb/ https://cloud.google.com/bigquery/ https://docs.pingcap.com/tidb/dev/transaction-overview https://proxysql.com/ Author: (Senior Engineering Manager @ Delhivery) Hari Kishan (Director of Technology @ Delhivery) Akash Deep Verma

Delhivery’s Data Marts - Migration Journey from OLTP to HTAP

Data Marts de Delhivery: viaje de migración de OLTP a HTAP

Data Marts de Delhivery - Parcours de migration d'OLTP vers HTAP

डेल्हीवरी का डेटा मार्ट - ओएलटीपी से एचटीएपी तक प्रवासन यात्रा

Delhivery のデータ マート - OLTP から HTAP への移行ジャーニー

Data Marts da Delhivery - Jornada de migração de OLTP para HTAP

Data Marts của Delhivery - Hành trình di chuyển từ OLTP sang HTAP

Delhivery 的数据集市 - 从 OLTP 到 HTAP 的迁移之旅

A look at two databases that have made claims to the Kubernetes native label: TiDB and DataStax Astra DB. The cloud computing revolution has inspired and benefitted from multiple interrelated trends. The availability of self-service, public cloud infrastructure has helped to drive the adoption of microservice architectures and DevOps practices, including automation and observability. The drive toward containerization and container orchestration has led to the widespread adoption of Kubernetes as an environment for managing cloud-native applications. But one of the lagging areas in this revolution has been data and data infrastructure. For too long, data has been something that has lived outside of Kubernetes, leading to a lot of extra effort and complexity for developers in deploying cloud-native applications. One oft-repeated axiom in the early years of Kubernetes was that it was not yet ready for stateful workloads. Thankfully, a major shift has been quietly underway and has reached a point of maturity. The transformation happened slowly initially, beginning with efforts to containerize existing databases. This worked relatively well in small databases that ran on a single compute node, or databases that had been designed in a cloud-native world, like Apache Cassandra and DynamoDB, but challenges remained. Over the past two to three years, a new generation of databases has emerged. These “Kubernetes native” databases have been designed from the ground up to run on this open-source orchestration system. Here, we’ll define the qualities that make a database Kubernetes native and the benefits of adopting a Kubernetes native database. To do that, we’ll look at two databases claiming the Kubernetes native label: TiDB and DataStax Astra DB. Kubernetes Native MySQL with TiDB First, let’s examine a database with a relational emphasis: (short for Titanium Database). TiDB is an open-source system built by PingCAP that provides a and a columnar database to support hybrid transactional and analytic processing (known as HTAP, for short). TiDB MySQL-compatible database As shown in Figure 1 below, TiDB has a microservice design. The TiDB query layer, TiKV MySQL databases, TiFlash columnar databases, Spark nodes, and metadata management are each deployed as scalable microservices in their clusters. This design separates compute-intensive work from storage-intensive work, as the query and database layers are independently scalable. One critical commitment the TiDB creators made was that the database only runs on Kubernetes. Is that enough to make it Kubernetes native? Let’s dig a bit deeper. First, TiDB is deployed and managed by a Kubernetes operator using (CRDs). The TiDB CRDs include the TiDBCluster, which enables you to specify the scaling and configuration of each microservice and how the database layer components use storage through Kubernetes Persistent Volumes. Additional CRDs are used to deploy monitoring tools and manage operational tasks like backup and restore. custom resources that interfaces with the default K8s scheduler to make more application-aware scheduling decisions. This emphasis on using existing Kubernetes capabilities where available is the mark of a Kubernetes native database. TiDB also has an optional scheduler extension Kubernetes Native Cassandra with DataStax Astra DB Now, look at another Kubernetes native database and note some similarities and differences. that was one of the first to claim to be cloud native, but what does it look like to deploy Cassandra in Kubernetes? is a highly scalable NoSQL database Cassandra that has been factored into microservices, as shown in Figure 2. is a version of Cassandra DataStax Astra DB Like TiDB, the database includes microservices concerned with query processing and data storage, as well as services for identity and access control, data repair, and backup/restore. The data services are particularly interesting in their use of , with Kubernetes Persistent Volumes used only for caching and object storage used for longer-term persistence. Separating compaction into its service enables this compute-intensive processing to happen in the background without affecting the performance of data services serving read and write traffic. storage Astra DB is offered as a managed service available in multiple cloud regions. Each region contains a data plane consisting of the services mentioned above, managed by a Kubernetes operator, as well as infrastructure services, including the stack for observability and for metadata management. Kube-Promethus etcd The data planes are managed by a control plane that can run in one or more clouds to manage customer accounts and databases and provision Kubernetes clusters in new regions. in which multiple user databases can share the same microservices and supporting infrastructure, lowering unit economics for smaller-scale users. One novel aspect of Astra DB is its multi-tenant architecture As users grow their applications, they can move to dedicated resources to achieve optimal performance at scale, all on a “ ” basis. pay-as-you-go Kubernetes Native Database Principles Based on our observations of TiDB and Astra DB, we can derive some ideas of what makes a database Kubernetes native. Many of these correspond to a list of principles for cloud-native data, which I described in an : earlier article First, a database broken into constituent microservices enables each service to be scaled independently. Some types of compute-intensive processing may even be scaled to zero for a true serverless solution, especially when combined with a multitenant design. Composable microservice architecture: Microservices composed of a Kubernetes native database should make maximum usage of Kubernetes APIs for managing the fundamental resources of cloud-native applications: compute resources such as , Kubernetes ingress and services for exposing network access to data and more. This includes leveraging capabilities already present in Kubernetes, such as etcd for metadata management, instead of bringing along components with duplicative functionality. Treat compute, network, and storage as commodities: StatefulSets and deployments for managing workloads, the Persistent Volume subsystem for storage Following common patterns for Kubernetes applications will yield multiple operational benefits, for example, . By default, Kubernetes itself sets a great example that databases should follow for how to be secure: using Kubernetes Secrets to distribute security credentials, only exposing ports as needed, and so on. Leverage Kubernetes best practices: exposing liveness and readiness checks on each microservice to help availability and exposing metrics via the Prometheus PromQL API for observability A Kubernetes native database should embody the Kubernetes principles of declarative management via operators and custom resources, rather than relying on legacy database management UIs and CLIs. When necessary, . The goal is a clean separation of data plane functionality (managing data) from control plane functionality (managing the database). Declarative management via operators: Kubernetes extension points, such as scheduler extensions, can be used to add application-specific behavior Databases and other data infrastructures that faithfully adopt these principles will yield benefits, including a , lower operational complexity resulting in faster time to market, and standards-compliant solutions meeting today’s high availability and security demands. high performance for optimal cost at all scales The Future of Kubernetes Native Data Infrastructure Much progress is still to be made, and it’s not limited to databases alone. Kubernetes native principles can be applied to other types of data infrastructure, including streaming, analytics, and machine learning. Kubernetes native solutions will continue to make strides in multicluster and multi-cloud deployments to scale globally and will adopt multitenancy and serverless principles for better cost optimization. Kubernetes itself has room for improvement in adding more flexibility to StatefulSets and support for multicluster federation. The key to continued progress is open collaboration. The is a highly active group of data geeks bringing together builders of data-intensive applications and the infrastructure that supports them. Data on Kubernetes Community Join us to talk about ideas like developing reusable operators that can manage multiple databases or defining a common set of CRDs for concepts like backup/restore and data loading. Together we’ll continue to push the horizon of cloud computing for the benefit of all. Learn more about Kassandra native databases and more at the digital summit on March 14, 2023. Cassandra Forward This article is based on Chapter 7, “The Kubernetes Native Database,” from the O’Reilly book “ Managing Cloud Native Data on Kubernetes ” by Jeff Carpenter and Patrick McFadin. [ By Jeff Carpenter, DataStax Jeff Carpenter has worked as a software engineer and architect in multiple industries and as a developer advocate at DataStax, helping engineers succeed with Apache Cassandra. He's involved in multiple open source projects in the Cassandra and Kubernetes ecosystems, including Stargate and K8ssandra. He is co-author of the O’Reilly books "Cassandra: The Definitive Guide" and "Managing Cloud Native Data on Kubernetes."

Kubernetes-Native Database: TiDB Vs. DataStax Astra DB

Base de datos nativa de Kubernetes: TiDB vs. Base de datos DataStax Astra

Base de données native Kubernetes : TiDB Vs. DataStax Astra DB

कुबेरनेट्स-नेटिव डेटाबेस: TiDB बनाम। डेटास्टैक्स एस्ट्रा डीबी

Kubernetes ネイティブ データベース: TiDB Vs. DataStax アストラ DB

Banco de dados nativo do Kubernetes: TiDB vs. Data Stax Astra DB

Cơ sở dữ liệu gốc Kubernetes: TiDB Vs. DataStax Astra DB

Kubernetes 原生数据库：TiDB 对比。 DataStax Astra 数据库

Approaches to Video Game Asset Interoperability

Moledao, a social platform for blockchain enthusiasts, announced today its upcoming Web 3.0 Hackathon. This pioneering global hackathon will be held in the Metaverse from 15th November 2021 to 9th January 2022. Web 3.0 is the vision for the next internet generation that is decentralized, verifiable, and secure. Web 3.0 Hackathon is supported by Bybit, BitDAO, Web3 Collective, and Blockchain Infrastructure Alliance, which includes established organizations like EthSign, Mask, Torus, Biconomy, Polygon, PingCAP, and Alchemy Pay. The hackathon aims to be a platform that empowers developers to create projects that are innovative, user-friendly, and applicable in real-life. There are three phases to the hackathon: Registration + Team Formation, Preliminary Review, and Finals. Registration + Team Formation: 15th November — 31st December Preliminary Review: 15th November — 31st December: Project Submission Period 31st December (before 24:00): Deadline for Project Submission 1st January — 3rd January: Preliminary Review by Judges 3rd January(night): Announcement of Finalists Finals: 8th January (morning): Opening ceremony for Hackathon finals 9th January (afternoon): Project Demo + Award ceremony (Held in Cryptovoxels) Prize Allocation: 1st Prize: $30,000 2nd Prize: $20,000 3rd Prize: $10,000 Details of other prizes will be announced at a later date. All entries will be scored based on the following criteria: Commercial value (25%) Whether the problem has a solution, whether it is applicable in real life, and whether it has potential commercial value. Creativity (25%) The work breaks through conventional thinking, limitations and is innovative. Technical Challenge (25%) The technical solution of the work has a certain degree of technical difficulty, or has a new breakthrough in technology. Percentage Completion (25%) How and how much of the work is completed, what is the proportion of coding, whether it can be demonstrated, avoid PPT projects. Main Theme: Web3.0 Welcome to the Web3.0 era. Web3.0 is the vision for the next Internet generation, which is decentralized, verifiable, and secure, where users are able to control their own identities, data, and destinies. In the present exploration stage of the Web3.0 world, new and exciting things have been created! We have seen how multichain decentralized applications (dApps), Metaverse, and Decentralized Autonomous Organizations (DAO) are slowly shaping the future, which brings our reality closer to the Web3.0 dream. Let’s buidl the future together! Recommended Track 1：Multichain Dapp Public chain, side chain, Layer 2 solutions have been on the rise recently, especially with Ethereum network congestion and high gas fees. With the Ethereum Virtual Machine (EVM) as the common standard, it is now even easier for developers to deploy applications. However, current solutions are not so user-friendly with problems such as switching between networks, data issues, native token fees, and limited cross-chain liquidity. There is still a huge room for improvement in the development and design of multichain dApps. For this track, you can explore optimizing the user experience of multichain dApps, such as multichain gas fee proxy, cross-chain solutions, and many more! Recommended Track 2：Metaverse Infrastructure Communities are moving towards the Metaverse. Virtual land trading, virtual buildings construction. We have gone beyond the limitations of the physical world and your own imagination! In this track, you can explore creating Metaverse portals, developing virtual worlds, and/or building on current Metaverse platforms such as Cryptovoxels, Decentraland, and The Sandbox. Recommended Track 3: DAO Toolkit Web 3.0 has enabled the rise of Decentralized Autonomous Organization (DAO), the new (and preferred way) for crypto natives to build and organize truly community-owned communities. What comes next? DAOs would require a full ecosystem that covers wallets, cross platforms integrations, payroll management, resolution management, and many more. In this track, you can explore developing various solutions for DAOs such as payroll systems, project investment, and community management! New and exciting things are gradually shaping the future, which brings our reality closer to the Web 3.0 dream. Register now for the hackathon and get access to free exclusive Web 3.0 related workshops . here About Moledao Moledao is a social platform for all blockchain enthusiasts to learn about the latest in blockchain, grow and contribute to building more innovative ideas with the help of experienced blockchain pioneers and innovators. It aims to bring blockchain to everyone and grow the ecosystem through education and global hackathons. Related Links Registration: https://www.moledao.io/#/hackathon Event communication channel: https://discord.gg/5m4w49uXJg General community discussion: t.me/moledao

Moledao Web 3.0 Hackathon in the Metaverse: Over $100,000 Prize Pool!

The Kirby games franchise is charming and surprisingly filled with depth, but it never managed to reach the level of fame that other Nintendo titles gained. Despite this, it’s a series that’s still going strong today, with its coming in March 2022. most recently announced title Kirby games deserve more recognition, and it’s interesting to see just how much recognition they’ve truly gained to this date. To honor some of the best titles in the franchise, here are the top 10 Kirby series games ranked by how much they sold. it’s difficult to find truly accurate lifetime sales data for the whole Kirby series. The sources for this data might not be entirely reliable, so feel free to double-check the listed numbers if they don’t seem right to you. Side note: The Top 10 Kirby Games Ranked by Sales 10. Kirby’s Return to Dream Land 9. Kirby’s Epic Yarn 8. Kirby: Nightmare in Dream Land 7. Kirby’s Pinball Land 6. Kirby: Squeak Squad 5. Kirby’s Dream Land 2 4. Kirby Triple Deluxe 3. Kirby Super Star Ultra 2. Kirby Star Allies 1. Kirby’s Dream Land 10. Kirby’s Return to Dream Land (Wii) - ~1.79 Million Copies Though it ended up changing the landscape of Kirby games for years to come, Kirby’s Return to Dream Land only makes it to number 10 on this list. It was the first console-made Kirby game to feature full multiplayer alongside extra modes and challenges, and many of the improvements and changes it made to the series are present today. Despite its placement, you’d be hard-pressed to find a Kirby fan that wouldn’t consider this game to be one of the best in the series. 9. Kirby’s Epic Yarn (Wii) - ~1.85 Million Copies Kirby’s Epic Yarn isn’t actually much of a Kirby game. Without copy abilities or even being able to inhale enemies, this game offers a more lighthearted take on traditional Kirby gameplay. It’s an even more kid-friendly version of an already kid-friendly series...but as a result, it has some of the best charm and most relaxing atmospheres you’ll find in any video game. 8. Kirby: Nightmare in Dream Land (GBA) - 2.1 Million Copies A remake of the NES title, Kirby’s Adventure, this game featured updated graphics and new game modes to draw in fans both old and new. Kirby: Nightmare in Dream Land’s changes were pretty miniscule overall, but an already fine game with updated visuals didn’t need much more to reach over 2 million copies sold. 7. Kirby’s Pinball Land (GB) - 2.19 Million Copies This is honestly an odd one to see here. Kirby’s Pinball Land was pretty much just pinball with a Kirby skin over it. It release on the Game Boy, and also the console the first-ever Kirby game released on. Simple games like these had great appeal on handheld systems, so that could be at least one reason this spinoff found such success. did one of the best-selling handheld consoles ever 6. Kirby: Squeak Squad (DS) - ~2.2 Million Copies Kirby: Squeak Squad is, in the context of the Kirby series, a little weird. It featured an in-game view of Kirby’s stomach where items and treasure could be stored, as well as unique mouse-like enemies known as the Squeaks. It’s also the first game - and so far, the only game - with copy abilities like Animal and Metal. Though it hasn’t been as much of an influence on the series as other games, it had some creative ideas that certainly helped it rise to its level of success. 5. Kirby’s Dream Land 2 (GB) - 2.36 Million Copies As the sequel to the first-ever Kirby game, Kirby’s Dream Land 2 manages to crown itself as part of the top 5 best-selling games of the series. Being the first game to feature animal buddies and the fan-favorite Dark Matter antagonist, Dream Land 2 offered a new perspective that other titles couldn’t quite measure up to. It might not be the most iconic game, but its spot in the top 5 was well-earned. 4. Kirby Triple Deluxe (3DS) - 2.61 Million Copies This game built off of Return to Dream Land, downsizing its content to match a handheld system’s scale while also refining it to make the entire experience even more fun. Kirby Triple Deluxe featured new copy abilities, 2.5D level structures, and - in this writer’s opinion - some of the best music of any game out there. Fans of this game should check out Kirby: Planet Robobot if they haven’t already; it didn’t make the list, but it’s a perfect companion piece to a fantastic title. 3. Kirby Super Star Ultra (DS) - ~2.9 Million Copies A remake of the original SNES title, Kirby Super Star Ultra ended up being more than just a prettier game. Not only did it feature updated music and graphics, it included entirely new bosses and story content. Some of this content became a staple in newer games, making Super Star Ultra a must-play for anyone even remotely interested in the Kirby series. 2. Kirby Star Allies (Switch) - ~3 Million Copies As the latest mainline title, the success of Kirby Star Allies gives high hopes for the series’s future. Featuring characters from previous games and more expansive gameplay options, Star Allies brings the tried-and-true Kirby formula to one of its highest peaks yet. 3 million copies might not seem like a lot compared to other franchises. For example, that number might only come somewhat close to . However, it’s a number the Kirby series can be proud of...especially when considering the gap in total sales between second and first most-sold games in the Kirby franchise. the top 10 best-selling Zelda titles 1. Kirby’s Dream Land (GB) - 5.13 Million Copies Having been alluded to throughout this list, Kirby’s Dream Land is the first and most successful Kirby game ever. Kirby wasn’t even fully pink by this time - his appearance on the box art was based on the gray palette of the Game Boy. Despite the series only finding its feet, Kirby’s Dream Land became a success that hasn’t been replicated by the series even today. With renewed interest in the series thanks to the success of Star Allies, and a brand new style of gameplay in Kirby and the Forgotten Land, this list might end up blown away before long. The Kirby series of games is one filled with unique ideas and interesting possibilities for the future - both inside and outside the titles themselves. References: Kirby for Series - Sales, Wiki, Release Dates, Review, Cheats, Walkthrough (vgchartz.com) Kirby (series) - Wikipedia Kirby | Video Game Sales Wiki | Fandom Nintendo software and hardware sales data from 1983 to present | Install Base (installbaseforum.com) All images taken from Unofficial Kirby Wiki

Top 10 Kirby Series Games Ranked by Sales

Parsing SQL queries provides superpowers for monitoring data health. This post describes how to get started on parsing  SQL for data observability. Query history of a data warehouse is a rich source of information to glean how data is used in your organization. Many aspects of data observability can be tracked by analyzing query history. For example, query history analysis can extract: Popular tables and columns Unused tables and columns Column-level lineage Freshness These statistics also help to automate common data engineering tasks like: Backup and Disaster Recovery Triage Data Quality issues Track sensitive data and how they are used. Challenges and Approaches SQL language is an ISO/IEC standard and the latest version is . However, every database implements the standard differently, uses different function names for the same operation, and has extensions to access specific custom features. Therefore, there isn’t one SQL parser for dialects of all popular databases and data warehouses. SQL2016 Regular expressions is a popular approach to extract information from SQL statements. However, regular expressions quickly become too complex to handle common features like WITH, sub-queries, windows clauses, aliases and quotes. is a popular Python package that uses regular expressions to parse SQL. sqlparse An alternate approach is to implement the SQL grammar using parser generators like . There are similar open-source parser generators in other popular languages. There are multiple projects that maintain parsers for popular open-source databases like MySQL and Postgres. For other open-source databases, the grammar can be extracted from the open-source project. For commercial databases, the only option is to reverse engineer the complete grammar. There are SQL parser/optimizer platforms like that help to reduce the effort to implement the SQL dialect of your choice. ANTLR Apache Calcite Open Source Parsers Some popular open-source databases and data warehouses are: MySQL/MariaDB parser is a MySQL parser in Go. Pingcap in phpmyadmin is a validating SQL lexer and parser with a focus on MySQL dialect. SQL Parser Postgres extracts the parser (written in C) from the Postgres project and packages it as a stand-alone library. This library is wrapped in other languages by other projects like: libpg_query : Python pglast : Ruby pg_query : Golang pg_query_go : in Node and in the browser JS psql-parser pg-query-emscripten : Rust pg_query.rs Multiple Engines implements Apache Hive, Presto/Trino and Vertica dialects. queryparser implements BigQuery, Spanner, and Dataflow dialects. zetasql Generic Parsers : Python sqlparse : Rust sqlparser-rs : Python mo-sql-parseing Platforms Parser/Optimizer platforms implement the common SQL language features and allow customization as a first-class feature of the platform. Two popular open-source projects are: is a popular parser/optimizer that is used in popular databases and query engines like , , and . Apache Calcite Apache Hive BlazingSQL many others can parse multiple SQL dialects like MySQL, Postgres and Oracle. The grammar can be modified to support other SQL dialects. JSQLParser Apache Calcite allows customizations at various points of the parsing process. Parser rules can be to support custom syntax. changed Conventions such as quotes vs double quotes, case sensitivity. Add optimizer rules. Apache Calcite also provides visitors for traversing the SQL execution plan. Visitor pattern is an algorithm to traverse a SQL plan. Practical tips to Getting Started There are many abandoned open-source SQL parsers. The first filter is to use a project that will be supported in the future. For popular databases such as Postgres and MySQL/MariaDB, there are parsers available in multiple programming languages. What if there is no parser for your database? Most teams do not create a parser from scratch. A popular option is to use the Postgres parser and then add custom SQL syntax. AWS Redshift, Vertica, and DuckDB are examples. Use a Postgres SQL parser to parse the query history of these databases to parse the majority of the queries. Many queries will fail to parse such as UNLOAD in AWS Redshift. If it is important to also parse the variants, consider modifying the projects to accept the custom grammar OR use a platform like Apache Calcite. Conclusion There is a demand for SQL parsers to build reports on database or data warehouse usage. There are a number of good open-source projects. However, there is a steep learning curve to use these projects and in many cases, a project may not fit your specific requirements. Struggling with parsing query history? Get in touch Also published . on Tokern

14 Open Source SQL Parsers

14 analizadores SQL de código abierto

Before the Nintendo DS and the Nintendo Switch, the handheld consoles that ruled the ‘90s were the Game Boy and the Game Boy Color. With their simple designs and their ability to easily fit in your pocket, the Game Boy and Game Boy Color were easy picks when choosing a handheld console. Apart from these features, what made the consoles even more special was their game catalogs. Iconic games such as Super Mario Land and Pokemon Red and Blue made their debut on the Game Boy, and those weren’t the only ones. The Game Boy and Game Boy Color had an unlimited amount of fantastic games. Here are the best Game Boy Color games and Game Boy games ranked by sales. Best Game Boy/Game Boy Color Games 10. Wario Land: Super Mario Land 3 9. Pokemon Pinball 8. Dr. Mario 7. Pokemon Crystal 6. Super Mario Land 2: 6 Golden Circles 5. Pokemon Yellow 4. Super Mario Land 3. Pokemon Gold and Silver 2. Pokemon Red, Green, and Blue 1. Tetris 10. Wario Land: Super Mario Land 3 - 5.1 Million Copies Sold Mario’s long-standing counterpart, Wario, would headline his own game on the Game Boy. Released in 1994, Wario Land: Super Mario Land 3, sees Wario trying to gain money to buy his castle; he does this by stealing from pirates. Similar to the gameplay of previous Mario Land games, Wario Land puts more emphasis on collecting coins. Although Wario Land didn’t sell as well as its predecessors, their sales numbers are nothing to scoff at. The game managed to sell worldwide. 5.1 million copies This wouldn’t be the last time Wario starred in his own game; he would go on to star in the WarioWare franchise. The latest game in the series, , is set for release in September 2021. WarioWare: Get It Together 9. Pokemon Pinball - 5.3 Million Copies Sold Pokemon was (and still is) an unstoppable force. Every game they release seems to be destined to sell well. So, it’s no surprise that it has more than one entry in this list, including this game, Pokemon Pinball. Released in 1999, the game is relatively self-explanatory; it’s a Pokemon-themed pinball game featuring iconic Pokemon. The game would go on to sell an impressive , making it one of the best Game Boy Color games in terms of sales. Its popularity would lead to a sequel getting made in 2003. 5.3 million copies Pokemon Pinball: Ruby and Sapphire, was released for the Game Boy Advance and would add more features than seen in the previous game. 8. Dr. Mario - 5.3 Million Copies Sold People love a good pinball game, but they also love a good puzzle game, especially one that stars Dr. Mario. This game sees the titular character trying to get rid of viruses, you do this by matching color pills with one another. If the pills reach the top, you lose. How Mario can juggle being a plumber, a doctor, and a hero of the Mushroom Kingdom is unexplainable, but he does it well. This fun game made its debut in 1990, and would sell exceptionally well; of Dr. Mario were sold worldwide. Modern versions of Dr. Mario are being played, with Dr. Mario World being available to play on mobile phones. 5.3 million copies Although the game is different than the Game Boy version, the concept is still the same: get rid of the viruses. 7. Pokemon Crystal - 6.3 Million Copies Sold Pokemon Crystal was released in 2001 in Japan and is an updated version of Pokemon Gold and Silver. In a first for the series, players were able to choose whether their character was a male or female. The game also introduced Eusine, a character that would make appearances in the Pokemon anime. Although Pokemon Crystal debuted just a year after Pokemon Gold and Silver, that didn’t hurt its sales in the slightest. The game would sell an astounding . 6.3 million copies If you’re looking to play it on a modern console, you’re in luck. The game is available to buy and play on the . Nintendo 3DS 6. Super Mario Land 2: 6 Golden Coins - 11.1 Million Copies Sold Before Wario was trying to steal coins to buy his castle, he tried to take over Mario’s land and tried to steal his castle. For Mario to confront Wario and take back his castle, he must collect 6 coins. Released in 1992, this sequel to Super Mario Land managed to retain elements from the first game, but still added new features to make the game fun and refreshing. Mario fans loved this game, and it’s clear by its sales numbers, Super Mario Land 2 sold . But it isn’t just the amount of copies sold or its gameplay that makes it one of the best Game Boy games of all time. 11.1 million copies It’s the fact that it introduces Wario, a character that would become a staple in the Mario franchise. 5. Pokemon Yellow - 14.6 Million Copies Sold Just like Pokemon Crystal was an updated version of previous Pokemon titles, Pokemon Yellow is the same thing. It’s an updated version of the popular games, Pokemon Red and Blue. Pokemon Yellow is based on the Pokemon anime and features characters from the show. Just like the anime, Pikachu plays a big part in the game and has a strong relationship with the main character. With how popular the games and the anime were (and still are), it’s not a shock that Pokemon Yellow was flying off the shelves. The game sold worldwide. 14.6 million copies Just recently, a remake was released titled, , and it allowed players to connect their Pokemon Go accounts to their game. Pokemon: Let’s Go Pikachu and Let’s Go Eevee! 4. Super Mario Land - 18 Million Copies Sold Released in 1989, Super Mario Land featured Mario going on an adventure on the Game Boy. Instead of saving Princess Peach like he usually does, this time Mario has to save Princess Daisy. And instead of fighting the famous villain of the series, Bowser, Mario has to fight the alien Tatanga. Although the story was a departure from the series, it was still just as fun. The game’s story derived from previous installments in the Mario franchise, but that did nothing to hurt its sales. Super Mario Land sold . 18 million copies The success of this game would launch two sequels, both of which have made it on this list. Because of how fun it is and the legacy it created, Super Mario Land deserves to be called one of the best Game Boy games ever. 3. Pokemon Gold and Silver - 23.1 Million Copies Sold A year before Pokemon Crystal debuted, Pokemon Gold and Silver were making waves worldwide. They’re also the sequels to the franchise’s first pair of games, Pokemon Red and Blue. Instead of taking place in the first game’s Kanto region, Pokemon Gold and Silver take place in Johto and feature new Pokemon. However, the player can visit Kanto and collect the Pokemon from that region. Like the first installments in the franchise, Pokemon Gold and Silver would be a financial success; were sold. The legacy of this game can’t be understated with it receiving an enhanced version, the aforementioned Pokemon Crystal. 23 million copies Apart from that, remakes of Pokemon Gold and Silver were also released titled, Pokemon HeartGold Version and Pokemon SoulSilver Edition. 2. Pokemon Red and Blue - 31 Million Copies Sold The games that started the entire franchise, Pokemon Red and Blue (or Pokemon Red and Green in Japan) were first released in Japan on the Game Boy in 1996. It allowed players to jump into the Kanto region and try to collect all the Pokemon the game had to offer. Along the way, they could challenge Gym Leaders and work their way up to being the very best. Pokemon Red and Blue would take the world by storm and sell , and it would be the first step into becoming the gigantic franchise it is today. Movies, anime, trading cards, and worldwide recognition for Pokemon all started with these two games on the Game Boy. 31 million copies Although they're not the most sold games on the console, they are pretty close, and it’s not hard to argue that these are the best Game Boy games the console had to offer. 1. Tetris - 35 Million Copies Sold Tetris seems as though it’s been around forever, but it first debuted in 1984. The game is a classic and has stood the test of time. Tetris is relatively simple, tetrominoes (or blocks) fall from above and the player has to accommodate them so that they fit with the rest of the blocks. Although the idea is simple, the execution can be complex, with the player having to figure out where to best place the blocks in a short amount of time. Tetris has become a phenomenon worldwide, and even people who aren’t heavily into video games, have surely played Tetris at least once. Tetris has seen a lot of success in different formats, including the Game Boy. It sold on the console, making it the best-selling Game Boy game of all time. 35 million copies The Game Boy and Game Boy Color games on this list have stood the test of time and created legacies that are still standing today. Although this list was dominated by Pokemon and Mario games, the consoles had more incredible titles in their catalogs and helped make the Game Boy and Game Boy Color iconic. More in Gaming: 1. 5 Best Superhero Games Coming in 2021/2022 2. 10 Best GameCube Games of All Time Ranked by Sales 3. 10 Cutest Pink Pokemon Of All Time For more Nintendo lists and articles, make sure to down below. subscribe to our newsletter

10 Best Game Boy Color Games Ranked by Sales

The nostalgia of is reminiscent of arcades reinventing the idea of entertainment and fun. Even with the innovative AR/VR games now joining the market, arcade games have not lost their popularity. gaming in the '90s Due to the increased demand, Mobile Arcade Games have also been launched to provide the ultimate gaming experience to gaming fanatics. However, few online games still remain on top of the list. But before going into those, let's look back into the . history of gaming The Era of the Arcade Games The retro gaming period was the time that built gaming communities all over the world. The cult favorites grabbed the attention of many, and it all began with a coin-operated pinball machine. The period of Arcade was in the 1970s till the mid-1980s. Video Games – the first arcade game was made in 1971 by a student of the Standford University. The game became to be known as Spacewar. It is was inspired by the previous coin-operated version – Galaxy Game. FUN FACT However, after almost two decades, the grandeur of Arcade Games started to decline. The acceptance of home gaming consoles took over the popularity of arcade games. Then in the 2000s, the rise of networking games via computers and the internet took the gaming industry by storm. Fast Forward to the Current Time Arcade games are still commonly played today. Many old ones, like Tetris, are still among the favorites of gamers, whereas many new additions have also made their place in the world of gaming. Let's take a look at some of the best arcade games of all time, which are not available online and/or on mobile. – Ever played a pinball game that challenged you? is a pong-themed game that uses long vertical tables with a three-dimensional layout. The game has three difficulty levels. The default level is a piece of cake, but the levels after that will surely test your gaming skills. 3D Pong Pinball Game 3D Pong Pinball Game – It takes mundane tasks such as unpacking suitcases or fixing tape recorders and turns them into entertaining puzzle-solving fun. It is the perfect soothing game for people who like to organize things. With the impressive interface capabilities, the developer indeed did an excellent job. Assemble with Care – Its pleasing aesthetics, unexpected remixes of elegant and familiar strategy systems have indeed caught our eye. It's a number-based card game mechanics. Nothing you can't accomplish within a few tries. Card of Darkness – A game that has made quite a name among gamers of all ages. It is exciting, fun, and everything that you have ever imagined. When it launched, it became an instant favorite. The features that people like most are its excellent resolution and graphics. Subway Surfer – The simple puzzle game became a fad in 2009 when it launched. It is also known for its animation and graphics. The incredible thing is that it contains 640 challenges in Mighty Leagues. If you haven't played it yet, then try it! Angry Birds Classic Another famous among the classic arcade games. This endless runner and platformer game provides single-player and multiplayer modes. The central fun part of this game is its stunning 3D environments and unique boss battle programs. If you have the expertise to make it through the challenges, then you have your pick. Sonic Dash – – It is a labyrinth game and would require you to control a ball made of steel by tilting the wooden labyrinth. It is not as easy as it seems. It needs precision to accomplish 120 exciting levels. Customized time set options are among the favorites of this game. Want to enjoy even more? You can play some background music of your choice to up the game. The cannot be ignored. Teeter Pro importance of music in video games – The fun name might already have aroused curiosity in you. Let us give you more to be excited about. Fruit Ninja is both a single and multiplayer game that offers three classic modes. You can optimize the quality and speed. While playing this game, you will surely crave some food. Do keep some with you! Fruit Ninja – It's a spin on the 3D spatial puzzles. A simple yet interactive game that will take you into space. A perfect match for people for love space. ChuChu Rocket! Universe – It is an automatic runner game. It is similar to the common arcade games, occasionally broken by bits where the player falls from the sky. But the music is so fresh, the art is so distinct, and the motion is fluid and free. You can't help but be swept into it. Plus, you can even stab a dragon's eye with a sword. How cool is that? If you love dragons then take a swing at this game. EarthNight – This game does not need an introduction, right? It has always been featured as the best arcade game of all time. It is a video gaming institution. Pac-man is no doubt the most recognizable video game character and is a cult hero too. Even kids wear its t-shirts without having even played it. The game is pretty simple. Eat the dots in the maze, and don't let the brightly colored ghosts get you. The levels get more challenging as you move on. So, try it and see which level you can reach up to. Pac-Man Final Word Arcade games have maintained a legacy of providing fun for gamers while offering the best animation and graphics. Their online versions are just as fun as their coin-operated machine version. The best part is it won’t even cost you a penny to play. So, you have so many options to pick from now and enjoy the legacy of arcade games. We would suggest trying out all the games mentioned above. Because each and every game is a 5 star hit itself. Don't miss out on the arcade fun by just sticking to one game.

The Rebirth of Arcade Games in the 21st Century

Earlier this month, we were joined by Joris Sijs, Lead Scientist at on the second series of . TNO Grakn Orbit TNO is the national research association in the Netherlands, where Joris and his team look to combine robotics and artificial intelligence. They first started working with Grakn about two years ago. Up to that point, there was no suitable database for robotics that could accurately represent the real world. This is essential in autonomous systems that need to perform tasks and make decisions within a real world environment. Too often, robotics projects are run in curated environments and in TNO’s case, they wanted to get as close to real world scenarios as possible. Search and Rescue — Project SNOW The project that TNO is working on is called SNOW, focusing on autonomous systems. The team defines as . autonomous systems the combination of robotics with AI In practice, this means that the robot is given more autonomy, with less human intervention from a user point of view. This then enables the robot to operate in a more complex environment. Project SNOW objective. Slides used with permission Traditionally in robotics, you would have remotely controlled systems. However, with SNOW, TNO is trying to reduce human intervention as much as possible, especially when the complexity of the environment increases. The team working on the SNOW project is comprised of 15 scientists — primarily focused on 3 challenges: — does the robot understand where it is operating Situational Awareness — what can the robot do at this moment given circumstances Self Awareness — based on what the robot knows, how should it complete a task Situational Planning The use case that TNO chose for the project is meant to be semi-realistic. Normally, their customers would ask for only a narrow Artificial Intelligence task to explore. However, by creating their own case, they’re able to test the full set of technical situations and integrate all technical solutions. What is the environment and situation SPOT will be operating within? TNO makes use of an on-premise villa, made up of four rooms, a hall, and a porch. There are four victims and a fireman on site. SPOT is sent in to get accurate information on the whereabouts of the victims, and any additional information on the situation useful for search and rescue. The robot — SPOT from — is then sent into the villa to retrieve or localise the victims. Boston Dynamics SPOT is then tasked with a set of objectives: locate family members medically assess them For example, the robot might report that the daughter is in the hallway going to the kitchen, and that she is responsive. The action, then, would be to continue to search for other victims. Some time later, the robot reports that it found the father in the living room, next to a chair, and was not responsive. In this instance, the is . action to stay put and make noise for the rescue team There are some challenges that SPOT faces when operating in a real world environment: SPOT shouldn’t get confused by a toy dog — it should differentiate a real dog from a toy SPOT should assess when the situation is too dangerous — based on conditions in the room, how search and locate capabilities are diminished SPOT should be able to make a trade off of whom to rescue based on victims’ condition or other variables like location, or proximity to danger, etc. SNOW’s Robotics System How does SPOT observe and collect data — what’s the hardware used in SNOW? PTZ camera — pan tilt zoom camera mounted on top of SPOT Speech array and speaker for speech interaction These components are mounted on top of a mini PC. This mini PC has a lot of computing power, as most of the computations is done on the device itself to ensure as much autonomy for the robot as possible. What Does a Typical Robotics System Look Like at TNO? E.g. TNO robotics system. Slides used with permission First, an image is captured from the , this is then passed to an which is then used to do some so that the robot can localise itself within the room. PTZ camera image recognition module, room characterisation The takes all the detections from the camera and associates them so that they can create better tracks instead of individual detections. association module Grakn is used as the , to orchestrate all the data and knowledge in their system. database Traditionally in robotics, ROS and Python are used to enable communication between the modules in the system. If you take one of your modules or software components and create it in Python, ROS then adds another layer to the Python code for communication with the rest of the system. Because of this, they need to create a dedicated ROS client for Grakn as well, along with using the native Python client. Joris notes that their database, while relatively small, is extremely dynamic in terms of handling administrative burden and adding new knowledge into the database. Grakn ROS Client What is ? What role does ROS play in the process? ROS ROS (robot state publisher) is a publish / subscribe mechanism. A setup consists of: a camera, image recognition, an association layer, a planner and a controller. ROS facilitates the merging of that input date into your database. Let’s look at this example where a dog is identified: An image is published by the PTZ camera The Grakn client subscribes to the image in order to feed it back to the database The image is then passed to the recognition module A dog is detected The dog is then published on the ROS bus The Grakn client again subscribes to this output (dog) in order to send and write it back to the database The same happens with the association module where the speed and position of the dog are written into the database Then the planner might request some piece of information The Grakn client will also subscribe to these requests coming in from the planner (object velocity) and vice-versa How Do You Go About Building the ROS Grakn Client? The team, setting out to build this ROS client, divided it into two parts: the and the . ROS wrapper Grakn client session Building a ROS client. Slides used with permission The handles the publish / subscribe mechanisms, the is built on top of the as an abstract layer. ROS wrapper Grakn client session Grakn client What are the requirements for each? The ROS wrapper initialises the client and the topics to publish or subscribe to. The Grakn Client should automatically start Grakn and delete any existing keyspace - deleting the keyspace is necessary as in robotics we want to start with an empty keyspace. We want to have a fresh scenario for the dynamically changing environmental situations that the robot finds itself in. The Grakn client session should also load the schema and instances that are already known, back in. After a while, when things may have been running for some amount of time, a new ROS messages comes in (e.g. a request for object_velocity). Here, they use Grakn utilities, which is based on the Grakn Python client. Joris and his team are currently looking at one addition that may automate the query generation. This is noted as future work. This slide shows us how a read function looks like under the hood. The function, request_all_humans , fetches us all the humans that are known in the database. They’ve set this up to read the query from the database using Grakn utilities. The data is then retrieved, and put in a nice format that can be given to the ROS wrapper which then publishes it again as a ROS topic. This is a fairly simply function to create. However, it gets a bit more complex when we look at adding additional variables for the robot to observe. Before we get there, let’s look at their schema — Joris walked through a portion of it as a schema diagram in the slide below. Section of schema diagram. Slides used with permission Here we see that they have defined a living_being, which is the parent entity for a human or an animal. These two are then the parent entities for: adult, child ; and dog, cat. SPOT will need to report on the state of the living_beings, both as a physical state and mental state. Specifically, SPOT is tasked with identifying the mental-responsiveness of an identified living_being. Let’s look at how they modelled relations in this snippet of schema. define
## relation : mental responsiveness a discovered (by SPOT) living-being ##
well-being sub relation,
	relates health,
	relates being;
mental-responsiveness sub attribute,
	plays health;
living-being sub entity,
	plays being;
	
## relation : family living-beings ##
family sub relation,
	relates father,
	relates mother,
	relates son,
	relates daughter,
	relates pet; 
human sub living-being;
adult sub human;
child sub human;
man sub adult,
	plays father;
woman sub adult,
	plays mother;
boy sub child,
	plays son;
girl sub child,
	plays daughter;
animal sub living-being,
	plays pet; 1 of 2 of We can also see how an instance of this model looks, referring to the lower section of the slide above. First, they instantiate the mental concept with either true or false. They have some people and a dog, . Notice that in this instance there are two adults, man(with name Sam) and man(with name George). Sam is the fireman, and George is the father of the family. fluffy We can see that Sam is mentally responsive and George is not mentally responsive. How do we create the mental responsiveness in code? Let’s say the mother is mentally responsive: Slides used with permission Here’s where you can see that the code grows quickly, and the reason for wanting to explore automated query generation. Small but Dynamic Remember when we talked about the database being small but dynamic? Here we get to see what happens as SPOT operates in a real world scenario. Setting the scene in the real world, we have a family, a fire-brigade, and a house with a hall and a set of rooms. Here is, more or less, the full schema diagram for the SNOW project. Full schema diagram. Slides used with permission You can see all the relations in green and all the attributes in dark blue. All the concepts, or entities, are in light blue and organised into a type hierarchy. At first glance, it’s not as large or complex as it may appear, but as Joris goes on to describe, once the robot is in a room the complexity grows quickly as the robot needs to orient itself. They are able to model this by representing polygons in the database. Looking at the slide below we see that the kitchen, kitchen door, and four walls are mapped as points and edges of a polygon. A polygon is a mathematical concept that you can use to describe the boarders of a room, like the kitchen. Written as a polygon, you have a set of points and edges or lines. These edges then correspond to either walls or the kitchen door. A polygon is constructed of lines, and a line is defined by two points. If you were to model this polygon into Grakn, the polygon relates to a set of lines, each related to two points and a structural part. Modelling a polygon for spatial awareness in Grakn. Slides used with permission. Modelling this in Grakn we get the entities: mathematical-concept, polygon, lines, points, and two sub-types of the entity point: local-origin and global-origin. These lines can also take some kind of physical form like a structural part: walls or doors. Why is this useful information to know? If SPOT is in the kitchen it should be able to localise itself within that room. If it is in the kitchen and needs to exit the room via the kitchen door, it must know the position of the kitchen door. Using a lidar system, SPOT is able to measure the distances to the walls and thereby map the array to the polygon. Next, it should locate the door by retrieving the end-points of the door. Finally, to head towards the door, it finds a waypoint to exit. In this way, using polygons are handy to have if you are working with robots and real environments according to a floor-plan. Reasoning How to Move From One Room to Another We saw how Joris modeled a specific room in order for SPOT to move within it; but what about moving throughout the building? How should we model a building such that SPOT can move freely between rooms and halls? First, Joris needed to model the composition of a building in the schema — we can see how his diagram might look in Graql: define
building sub entity,
plays composition; 
	
office-building sub building;
res-house sub building;	
space sub entity,
	plays partition;	
open-space sub space;
closed-space sub space;
real-estate sub closed-space,
	plays composition;
room sub real-estate;
	composing sub relation,
	relates composition,
	relates partition;
structural-part sub entity,
	plays partition; sub structural-part;
wall sub structural-part;
door sub structural-part; window This means that when we have an instance of a res-house like the villa in this case, it is composed of rooms: kitchen hall living. These rooms are composed of structural-parts: kitchen-wall, kitchen-door, hall-wall, living-wall, living-door. As Joris explains, we can make use of Grakn’s hyper-graph and rule-based reasoning to create room connections (relations) based on commonly associated structural-parts. If we know that the kitchen-door is a role-player in a relation (in the slide above) with the room kitchen, as well as the room living; then we can infer a relation between the rooms, kitchen, and living via the kitchen-door. This gives SPOT the knowledge that it can move from the kitchen to the hall via the kitchen door. As you might infer yourself, we can then make a relation between the rooms: kitchen and the living, via the kitchen-door and living-door. This is an example of a transitive relation in Grakn. Traditionally, a robotics team might use or other navigation techniques to achieve this mobility through spaces. In Grakn this becomes fairly simple to do. SLAM You can see what this looks like in Grakn Workbase — Grakn’s IDE: Modeling Negation How do we address the fact that SPOT doesn’t yet know where the living-beings are located when the robot enters a building. How do we model this lack of knowledge in our database? In Grakn, we use a locating relation with two sub relations: possibly-locating, not-possibly-locating, and actually-locating. These allow us to address the negative; once a space is searched, capturing in the database that a living_being is not located in that room. We don't need SPOT re-checking rooms and wasting valuable time. This requires a frequent update to the database during the active search. What About Adding New Knowledge to the Database? In real-world scenarios, new facts are presented during an active search and rescue. Imagine a fire commander identifying that one of the bedrooms has a pinball machine, data that may not be currently known in the database. Rather than adding this new knowledge to the database as an instance, you should update the underlying knowledge. You want to add this to the schema so that the knowledge can be reasoned over and used to help SPOT achieve its objectives. Joris notes that this is something that would potentially be happening on a regular basis. Doing this in a suitable and automated way is essential. Grakn’s dynamic schema — able to be updated at any time without needing to do any migrations — makes this quite simple. Summary For me, robotics are extremely cool. Also, knowledge graphs are hot. So combining those, in my sense, gives me the fever. You can see some of my fevers here. Just a few additional “fevers” that move Joris and his team. Concluding his talk, Joris talks about his interest in using Machine Learning over a Knowledge Graph to localise yourself through object recognition. For example, if we recognise two objects: an oven and a sink, we should be able to know that we are in the kitchen. Joris and his team are currently collaborating with James Fletcher, Principal Scientist at Grakn Labs — whose research on knowledge graph convolutional networks (KGCN) is utilised in this project. Special thank you to Joris and his team at TNO for their enthusiasm, inspiration and thorough explanations. You can find the full presentation on the Grakn Labs YouTube channel . here Previously published at https://towardsdatascience.com/object-recognition-and-spacial-awareness-for-a-spot-robotics-system-2ba33152bf65

Object Recognition With SPOT from Boston Robotics

This Slack discussion by Limarc Ambalina, Amy Tom, , Nicolas Ng, richard-kubina and Jack Boreham occurred in official #gaming channel, and has been edited for readability. Tomas Sirio Slogging's What is your favorite video game system of all time and why? Limarc Ambalina Feb 10, 2021, 5:54 PM N64! It’s the most nostalgic for me. Endless hours of smash and Pokemon Snap Amy Tom Feb 10, 2021, 5:56 PM The SNES and GBA Tomas Sirio Feb 11, 2021, 12:30 PM I couldn't afford any of those. But emulation was great back then Tomas Sirio Feb 11, 2021, 12:30 PM Some of my best memories were playing Halo and Gears on the Xbox 360 but the versatility of the Switch really makes it my favourite dedicated video game system Nicolas Ng Feb 11, 2021, 2:03 PM N64 is definitely up there, coming out with a system that had 4 ports out of the box was big.  Having the joystick and shoulder/trigger buttons were a game changer. Playing 4 player Golden Eye with friends provided so many hours of fun, we didn't need much else in terms of titles, Mario Kart 64 block fort battle mode didn't hurt! richard-kubina Feb 11, 2021, 3:33 PM Lots of Nintendo fans in here I see! I grew up with the Game Boy Color and PlayStation 1 and in a lot of ways, RPGs like Final Fantasy 7 and Final Fantasy 8 inspired me to become a writer and led to me being here today. However, at the moment and for the past 5 years or so, my favorite system has been the PlayStation Vita. I don't know why it doesn't get enough love outside of Japan, but it is portable, has a touch screen, and can connect online. Not only that, it also has remote play abilities so you can play PS4 games on it if you want to lie in bed instead of sitting in front of the TV. It is so versatile and home to Danganronpa, one of my favorite games of all time. I'm trying to get a complete collection of every english game released on the device! Limarc Ambalina Feb 11, 2021, 3:53 PM Vita reminds me of the Sony Tablet S.  It had a really advanced (at the time) GPU.  I picked one of those up when it came out and could play some PlayStation games like Crash bandicoot on it, but that game is hard enough without a touch screen... I did like playing Pinball Arcade on it though, nudging the game with the accelerometer was fun, although when you sneezed :sneezing_face:, you immediately tilted the f out 😦 richard-kubina Feb 11, 2021, 5:25 PM https://en.wikipedia.org/wiki/Nvidia_Tegra I loved my vita, as well. It's a portable indie game machine, which I love. It's a shame many third-party developers didn't support it. Jack Boreham Feb 11, 2021, 11:47 PM Personally, my favourite console of all time is the Nintendo DS. Such a versatile machine with tons of games. I remember playing New Super Mario bros with my sister and spending hours playing Pokemon on the system. Such as a great console. It made my childhood and gave me some of my fondest memories. Jack Boreham Feb 11, 2021, 11:51 PM Jack Boreham the DS is incredible too, also can be used as a retro gaming system. The only issue I have is lack of thumbsticks, which is why I prefer the Vita and 3DS. But the Vita just has a better screen. The PHAT vita specifically. Limarc Ambalina Feb 13, 2021, 5:32 PM

Nostalgia for Nerds: What is your favorite game system of all time?

I love this time of year! And no, I’m not talking about holiday parties on Zoom. What I’m really excited about is the opportunity to shape all those big ideas into something that can become reality. Isn’t this why we do the startup thing in the first place? But planning in a startup can feel like an exercise in futility — especially when it comes to data — especially when your data team is small and scrappy. I know the feeling. I’ve spent several years working with data, startups, and data in startups, and I know the struggle. It’s a constant push-and-pull to balance working in service to other teams vs advancing your own agenda and truly putting the data to work. I recently discussed this with a friend and project management wiz, . The conversation, the books , and inspired us to collaborate on this post. Anders Schneiderman Your Strategy Needs a Strategy The Lean Startup Here’s what we came up with: A guide to prevent you from thinking of plans as nice ideas that are quickly thrown out the window, and to start thinking of planning as a way to build balance and strategy into the way data works at your company so you can help your startup thrive and make your corner of the world a little more sane. What does it mean to create a plan for a startup? Before we dive in, there’s a question you need to answer: in your startup, what exactly does it mean to create a plan? If you worked for a big corporation, you could create a plan for an entire year. And assuming that another turning-our-world-upside-down-crisis like the coronavirus doesn’t hit in 2021, you’d have a decent chance of executing it. In a startup? If your plan survives an entire quarter, you get a gold star. . But you’re probably going to spend a good chunk of 2021 being bounced around like a pinball unless you have at least some sense of where you want to go. So how should you construct your plan? A year-long plan doesn’t make sense for most startup data teams : The most useful way to approach creating a plan is to think of it as a roadmap Q1: Here’s what I think is reasonable to expect to get done. Q2: Here’s what’s probably going to be happening and what I have a shot at getting done. Q3 & Q4: Given what I know right now, here’s what would be nice to accomplish. Or to put it another way, here’s a parking lot of tasks I hope I’ll get to work on in the second half of the year. Take stock . Here are some topics you’ll want to explore: Before you start thinking about what you hope to do in 2021, spend some time analyzing what you can learn from 2020 What’s currently working well? What needs improvement? From the successes you had this year, what lessons can you learn? What mistakes did you make this year that you’d like to avoid making in the future? And are there any weaknesses you discovered as a result of these mistakes that you’d like to try to improve? Are there any areas where you (or the rest of the data team) were a blocker to other coworkers or projects? If so, what can you do next year to reduce or eliminate these problems? Are there areas where you accumulated the data analyst’s equivalent of technical debt? For example, are there a bunch of SQL scripts you had to frantically bang out when you unexpectedly pivoted that are important enough to day-to-day operations that you need to go back and clean up and document in 2021? Are there any areas where a more self-service approach would have really helped the teams you support? You can use these prompts to play the game, . Start, Stop, Continue Whatever you do, . In the chaos that is startup life, nobody’s perfect. The point of looking back isn’t to point out all your flaws, it’s to help you improve. don’t use taking stock as an excuse to beat up on yourself Celebrating your wins isn’t just good for your ego, it helps get you charged up for next year. Similarly, don’t use what you didn’t accomplish as an excuse to ignore or downplay your successes. Evaluate your resources Once you’ve identified areas you want to address in 2021, and what you might be able to get if you make a strong enough business case. Need a guide? Here’s one on . The same thought process applies to arguing for all sorts of resources. figure out what resources you’re pretty confident you’ll have next year how to propose a data stack Your primary resources are money and headcount you directly control. But . you should also consider whether there are resources you’ll either need or could elicit from — or share with — other teams For example, if you rolled out a new BI tool in 2020, will some of the teams who aren’t using it have time to get trained up in 2021? And would teams that are heavy users of the tool have the time and interest to work with you to deepen their skill in using it? It’s also worth asking whether there are any projects where you think you can enlist members of your to either help out or take the lead. What you think of as just another day at the office, they may view as a coveted professional development opportunity. network of allies Finally, now’s a good time to find out what teams are planning for next year that will require dedicated resources from you. Knowing that in advance will ensure that your expectations are aligned…or at least that you’re not blindsided by someone else calling dibs on your time. Define your projects and set your goals and metrics For this phase of your planning, what you need to do depends on how your startup handles developing goals, metrics, and project plans. Regardless of which planning method your startup uses, here are a few tips on how to get the most out of this stage in the planning process: 1. For hard-to-measure work, shoot for good-enough metrics For some of the most important work you do, you might find it difficult to accurately measure your impact. That’s okay, just use a good-enough proxy. Say you’re going to use training and mentoring to deepen your team’s ability to use your BI tool. Ask yourself, if they’re getting more skilled at using the tool, how would I expect the quantity and types of support (or Jira) tickets I handle to change? For example, would I expect the total number of tickets to drop, or would I expect I’ll get fewer tickets for simple list requests and more tickets for more complex analysis? Once you’ve nailed down what you expect to happen, create metrics, and . If you need to, add new categories or tags to your helpdesk software or Jira account so you produce the data you need for the metrics — e.g., a category/tag for simple versus complex requests — far enough in advance of the new project to establish a baseline. get them into dashboards 2. Don’t neglect your own needs Facing a never-ending stream of requests, many analysts guilt themselves into sacrificing work that benefits them. It’s understandable, but it’s a mistake. Taking the time to invest in your skills, explore new tech, and build views and other infrastructure that reduce the effort it takes to fulfill requests doesn’t just benefit you, it also benefits your company. So be sure your plan carves out time for projects that make your life better move the business forward. and 3. Don’t rack up too much data infrastructure debt Make sure your plan includes time to clean up SQL, write or rewrite documentation, add new views that better fit where teams’ needs are headed, and so on. How you do this will depend on your startup’s culture and the challenges you currently face. For example, rather than setting aside January to knock out that work, you might be better off adding helpdesk tickets throughout the year. Or you might want to add time to some high-priority projects to pay down a little infrastructure debt in the project’s early stages. This is also a great place to get help from your allies: you can ask them to put in requests that pay down the debt that impacts their work. 4. Just because you have to write a year-long plan doesn’t mean you have to believe in it If your startup requires you to create a plan that suggests you know what you’re doing for an entire year but you’re still in the “next quarter is uncharted territory” stage, don’t sweat it. Managing a startup is a nerve-racking endeavor, and if the people at the top need to pretend they’ll have more control than is likely, that’s okay. There’s nothing wrong with having a business blankie so long as everyone knows that’s what it is. Write up the plan Now that you have a rough idea of what you want to put into the plan, what’s the best way to write it up? . Your main goals with your writeup are: 1) to make your boss and whoever else needs to sign off on the plan think it’s clear and easy to skim, and 2) to be able to refer back to the plan in a few months and easily see if you’re on track. There’s no one right way to write up a plan You may want to make a strategic decision about where and how to document your plan. For example, while plans typically are written as Google or Word docs, if everything in your startup ends up in Jira, you might want to check with your boss to see if it makes sense to skip writing a document. Instead, you could create one or more projects in Jira, then create a backlog for each and schedule changes from there. (Note: If you go down this road, you might want to explore using milestones and components as a way of structuring it). The other thing you’ll certainly want to do is . Obviously, you’ll want your boss to weigh in, but you should also get input from key higher-ups, users, and allies. Getting that input early will help you come up with a finished product that satisfies all your stakeholders. get feedback on an early draft Conclusion It’s easy to drive yourself a little nuts when creating a plan for next year — especially in the fast-moving world of startups. But there’s no reason it has to be that way. . So long as you use the simple, structured approach we’ve discussed here, you should be able to come up with a 2021 plan that will make next year more predictable (and enjoyable!) for yourself and help your startup succeed

Planning for Your Startup: The Data Team's Guide to 2021 

In recent weeks and days, the crypto markets have been exploding again and Bitcoin is back above the level it was at the end of 2017 with an all-time high based on the market cap. But we all know what came shortly after 2017... the big crash from which Bitcoin had not really recovered for several years. So it's a fair question: Are we in a 2017 bubble again or is Bitcoin breaking out for good this time? In this article we'll try to get to the bottom of this question as rationally and objectively as possible. What happened in 2017 In early 2017, the Bitcoin price was still fluctuating around the $1000 mark. In the following 10 months until October, there was a constant up and down of the Bitcoin price, which was now pretty solid between $4000-$5000. Bitcoin was gaining more and more attention on social media, then even the mainstream media started reporting about Bitcoin. And suddenly the domino knocked over: This is a trends graph of how many people searched the term "bitcoin" on Google: Within just a few weeks suddenly everyone knew about Bitcoin and the price exploded to $20,000. ... Only to crash again at the beginning of 2018 (without recovery until now), after Bitcoin saw a 20-fold increase the year prior. What was the driver of all this? In short: incredible FOMO (Fear Of Missing Out). Left and right, everyone wanted to get rich quickly and invested in Bitcoin without much thought because they were afraid of missing something and being left behind as losers. So is the same thing happening again now in 2020? The market situation today is very different from what happened 3 years ago at the end of 2017. Sure: We are again at the all-time high and there are few to no addresses that are in the minus. But retail (private investors) have not yet realized anything... In the summer of 2020, the general interest in Bitcoin was even higher than is currently the case. And it does not even come close to the values of the end of 2017. The money which is currently flowing in is coming mainly from institutional investors with a lot of capital, who have recognized Bitcoin as an asset now to include in their portfolio. Generally, Bitcoin is gaining more and more acceptance - even and especially from the big boys. PayPal, for example, has only recently integrated Bitcoin into its system and now allows buying, selling and trading with Bitcoin in the USA - with the plan to roll out this feature worldwide soon. Something personal, which is still completely different this year than last: I and also other public figures within the cryptospace are hardly receiving any inquiries from reporters and news outlets to say something about the current market events... which is actually a quite positive thing from an investment perspective. The market currently resembles more the beginning of 2017 rather than the end... So does it make sense to invest in Bitcoin now? In my opinion, there are two wrong amounts to invest in Bitcoin: 0% of investable capital and 100% of investable capital. So to get into FOMO now and panically throw all your money into Bitcoin is certainly not a good idea. Having invested nothing at all in Bitcoin makes just as little sense, though. More and more professional investors have now recognized this - as already mentioned, this is actually the main driver of the current price increase. So if you don't have enough Bitcoin yet, you can easily buy Bitcoin by bank transfer or credit card via Cake DeFi. The best thing about Cake: after your purchase it's even possible to get up to 11.5% guaranteed cashflow on your Bitcoin!

Bitcoin Bubble 2020 - When's It Gonna Burst?

Japan is home to many things, but perhaps its most unique element is its unparalleled otaku (nerd) culture. With one of the largest video game markets and industries in the world, Japan is home to hundreds of video game developers and publishers, each trying to one-up the other and make a game unlike anything else that has come before it. This cold war within the Japanese video game industry has led to some of the wackiest, craziest and weirdest games ever to be played. Just when you thought you’ve seen it all, Japan comes out with something no one in their wildest dreams would ever think of. From eliminating vampires by stripping off their clothes to playing pinball with falling boogers, the games on this list are guaranteed to have you scratching your head in confusion and facepalming out of astonishment. All of these games are available outside of Japan (if that’s where you’re reading this) and are playable in English. : this post contains affiliate links to product pages Disclaimer 1. Mister Mosquito Box cover for Mister Mosquito. Our first game is an insect simulator developed by Zoom Inc. that was originally released in 2001 on the PlayStation 2 in Japan and then localized in English by Eidos Interactive’s Fresh Games. While it had great sales and reception in Japan, it didn’t get much hype in North America or Europe. However, it has since gained a cult following and is regarded as one of the weirdest and craziest games ever made. In Mister Mosquito (known as Mr Moskeeto in PAL regions and in its home market as Ka, the Japanese word for the bug) you play the part of a pest that everyone knows and hates with a fury: the common house mosquito. … regarded as one of the weirdest and craziest games ever made. Gameplay consists of terrorizing the Yamada family in the comfort of their own home by sucking their blood while trying not to get smacked in the process. In order to find the perfect opening, players can also distract members of the Yamada family by turning off the lights, switching on electronics or simply waiting until the target falls asleep. Due to its low sales and cult following, Mister Mosquito has become something of a collectible item in the West, with used copies selling on eBay for upwards of US$70. If you ever see the game at an affordable price, be sure to pick it up — Mister Mosquito is a must-play for retro game lovers. Good for: PlayStation 2 lovers and those who like simulator games. Available on: and Amazon eBay 2. Chibi-Robo One of the weirdest Japanese games that received positive reception outside the country is Chibi-Robo. Originally released on the Nintendo GameCube, Chibi-Robo is about one tiny robot’s mission to bring happiness to the Sanderson family while fighting off evil robots programmed by a toy company. In Chibi-Robo, players must collect happy points by bringing happiness to the Sanderson family. How does a tiny robot make a family of three happy? By doing mundane chores around the house, of course. The gameplay of Chibi-Robo revolves around picking up trash, scrubbing the floors and tending the garden among other tedious household tasks. How does a tiny robot make a family of three happy? By doing mundane chores around the house, of course. Despite this wacky premise, the game received an 8.2 out of 10 rating on IGN and 8 out of 10 rating on Eurogamer. Numerous sequels have been made and released on the Nintendo DS and 3DS, but the original Chibi-Robo remains the highest rated game in the series. Good for: People who enjoy silly and original gameplay and lovers of Nintendo. Available on: and Amazon eBay 3. Food Fantasy Food Fantasy. With personified foods, restaurant management and evil creatures roaming the world, Food Fantasy is one of the most unique mobile games on the market. It was developed by Elex Wireless and just published in the spring of 2018. Food Fantasy is an eclectic mix of game styles comprising Japanese role playing games (JRPG), a business and a cooking simulator all mixed into a bizarre, yet incredibly fun, package. In this mobile game, you are part cook, part restaurant manager and part adventurer. While running your restaurant you must also manage staff, create new recipes and fight evil creatures. Battles are fought using summoned food souls, personified food spirits that both fight your battles and staff your restaurant. Food Fantasy is a mobile game that can be played on the go for a few minutes or even hours at a time. Good for: People interested in JRPGs and cooking simulators. Available on: or Android iOS 4. Akiba’s Trip: Undead and Undressed Akiba’s Trip: Undead and Undressed. A play on the words “Akiba” and “strip,” Akiba’s Trip is an action-adventure game set in the Akihabara Strip of Tokyo. Furthermore, the gameplay consists of attacking enemies by stripping off their clothes. Developed by Acquire Corp. — a veteran action game developer that brought us the Tenchu and Way of the Samurai series — Akiba’s Trip: Undead and Undressed employs smooth and enjoyable real-time battle mechanics. While the game’s premise may just sound like an unseemly excuse to get a look at animated undergarments, the plague of monsters infesting the Akiba Strip leaves the main character, Nanashi, with no other choice. … the gameplay consists of attacking enemies by stripping off their clothes. In Akiba’s Trip: Undead and Undressed, players fight against synthetic humanoid vampire-like creatures known as Synthisters, who — instead of feeding on blood — suck away people’s sociability and take away their will to live. The only way to defeat these creatures is to weaken them with physical attacks and strip off their clothes, exposing them to their biggest weakness: sunlight. Good for: People who like action or beat-em-up games and people who want to see an incredibly accurate recreation of Akihabara’s Electric Town Available on: , and . Amazon Steam PlayStation Store 5. Wario Ware Gold Wario Ware Gold. Easily one of the weirdest games ever released by Nintendo, the Wario Ware series was made for people with short attention spans or very, very little time on their hands. Wario Ware Gold is the newest release of the series and is available on the Nintendo 3DS. Like every other title in the series, Wario Ware Gold consists of a series of minigames, each lasting around three to five seconds with boss levels lasting around 10 to 20 seconds. Usually, games start with just a single word as explanation such as: “stop,” “catch,” “stomp” or no explanation at all. From picking your nose to barbecuing ham, there’s no predicting what game will come next. Because Wario Ware Gold is the latest release of the series, it encompasses all the minigames from the releases that came before it and includes a total of over 300 minigames. Not only are these games fast, but they are also nonsensical and wildly crazy. From picking your nose to barbecuing ham, there’s no predicting what game will come next. While the premise sounds a little bit unorthodox, Wario Ware games are the perfect games to play on-the-go, during your commute or when you’re in the waiting room. Because there is no continuity between each minigame, you can literally pick up and play Wario Ware anywhere for seconds, minutes or hours at a time. Good for: Those with little time to play, people who like fidget spinners and gamers with little to no attention spans. Available on: Numerous titles are available on and the Amazon Nintendo eShop Japan is home to many over-the-top games — some that may not be entirely appropriate for viewing at work or in public, which may be why one of your favorite games may not have made this list. While all of these games are worth a try, I think that Wario Ware is a game like no other and should definitely be next on your list of games to play — especially if you’re a Nintendo 3DS owner. Also published on: https://blog.gaijinpot.com/5-of-the-weirdest-japanese-video-games-you-can-play-in-english/

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