Posts in Category: Engineering

Getting More Familiar with Docker

I’ve been spending this week getting more familiar with Docker. I’ve learned how to build new images, spin up a collection of related containers with Docker Compose, and push an image to AWS.

I’m pretty excited about how this will help my team, but I’m also nervous about the unknowns we’ll encounter. My goal is to free up time, not take up more.

It’s important to know what Docker is and isn’t. To be honest, I’m still a little fuzzy. I wrote about this in my last post.

Docker utilizes virtualization technology to run processes in isolated environments called Containers. It has some similarities to virtual machine technology, such as VMWare and VirtualBox.

Docker Containers do not hold an OS, but they do have libraries and binaries from other OSes.

After working with Docker a little, I’m now much familiar with commands to setup a container and access the container (docker exec -it is my friend). I’ve also gotten more familiar with docker-compose (docker-compose up/down are pretty cool).

The documentation for Drupal on Docker provides info on both setting up Drupal and MySQl.

I’ve been able to spin up a Redis and MySQL server with Docker, it has simplified the setup and given my team a consistent toolset.

What is this Docker Nonsense?

This last week I’ve been working on getting Drupal running through NGINX so I can test out a page builder feature. I was getting a weird error with the dev-server built into PHP.

I didn’t want to have NGINX running on Windows, so I spun up a VM. Setting up an environment can be time consuming and sharing content between host and client is a bit of a pain.

The last two weeks has had a theme: environment/tools setup. So my mind has been on “how do we improve this process?”

Documenting the process helped a little, but it is still a time consuming process. It also seems like there’s always some new gotchas that eat up time. If only there was a way to automate this…

Here is where Docker enters the picture and where it’s suppose to shine. We can create a group of containers that run a web server, database, and other needed services. This setup can be shared across workstations so we maintain a consistent work environment. We can also use Docker in production too with Amazon’s ECS (Elastic Container Service).

It sounds like a smart move and everyone is on board.

Great, now let’s tear down this idea and look at use cases and scenarios, starting with security.

But in order to feel out security we need to know what Docker is. That can be a little confusing. To be honest, I’m still a bit fuzzy.

My understanding is a Docker container is a very thin layer that can have libs and executables. When you run the container the processes run in their own isolated namespaces.

This diagram is the most helpful of everything I’ve come across.

A* Pathfinding In Game

I wrote a post on implementing a simple A* Pathfinding algorithm a couple months ago. When I went to add it to my game I ran into some interesting differences I wanted to write an update on.

Here is the algorithm working on my game server. Both player and NPC are red blocks. When the player is within viewable range of the NPC, the NPC will start chasing it.

The pathfinding algorithm allows the NPC to maneuver around blocked tiles.

Coordinate to Tile Mapping

One thing I discovered while incorporating it into my game was my simple example had a 1:1 coordinates to tile ratio. Coordinates 0,0 was the first tile, and 0,1 was the second tile. When tiles were 16×16 pixels, the coordinate to index mapping broke.

To address this, I needed to pass  map width and map height in tiles, as well as the tile size so it was known when a new row started and the bounds of the map.

I did this by creating a map struct that contained the width, height, size, and pointer to the tile vector.

struct GameMap {
	GameMap() {}
	GameMap(int _map_width, int _map_height, int _tile_size, std::vector<unsigned int>* _tiles) : map_width(_map_width), map_height(_map_height), tile_size(_tile_size), tiles(_tiles) {}
	int map_width = 0;
	int map_height = 0;
	int tile_size = 0;
	std::vector<unsigned int>* tiles;
};

A Simple A* Pathfinding Algorithm

Pathfinding is a fundamental tool commonly used to move characters around a map intelligently. Here I will be going over the A* algorithm written in C++.

It’s important to visualize how the pathfinding algorithms search for the most efficient path. Here is a neat demo using a JavaScript library called Pathfinding.js. By playing with Pathfinder.js, you should notice that the algorithm first tries to go straight for the end point and only when it hits a blocked node will it look for nodes that follow a less direct path.

The Algorithm

In a nutshell, the A* algorithm uses a graph of nodes that have a weight associated to them used to weigh paths from the start node to the end node.

What weight represents is arbitrary, since A* can be applied to different scenarios. For navigating through a map of squares for example, this value could be based on distance and steps taken. The algorithm processes neighboring nodes, adding all neighbors to an “open list” and then moving on to the lowest cost node in that list.

Given the open list begins with the start node (opposed to be empty), the main loop of the algorithm looks like this:

  1. Get next node from open list (now known as current node)
  2. Skip node if in closed list or out of bounds
  3. Add current node to closed list
  4. Remove current node from open list
  5. Process neighboring nodes (North, West, South, East)
    1. Set current node as parent of neighbor if weight is less

In all, the algorithm uses three lists:

  • Open List:  Keeps track of which nodes to search next and is ordered by weight
  • Closed List: Al nodes that have already been searched
  • Path: Linked list that connects the end node to the start node

To clarify on the path, there are actually multiple paths that exist because less efficient paths may be found before the most efficient path. The end node will have the final path, and that is all we care about.

Implementation

Next we’ll go over the structures and functions involved with this algorithm. One core structure is the node.

Node Structure

As mentioned before, this is implemented in C++ and the graph is comprised of nodes.

Here is the Node structure with only its members:

struct Node {
    int x;
    int y;
    int index = 0;
    int distance;
    bool blocked = 0;
    int weight = 0;
    Node *parent = NULL;
};

I use indices to keep track of nodes. This includes determining which node is the start and end, as well as which nodes have already been processed (closed list) and which nodes should be processed next (open list).

Note: The index  struct member is there for convenience, so a coordinate to index lookup doesn’t need to be run every time.

The path list mentioned before is a linked list created through the parent  struct member, which points to another node.

Grid and List Structures

Nodes are stored as pointers in a vector. The open list is implemented as a multiset with the comparison function, NodeComp, so sorting is automatically done. Lastly, the closed list is implemented as a vector of ints that stores the indexes.

typedef std::multiset<Node*, NodeComp> NodeList; // So we don't need to type out the full definition everywhere

NodeList open_list; // Node pointers to process
std::vector<int> closed_list; // Node indices already processed
std::vector<Node*> grid; // All nodes

Out of Phase: Race Conditions and Shared Mutexes

This is part of a series for the Out of Phase game project that reflects on various stages, covering pros and cons of the creative process and implementation of the game.

Last year I started porting over the backend of my game from Python to C++. The reason for this move ties into my long-term goals as a game developer. Programming a multiplayer server has been something that has intrigued me for a while. The idea of creating a virtual environment that is continuously running and allows multiple players to interact with that environment in real time is fascinating to me.

At this time, my game will only support two players, but I would like to play around with adding more.  I’m doubtful this will be a massively multiplayer game, like World of Warcraft or Elder Scrolls Online, since that would be a huge amount of effort. So maybe up to four players.

Real-time games that support multiple players typically require some special handling of synchronizing the game state as it is updated from the player’s clients. Without synchronizing, race conditions will occur which will result in erroneous and unpredictable ways.

So in this post, I’ll be covering how to avoid race conditions in C++ threads by using locks and mutexes.

Race Conditions

Let’s take a code snippet as an example (this is make believe pseudo code):

void attackGoblin(Monster* goblin) {
    int health = goblin->getHealth();
    health -= 10;
    goblin->setHealth(health);
}

Race Condition 1

Ok. So the problem here is what happens when two players are attacking this goblin at the same time. Just because this code is wrapped in a function, doesn’t mean each block of code gets executed sequentially. It’s possible that the lines of code being run between each player may be executed in a mixed order.

Let’s assume that goblin->getHealth  and goblin->setHealth  read and write the current health value from or to memory. (But they don’t use synchronization)

Two players are attacking a goblin with 500 health. Both players inflict 30 damage at the same time. We expect the goblin’s health to drop down to 440, but instead, it only drops down to 470. What happened?

(thread 1) int health = goblin->getHealth(); // getHealth returns 500
(thread 1) health -= 30; // local to thread 1
(thread 2) int health = goblin->getHealth(); // getHealth() returns 500
(thread 2) health -= 30; // local to thread 2
(thread 2) goblin->setHealth(health); // Goblin health is now 470
(thread 1) goblin->setHealth(health); // Goblin health is still 470

Where did the damage go? Well, it got overwritten because the instructions weren’t synchronized. Each thread keeps a separate copy of health and when the goblin’s health is changed in one of the threads, it never updates in the other.

Using SQLite in a Threaded Java App

A few months ago I decided to port my WoW data importer app from PHP to Java because the website was already built in Java. I also wanted to see if execution time could be improved in a multi-threaded app.

The PHP script stores the JSON returned from the WoW API into individual JSON files for each item. This means there are thousands of JSON cache files. There’s a second script that packs these responses into a single file, and then a third script that imports the data from the consolidated file in the second script.

The reason for this two-step process was to see the difference in time it took my script to process the individual files vs a consolidated file, as describe in my blog post on optimizing the PHP importer script.

This approach was overcomplicated and pretty inefficient. While writing the Java app, I wanted to create a cache source that didn’t require another script to pack the data, but was could be updated efficiently.

Choosing SQLite

At first, I tried Oracle BerkleyDB. Coding that up was pretty simple, and I got it working. However, I couldn’t find a good program to manage the BerkleyDB. The apps I came across either wasn’t specifically for BerkleyDBs or they required compiling, and I didn’t want to bother with that.

Since I’ve used SQLite in quite a few projects, it seemed like the next choice. While the mySQL database I’m putting the data into would have worked fine, that database could be remote, and I needed a local database to cache the API results into.

Threading Gotchas

A big challenge with SQLite is that you’re working directly with a file, and not a service like you do with mySQL. Because of this, special precautions need to be taken so that you don’t run into SQLITE_BUSY exceptions or accidentally corrupt your database by writing in two threads at once. This happened at least once while I was playing around with different configurations.

Tip #1: Share the SQLite connection between threads

Creating a shared connection should at least avoid corrupting the database. However, it’s still possible to come across the SQLITE_BUSY exception

Tip #2: Use a Lock

Sharing the connection worked very well at first. I was able to import data into a clean database without any problem. However, when the app was run again and started updated cache, I started running into SQLITE_BUSY exceptions.

Data Importer Optimizations

Nobody wants a slow application. Efficiently optimizing your application takes experience and constraint. You don’t want to prematurely optimize, but you also don’t want to code something subpar that will contribute to your technical debt and put your app in the grave early.

There is a balance that needs to be struck. Knowing when and how to optimize needs to become second nature so that it doesn’t interfere with the development workflow. Producing something so that it can be demonstrated often is more important than optimizing in many cases.

This post will cover a few optimization techniques associated to reading from files and running SQL queries. These tests are written in PHP, an interpreted language, though the techniques can be applied to other languages as well.

The Script

The program is basically a data importer. It takes item data from the World of Warcraft API and updates a mySQL database. Before this script runs, the Warcraft JSON data is saved in a single file delimited by a newline character. This single file, which acts as a cache, allows me to focus on optimizing the local operations without network overhead.

XDebug Setup

XDebug for PHP has a useful profiling feature. When profiling is enabled, XDebug will store the profiling data in the directory specified, and the file can be read with KCacheGrind (Linux) or WinCachGrind (Windows).

[xdebug]
xdebug.profiler_enable=1
xdebug.profiler_output_dir=\Users\Justin\Misc Code\Profiling\php7

Optimizations and Tests

The complete dataset consists of 99,353 records. There are empty records which take up a newline, so the text file contains 127,000 lines.

Base Test

(Link)

I started off with a PHP script that was purposely designed to be slow. Each item was stored in its own cache file.

For each item:

  • Open the item specific data file
  • Check if there is JSON data (move onto next line of JSON if none)
  • Parse JSON
  • Query database for existing record
  • Execute insert if no existing record
  • Execute update if record exists

This took 2 hours and 37 mins. This is absolutely horrible. The good news is there are quite a few things that can be optimized here.

Here is one thing to keep in mind in regards to speed, the closer your data is stored to the processor, the faster it can be processed.

CPU Cache < Memory < Hard Drive < Local Daemon < Network/Internet.

RPG Slots Progress – Cocos2d Review

rpgslots

I started developing a slots game using the Cocos2d C++ SDK. Cocos2d is an opensource game development framework that support C++, Objective-C, and JavaScript. Eventually, this game will evolve into a slots RPG, like King Cashing and King Cashing 2. For now it uses a pretty generic reels and a match 3 mechanic that matches on the same row as well as cells on adjacent rows. For score, it keeps experience points, since this will transition to the RPG slots.

Source for the project can be found here. As of this writing, it’s in early development.

Like many game frameworks, Cocos2d has many helper functions that allow for quick game prototyping. Scenes are easy to construct, and assets, sprites, and audio can be added using built in Cocos2d objects. It even supports the ability to add custom shaders.

Extending Sprites

I found quickly that I needed to create custom objects that extended sprites. In this project there two classes that extend cocos2d::sprite ; the reel, and the HUD.

Grouping elements within sprites helped with organizing code and separation of concern. I did run into strange memory errors when trying to add certain objects, such as cocos2d::Label , directly to the scene while also having a pointer to it in the scene.

Autorelease

The Cocos2d C++ framework uses a smart-pointer technique to automatically destroy dynamically allocated objects when its internal reference count is 0. This relieves pressure in remembering to destroy objects and worrying about pointer ownership. Though cyclical dependencies still need to be avoided.

The built-in Cocos2d objects are automatically added to the autorelease pool, so there is no need to use the new  keyword. In my project, I have an object that extends the Cocos2d sprite. So there’s some boilerplate code that I needed to add so my object would be added to the autorelease pool.

ReelSprite* ReelSprite::create(const std::string& filename, std::vector<int> _cells)
{
    ReelSprite* mainSprite = new ReelSprite();

    mainSprite->init(filename);
    mainSprite->autorelease(); // <-- ADD TO AUTORELEASE POOL
    mainSprite->cells = _cells;

    return mainSprite;
}

ReelSprite::create  is a static method that follows the Cocos2d convention of constructing an object and adding it to the autorelease pool. mainSprite->autorelease()  is the line that actually adds the object to the autorelease pool, so that it does not have to be manually destroyed.

Screen View to World Coordinates

I needed a map editor with more features than what I saw included in TILED back in August, so I decided to try my own hand at creating a map editor. It’s just an interactive grid, right? Not quite. At least in the approach I took.

I started writing the tile editor with C++ and SDL. Implementing drag functionality was pretty easy since that was baked in the SDL API, however, I didn’t want to build the UI widgets from scratch. Unfortunately, the existing UIs I found weren’t compatible with SDL, so I had to pivot and use straight OpenGL and matrix math.

Because I was ditching the SDL framework, I had to implement my own drag logic, which is what I will discuss in this post.

Moving Objects with Mouse Picking

I needed the ability to select objects in 3D space, which lead me to a technique called mouse picking. This technique utilizes ray casting, which is how you detect if a line (a ray) intersects with something else.

The article “Mouse Picking with Ray Casting” by Anton Gerdelan helped explain the different planes/spaces and what they represented.

In order to move the objects in 3D space at a distance that matched the mouse movement, I had to transform the coordinates between screen and world spaces. When working with 3D coordinates, there are several spaces or planes that have their own coordinates.

A very simplified list of these spaces are:
Screen Space > Projection (Eye) Space > World Space > Model Space.

newtranspipe

Anton Gerdelan’s Mouse Picking with Ray Casting

Fully understanding the transformation formula was a challenge for me. Normalization and calculating the inverse Projection Matrix tripped me up due to a combination of confusion and erroneous input.

The Solution

Here are some code examples of the final working solution.

Initialization of Projection, View, Model

Projection = glm::perspective(1.0f, 4.0f / 3.0f, 1.0f, 1024.1f);
GlobalProjection = Projection;

CameraDistance = 10.0f;
GlobalCameraDistance = CameraDistance;

View = glm::lookAt(
glm::vec3(0, 0, CameraDistance), // Camera location
glm::vec3(0, 0, 0), // Where camera is looking
glm::vec3(0, 1, 0) // Camera head is facing up
);
GlobalView = View;

Model = glm::mat4(1.0f);
GlobalModel = Model;

MVP = Projection * View * Model; // Matrix multiplication

View to World Coordinate Transformation
// SCREEN SPACE: mouse_x and mouse_y are screen space
glm::vec3 Application::viewToWorldCoordTransform(int mouse_x, int mouse_y) {
    // NORMALISED DEVICE SPACE
    double x = 2.0 * mouse_x / WINDOW_WIDTH - 1;
    double y = 2.0 * mouse_y / WINDOW_HEIGHT - 1;

    // HOMOGENEOUS SPACE
    glm::vec4 screenPos = glm::vec4(x, -y, -1.0f, 1.0f);

    // Projection/Eye Space
    glm::mat4 ProjectView = GlobalProjection * GlobalView;
    glm::mat4 viewProjectionInverse = inverse(ProjectView);

    glm::vec4 worldPos = viewProjectionInverse * screenPos;
    return glm::vec3(worldPos);
}

At first this algorithm felt a bit magical to me. There were things going on I wasn’t entirely wrapping my head around, and when I stepped through the algorithm I got lost at the inverse matrix multiplication. In addition, the “Mouse Picking” article normalizes the world space values, which we don’t need.

An Introduction to React

I’ve been working with React a bit lately and wanted to document my experience and findings. Since there’s quite a few “hello world”/getting started guides out there already, I’ll provide links to those and cover key points I took away from articles and experience.

When React was announced around mid-2013, it looked like an interesting concept and seemed like it should be pretty significant considering it was being maintained by Facebook. However, it fell off my radar soon after. as It was too early to use in any of my projects. Looking at where React stands now in addition to supporting libraries, I can see  that the scene has matured and stabilized quite a bit.

What is React?

React is a JavaScript library created by Facebook that fulfills the functionality of the view in MV*C. It stands by itself and aligns with the “single responsibility” principle that is the first of the five S.O.L.I.D object-oriented programming and design principles. Other concerns such as routing, controller, and model/stores are separate patterns that exist outside of React.

Because of this separation, React can fit into other frameworks or be pieced together with other libraries to make a complete MV*C framework, such as Flux (see which Flux implementation should I use on history/development of Flux), Redux, or Cerebral.

React is designed to be scalable and fast. Some patterns like its root level event listener are intended to make React fast, and other features, such as the virtual DOM, use encapsulation to reduce or eliminate common problems with scaled web applications caused by conflicting class/ID names and DOM manipulation side effects.

Also worth noting, React was split into react-dom and  react-native to independently support browser and mobile apps. For this article, I’ll be covering what is referred to as react-dom, which is React for the browser.

Learning Curve

Working with React and its ecosystem has been interesting. Given you’re already familiar with JavaScript, React itself isn’t that difficult to comprehend. Though it does take some time to understand the concepts React is founded on and what problems it is addressing. For example, the data flow design may take some time to get used to.

The challenges with React more lie in the ecosystem, when third-party libraries and the build process come into play. However, the libraries are worth getting familiar with, and the build process should become less confusing as things settle down. For now, there are plenty of boilerplate start projects on github.

Getting Started

The first step is to take it easy and not get overwhelmed. There are a collection of technologies that make a React stack, and they don’t have to be learned at once, I recommend first focusing on React and JSX first. By understanding the core concepts and working with plain React is a good start.

React’s homepage goes over the fundamentals of building a React app from scratch without diving too far into the tool chain. A starter kit can be downloaded from their getting started guide.

Most examples require compiling the HTML like markup called JSX into JavaScript. This can be done through a browser version of the Babel library called Babel Standalone. However I’ve found this makes debugging difficult, because I can’t set accurate breakpoints. Compiling the application outside of the browser as part of the build process is recommended.

The following is a simple “Hello World” component defined with a pure function. For components that don’t hold state (covered further down), pure functions are preferred over react factories, such as React.createClass or React.createComponent.

See the Pen React Hello World by Justin Osterholt (@hattraz) on CodePen.0