To summarise my main points from the talk (perhaps something I should have done in the talk!)

• Cassandra is a “highly scalable second-generation distributed database”
• It can be considered a schema-less database insofar that each row can have different columns
• Cassandra is designed to be both fault tolerant and horizontally scalable – both read and write throughput go up linearly as more boxes are added to the cluster
• I think the best way of accessing Cassandra from PHP is directly via the Thrift API. This allows a beginner to learn about the core functionality of Cassandra including its limitations
• Cassandra has Hadoop support which means that Hadoop Map Reduce jobs (a scalable, distributed mechanism for processing data) can read and write to Cassandra*
• Cassandra does not have any query language (as opposed to MySQL or MongoDB which both allow you to query data in different ways)
• When designing your data model, I think its easiest to try to forget about SQL and concentrate on how Cassandra works (don’t design a relational schema and then “port” it over)

* As of version 0.7!

Overall, I think Cassandra is a very useful tool. Whether it fits your use case or not is another matter!

If you’re interested in learning more about using Cassandra in a PHP project, I recommend the following starting points:

1. Using Cassandra with PHP
   https://wiki.fourkitchens.com/display/PF/Using+Cassandra+with+PHP
2. WTF is a SuperColumn? An Intro to the Cassandra Data Model
   http://arin.me/blog/wtf-is-a-supercolumn-cassandra-data-model

This post covers:

• A sample OOP system that we will discuss
• The basics of Dependency Injection
• Putting objects to sleep
• Waking objects up

Sample system

To illustrate the idea, I’ll use a simple domain model where we have a userList object (iterator) containing a number of user objects. Each user has an injected userDao dependency which is used for lazy-loading usageHistory, on request.

class userList
{
    public function current() { }

    public function key() { }

    public function next() { }

    public function rewind() { }

    public function valid() { }

    public function count() { }
}

class user
{
    private $usageHistory;

    public function __construct($dao, $userDataRow)
    {
        $this->dao = $dao;
        $this->usageHistory = NULL;
    }

    public function getUsageHistory()
    {
        if ($this->usageHistory === NULL)
        {
            $this->usageHistory = $this->dao->lazyLoadHistory($this);
        }
        return $this->usageHistory;
    }
}

class userDao
{
    public function __construct($database, $cache, $logger)

    public function getList() { }

    public function lazyLoadHistory() { }
}

class usageHistory
{
}

Dependency Injection

A sample invocation of this simple system might be to ask the DAO for a user list object. To create a DAO object we will almost certainly need to pass in a bunch of dependencies such as database services, caching services and logging services.

I’m using a DI container to create objects. To get a really quick idea of what these are about you can imagine doing this:

$diContainer = new diContainer();
$userDao = $diContainer->getInstance('userDao');

Instead of this:

$configuration = new systemConfig();

$database = new mysqlDatabaseConnection($configuration);
$cache = new memcacheConnection($configuration);
$logger = new firebugLogger();

$userDao = new userDao($database, $cache, $logger);
$userList = $userDao->getList();

The key idea is that the DI container will build the object graph for you. For each dependency needed it will go away and fetch that, building any other dependencies of those objects and so on recursively up the tree.

I’m using an annotation system to power my own DI container; making the whole process simple and configuration-light.

Putting objects to sleep

Caching is a very handy tool to improve the performance of applications. Storing objects in a cache (for example Memcache) prevents us having to go to database each time. Memcache is a very simple system; a key-value store. You give it some data (less than 1MB) and it stores it for you until you ask for it again. Storing objects is slightly more complex than simple strings; with objects you need to serialise them. Memcache actually does this for you (you don’t need to call serialize() first).

However caching objects can be problematic. Whenever you start to really use the power of OOP you inevitably end up with complex object graphs. Our user object, for example, contains a userDao object. This in turn contains a database service object, a cache service object and a logging service object. Some of these objects have their own dependencies! For example the database service object contains a configuration object.

The key point here is that by default, when we serialise a user object we will be serialising all the internal properties, including all the dependencies. This is undesirable.

This is where PHP’s built-in magic __sleep method comes to the rescue. Using __sleep we can tell PHP what we do want to store. Let’s assume our user object has the following properties:

class user
{
    private $dao;
    private $name;
    private $age;
    private $email;
    private $phoneNumber;
    private $usageHistory;
}

What we’ll do is tell PHP what we want to save.

class user
{
    public function __sleep()
    {
        return array('name', 'age', 'email', 'phoneNumber');
    }
}

Now we can serialise and/or cache objects without the overhead of complex dependency graphs.

Waking objects up

When it comes to restoring objects, for example via Memcache::get or via unserialize(), we will end up with a user object that has a valid name, age, email and phoneNumber property. What we won’t have is the DAO dependency or the usageHistory property. It is important to realise that the class constructor will not be called when the object is unserialised.

For pure simplicity we can use PHP’s built-in magic __wakeup method to execute code on unserialisation.

class user
{
    public function __wakeup()
    {
        $this->usageHistory = NULL;
        $diContainer = new diContainer();
        $userDao = $diContainer->getInstance('userDao');
    }
}

This is handy for ensuring that the usageHistory property is properly set to NULL (so it will lazy-load). The problem with this approach is that we lose the Inversion of Control. Instead of injecting the dependencies, we are instead looking them up; we have a tightly coupled dependency to the DI container. One of the key points of DI is that the objects themselves shouldn’t really know or care about the DI container.

When constructing objects using the DI container we never directly use the “new” keyword to create objects – instead we rely on the DI container to do this for us. This supplies all dependencies as parameters. However we can’t replace the call to __wakeup; and therefore we can’t inject dependencies here.

Restoring dependencies

To ensure that dependencies are restored correctly I use a “magic” method __restoreDependencies. Ok so it’s not actually that magic; PHP doesn’t call it automatically! However the serialisation/unserialisation in my application is localised within my cache object. Therefore what I can do is adjust my cache::get method:

class cache
{
    public function get($key)
    {
        $value = $this->memcache->get($key);
        if (is_object($value) && $value instanceof cacheable)
        {
            $this->diContainer->wakeup($value);
        }
    }
}

To make life easy I actually use a “cacheable” interface that objects must implement in order to be stored in cache. This formality really just ensures that no one tries to cache objects without making sure they think of the implications on dependencies. The cacheable interface simply ensures that an object has a __restoreDependencies() method.

The (bespoke) DI container has a “wakeup” method that will:

1. Call the __restoreDependencies() method injecting any required services (dependency objects)

2. If the __restoreDependencies() method returns an array of other objects, call the wakeup() method on those objects as well. This can repeat recursively if required.

The second point here ensures that we can cache an entire userList object and wake it up effectively. The userList object’s __restoreDependencies() method would return an array of all user objects that need waking up.

The result is that I can cache complex object graphs without dependencies, but have these dependencies automatically “fixed” when objects are retrieved from cache. The objects themselves don’t really know anything about the process. Instead all they need to do is define a simple interface which defines the required dependencies.

• Two minute intro to Git
• Installing Git on CentOS 5
• Creating and sharing a repository
• Tortoise; the familiar client for Windows
• Git hub
• Finding out more – useful links

Two minute intro to Git

I’ve come from an SVN background; you checkout a copy of a central repository, make some changes and commit. Git is a slightly different beast in that it is a distributed Source Control Management system. What this means is that you have your own local repository where you can happily commit changes (whether online or offline). To share your changes with others, you can then push your changes to another repository (either their repository or some central repository if you’d prefer). Similarly, to work on someone else’s code, you can create your own cloned version of their repository and then pull updates as required.

The reason I’m switching to Git is all about branching – I find this a real pain in SVN. If you’re not convinced you can click here to find out Git is better than your current SCM.

Installing Git on CentOS 5

Installing Git on CentOS 5 is easy if you make use of the EPEL (Extra Packages for Enterprise Linux) repository. You’ll know if you’ve got this installed if the following fails:

yum install git

To setup EPEL all you need to do is create a file /etc/yum.repos.d/epel.repo and then paste in the following:

[epel]
name=Extra Packages for Enterprise Linux 5 - $basearch
#baseurl=http://download.fedoraproject.org/pub/epel/5/$basearch
mirrorlist=http://mirrors.fedoraproject.org/mirrorlist?repo=epel-5&arch=$basearch
failovermethod=priority
enabled=1
gpgcheck=1
gpgkey=file:///etc/pki/rpm-gpg/RPM-GPG-KEY-EPEL

[epel-debuginfo]
name=Extra Packages for Enterprise Linux 5 - $basearch - Debug
#baseurl=http://download.fedoraproject.org/pub/epel/5/$basearch/debug
mirrorlist=http://mirrors.fedoraproject.org/mirrorlist?repo=epel-debug-5&arch=$basearch
failovermethod=priority
enabled=0
gpgkey=file:///etc/pki/rpm-gpg/RPM-GPG-KEY-EPEL
gpgcheck=1

[epel-source]
name=Extra Packages for Enterprise Linux 5 - $basearch - Source
#baseurl=http://download.fedoraproject.org/pub/epel/5/SRPMS
mirrorlist=http://mirrors.fedoraproject.org/mirrorlist?repo=epel-source-5&arch=$basearch
failovermethod=priority
enabled=0
gpgkey=file:///etc/pki/rpm-gpg/RPM-GPG-KEY-EPEL
gpgcheck=1

Now you can install using:

yum install git git-daemon

Creating and sharing a repository

Creating a repository is easy! Simply create a folder and type git init.

mkdir newrepo
cd newrepo
git init

Once created, we can copy/create our files (think svn import) and then do:

git add .
git commit

Once you’ve created a repository, you’ll probably want to share it. This means that other people can pull and push changes. There are a number of ways of accomplishing this (this blog post lists 8 possibilities). My usual method for sharing SVN repositories is via Apache; Git supports this as well. I think one of the simplest solutions is to use the Git Deamon. To allow others to pull and push you can share your Git repository using the following command:

git daemon --reuseaddr --base-path=/path/to/repos --export-all --verbose --enable=receive-pack

This command will share all repositories found within the folder /path/to/repos (so we would have created our “newrepo” folder within this location). Once shared you can clone the repository using the git resource locator syntax:

git clone git://remote.computer.hostname/newrepo

Or you can just use the IP address if you’d prefer.

You should now have a repository setup on a CentOS 5 server which you can clone and then pull/push updates.

Tortoise; the familiar client for Windows

When I’ve used Mercurial in the past (another distributed SCM), I’ve actually found the command line tools significantly easier to use than the GUI (Tortoise). However there is a level of familiarity that a TortoiseSVN-like frontend provides.

TortoiseGit has all the features you’d be used to from using TortoiseSVN plus Pull, Push and all the other Git-specific stuff.

Git hub

It’s worth making a quick mention of Git Hub. According to the website, “GitHub is the easiest (and prettiest) way to participate in that collaboration: fork projects, send pull requests, monitor development, all with ease.”.

Git Hub provides a handy way of visualising a Git project (listing commits, branches and pretty-printed code). It avoids the need to setup your own central Git repository and mess about setting the server up. A lot of projects seem to be moving this way, for example Symfony.

Finding out more – useful links

http://whygitisbetterthanx.com/

Some well thought out and concise arguments as to why Git is better than other SCM systems.

http://gitready.com/

Excellent site – “learn git one commit at a time”. Lots of help and advice clearly laid out.

http://git.or.cz/course/svn.html

Crash course for SVN users – really good comparison of SVN commands and the equivalent GIT commands.

http://www.jedi.be/blog/2009/05/06/8-ways-to-share-your-git-repository/

8 ways to share your git repository – file share, Git daemon, plain SSH server, SSH server git-shell, Gitosis, Apache http + gitweb, github.

1. Simple Dependency Injection (DI)
2. The Service Locator pattern
3. A DI framework

This includes a bespoke implementation of a DI framework for PHP that automatically creates configuration by conducting a simplistic static analysis of code.

What are dependencies

Consider the following code. This simple application comprises a simple event domain object combined with a Data Access Object (DAO) that deals with persistance.

event.class.php

class event
{
    private $name;
    private $cost;
    private $eventDate;

    /**
     * @param array $row Information on this event from DAO
     */
    public function __construct($row)
    {
        $this->name = $row['name'];
        $this->cost = new money($row['cost']);
        $this->eventDate = new date($row['date']);
    }

    public function __toString()
    {
        return "EVENT: {$this->name}\nCOST:  {$this->cost}\nDATE:  {$this->eventDate}\n";
    }
}

eventDao.class.php

class eventDao
{
    public function getById($id)
    {
        $db = new database('localhost','mydb','user','password');

        $row = $db->fetchAll(
           "SELECT name, cost, date FROM events WHERE id = ".$db->quote($id);
        );

        return new event($row);
    }
}

An event object is dependant on a money object and a date object. It needs to create these to function correctly.

An eventDao object is dependant on a database object and an event object. It needs the database object to get the data and it needs to create and return a new event object.

Why are depedencies problematic?

Dependencies are not in themselves problematic. It is going to be impossible to write any useful code that doesn’t have some dependencies. The problem is how we handle those the dependencies. The code example provided above presents the following problems.

1. It makes testing impossible

Writing a unit test for the event object will inevitably end up testing the money and date objects. When we create a new event object we have no control over the creation of those dependent objects. This means our unit test will cross the class boundary and what we end up with is an integration test rather than a unit test. Instead of testing the logic of the specific, isolated “unit” (our event object), we are instead testing the event object works in relation to the rest of the program.

While it may not seem immediately obvious why that’s a problem with fairly trivial dependencies such as a money object, the problem is more obvious when considering the DAO. Here we could not test the getById method without inadvertantly testing the database object. Without a fully-functioning database, setup with the expected data, our unit test will fail. Again, this isn’t a unit test, it’s more likely an intergration test or possibly even a system test.

2. The objects are tightly coupled

The eventDao class is tightly coupled to the specific concrete classes event and database. What if we want to use a different database object on our test environment? We can’t. Of course there’s ways round this immediate problem without changing too much at all. We could use global constants DATABASE_NAME, DATABASE_USER etc.. Don’t even go there! Tight coupling makes for brittle code. If you’re not convinced you can read this article or spend 10 minutes with Google.

3. It goes against the Don’t Repeat Yourself (DRY) principle

If we imagine adding some other domain objects and DAOs to our system we will end up repeating the new database() line again and again. The same goes for other domain objects that want to represent information internally as a date object.

An alternative coupling

Let’s say you’ve got this in your DAO instead:

        $db = database::getInstance();

Same problems! We probably still can’t test it (unless we have some kind of database::setInstance() method) and it’s certainly still tightly coupled regardless.

Strategy 1: Dependency Injection

Dependency Injection is very straightforward. In fact it’s so straightforward you’ve almost certainly already done it, even if you didn’t refer to it as DI. Fabien Potencier of Symfony fame explains it expertly in these slides.

To make use of dependency injection, our eventDao can be updated to:

eventDao.class.php

class eventDao
{
    private $db;

    public function __construct($db)
    {
       $this->db = $db;
    }

    public function getById($id)
    {

        $row = $this->db->fetchAll(
           "SELECT name, cost, date FROM events WHERE id = ".$this->db->quote($id);
        );

        return new event($row);
    }
}

$db = new database('localhost','mydb','user','password');
$dao = new eventDao($db);
$event = $dao->getById(1);

We can now test the getById method using a mock database object because we are injecting the dependency into the DAO object.

We can’t, however, isolate testing of the DAO completely because of the event dependency. This can be fixed by delegating responsibility for event creation to a Factory.

eventFactory.class.php

class eventFactory
{
    public function create($row)
    {
        return new event($row);
    }
}

eventDao.class.php

class eventDao
{
    private $db;
    private $eventFactory;

    public function __construct($db, $eventFactory)
    {
       $this->db = $db;
       $this->eventFactory = $eventFactory;
    }

    public function getById($id)
    {

        $row = $this->db->fetchAll(
           "SELECT name, cost, date FROM events WHERE id = ".$this->db->quote($id);
        );

        return $this->eventFactory->create($row);
    }
}

Our code is now loosely coupled and we are programming to interface (allbeit that I haven’t actually put any interfaces into the code at this stage!) To quote kdgregory from StackOverflow:

Programming to an interface is saying “I need this functionality and I don’t care where it comes from.”

By putting in place a factory for creating objects we can program only to the interface we require. In our event class, this means we don’t have to rely on specific concrete implementations for date and money, instead we merely require some object that implements iDate and iMoney, and we can use a factory to make us one of those objects.

Inversion of Control (IoC)

It’s worth noting that by injecting dependencies into the objects we have inverted control, effectively because rather than the procedural/linear style of setting up object and then doing something, we have passed in an object and are executing what almost amounts to a ‘call back’ on it. The term “Inversion of Control” seems to come up frequently when reading about DI, although I’m not sure that it’s always that clearly explained. Fowler explains it in this article. There are also some other interesting blog posts on the subject. If you want the short answer on what IoC is, check out this definition.

Object graphs

Using DI, what we inevitably end up with is a complex object graph. An object graph is simply a set of interconnected objects. In the case of DI, we have lots of interconnected objects since we are passing all our dependencies around as objects – so we end up with a lot of objects related to a lot of other objects at run time!

Strengths

This form of dependency injection is easy to understand. We avoid tight coupling, we can test our code and we are programming to interface. All is good!

Weaknesses

One of the web apps I work on uses a Front Controller pattern to handle incoming requests. The bootstrap code looks a bit like this:

$fc = new frontController();
$fc->dispatch();

If I take the issue of dependency injection to the extreme, slightly insane, but on some level undeniably logical, conclusion, I would have to inject all dependencies needed by the entire application into the constructor of the front controller! This post by Ben Scheirman on StackOverflow gives another example:

var svc = new ShippingService(new ProductLocator(),
   new PricingService(), new InventoryService(),
   new TrackingRepository(new ConfigProvider()),
   new Logger(new EmailLogger(new ConfigProvider())));

You get the idea.

We could be pragmatic about this and suggest that individual page controllers are allowed to be tightly coupled to domain objects. However it merely defers the inevitable.

The problem with this strategy is that if you add a dependency to an object, you then have to add it to all parent objects that use that object. This becomes a recursive task so the change causes a ripple effect to other code. The documentation to Google Guice explains it quite well (scroll down to the “Dependency Injection” section – due to their clever reader thing I can’t get an anchor link straight to it!) This problem relates to the inherent complexity involved in creating a large object graph.

Unfortunately, now the clients of BillingService need to lookup its dependencies. We can fix some of these by applying the pattern again! Classes that depend on it can accept a BillingService in their constructor. For top-level classes, it’s useful to have a framework. Otherwise you’ll need to construct dependencies recursively when you need to use a service

Strategy 2: Service Locator

Martin Fowler explains the idea of a service locator in detail in his article on the subject of DI. I’m going to explain it in the context of a PHP application.

A service locator is a straight forward system whereby objects can “look up” any dependencies they need from a central source. This gives the following advantages:

• It is easy to add a dependency to any object
• It is easy to replace which dependency is provided project wide, so we are adhering to the DRY principle
• It removes tight coupling between objects

The simplest service locator may look like:

serviceLocator.class.php

class serviceLocator
{
    public static function getDatabase()
    {
        return new database();
    }

    public static function getDateFactory()
    {
        return new dateFactory();
    }

    public static function getMoneyFactory()
    {
        return new moneyFactory();
    }

    public static function getEventFactory()
    {
        return new eventFactory();
    }
}

Our DAO now becomes:

eventDao.class.php

class eventDao
{
    public function getById($id)
    {

        $row = serviceLocator::getDatabase()->fetchAll(
           "SELECT name, cost, date FROM events WHERE id = ".$this->db->quote($id);
        );

        return serviceLocator::getEventFactory()->create($row);
    }
}

For testing we’d need to add in equivalent methods like serviceLocator::setMoneyFactory and serviceLocator::setDatabase.

We can simplify (or complicate depending on your point of view) our service locator by replacing methods like serviceLocator::getMoneyFactory() with a more generic serviceLocator::getService($serviceName). We could then configure the service locator in our bootstrap with calls to serviceLocator::registerService($serviceName, $object). If we really wanted to go to town we could use an XML or YAML file to store the details of the dependencies that the service locator provided. For a working system, we probably would want to go this far.

In terms of coupling, we have replaced the coupling of objects from our very first example (where eventDao was tightly coupled to database and event) with equally tight coupling, albeit this time to a single object – the service locator object. Whether this is desirable will come down to the details of the application. As Fowler points out in his discussion of locator vs injector:

The key difference is that with a Service Locator every user of a service has a dependency to the locator. The locator can hide dependencies to other implementations, but you do need to see the locator. So the decision between locator and injector depends on whether that dependency is a problem.

In terms of practical implementations, Mutant PHP has published an article on this subject which includes a sample service locator class.

The fairly new Symfony Dependency Injection Container appears to be based around the idea of a service locator. I say this because it doesn’t implement an inversion of control mechanism – as covered in strategy 3.

Strengths

The service locator provides a simple strategy for managing dependencies that is easily understood. It allows for testing and it avoids tight coupling between classes.

Weaknesses

The use of a service locator leads to a tight coupling between classes and the service locator itself.

Strategy 3: DI Framework

A dependency injection “framework” is an alternative strategy for dealing with dependencies to the arguably simpler service locator. They key idea is to stick with depedency injection (either into the constructor or via a setter), but have some external object (Fowler calls this an “assembler” in his article on the subject) actually deal with managing the dependencies, injecting them into objects as required, without the user having to worry about it.

Now coming from a PHP background, I’ve searched about for PHP-specific information on DI frameworks. So far, I haven’t managed to find anything that I feel explains the concept as well as the Guice documention does. In terms of responsiblity-driven design, Guice outlines the role of the “injector“ (Fowler’s “assembler”):

The injector’s job is to assemble graphs of objects. You request an instance of a given type, and it figures out what to build, resolves dependencies, and wires everything together.

This sounds promising, although I’m not 100% convinced I need a DI framework, I’m starting to see some advantages. There is an interesting discussion on StackOverflow (again!) about the need for a DI framework.

A bespoke DI Framework

To help understand the advantages of a DI framework I built my own, which I’ve rather confusingly called a “Service Injector”. As Benjamin Eberlei explains in a blog post on the subject of DI:

My subjective feeling tells me there are now more PHP DI containers out there than CMS or ORMs implemented in PHP, including two written by myself (an overengineered and a useful one).

Having recently read the excellent Coders at Work (go and buy it now if you haven’t read it), I took some advice from Donald Knuth who said:

The problem is that coding isn’t fun if all you can do is call things out of a library, if you can’t write the library yourself.

So I decided to write my own.

Design motivations

In Benjamin’s post, he goes on to say:

Its an awesome pattern if used on a larger scale and can (re-) wire a complex business application according to a clients needs without having to change much of the domain code.

I think my motivations for DI framework are somewhat different. I don’t see myself wanting to “re-wire” an application at a later date.
Ideally I want my logic and wiring to remain clear at the code level; I personally don’t want to delegate all the wiring to some configurator – I can see that making any debugging task harder. What I want from a framework is something that will do the hard work for me; something that will supply actual dependencies automatically.

This led me to make the following decisions:

• I wanted an automated builder; something that would look at the code and get the DI framework setup ready to go – based on class names and interfaces
• I wanted to keep Factory classes; I think it makes logical sense to have a class who’s responsibility is to create new objects of type blah

A sample application

At the top level, I can ask the DI framework to create me an object:

// setup the service injector
include APP_PATH.'siConfig.php';
$serviceInjector = new serviceInjector();

// ----

// for our test app we'll just pretend we're looking at the details
// of event #1:

$oDao = $serviceInjector->getInstance('eventDao');
$oEvent = $oDao->getById(1);

The DAO object is created, along with its dependencies; this all happens simply by annotating the code within the PHPDocumentor style comment blocks:

    /**
     * Constructor
     * @param iDatabase $database A service that will allow us to execute SQL
     * @param iEventFactory $eventFactory A service that will create event objects for us
     * @inject This informs the DI builder to inject constructor parameters on object creation
     */
    public function __construct(iDatabase $database, iEventFactory $eventFactory)

The service injector will find a class that implements iDatabase and iEventFactory and automatically inject these on object creation. The interesting thing is that either of these two services can have their own dependencies. For example, my eventFactory class declaration looks like this:

class eventFactory extends factory implements iEventFactory

It extends the Layer Supertype factory. The factory base class has a method to set its own dependency, again specified via annotation:

    /**
     * Set service injector
     * @inject This informs the DI builder to inject method parameters immediately after object creation
     */
    public function setServiceInjector(iServiceInjector $serviceInjector)
    {
        $this->serviceInjector = $serviceInjector;
    }

The service injector will happily go away and recursively assemble the required objects and their dependencies.

The builder

I have a script that can be executed as part of an automated build process (see my other post) that will create a pure-PHP configuration file for my service injector. It works by conducting a somewhat crude static analysis of the code you tell it to examine. It then works out which classes wire up to which interfaces, what extends what, which methods need parameters injecting and which classes should be shared (rather than a new instance created on every request).

Right now, it works as well as it needs to for the sample application. However it doesn’t do very well if you have more than one class that implements a given interface, and then you ask the service injector to build you a blah interface – in this situation it will fail. You’ll notice that although I’ve got a lot of interfaces in the sample application, they all have one class that implements the interface. I think this is a worthwhile exercise because it gets you into the mindset that you are programming to interface and thinking about messages that the objects send other objects.

Pros and cons

I like how my implementation creates the wiring-up configuration automatically based on the actual code. I also like how the service injector is really focussed on programming to interface: a service is simply some object that will provide a set of capabilities and the service injector’s only job is to inject these objects at run time. It does not deal with injecting strings and other configuration parameters; I think that’s OK since a string is not a service – and I set out to build something that would only do that job.

I guess that’s where my service injector differs from other implementations of dependency injection containers – I have focussed purely on something that will provide services, not any other types of depdency, such as configuration strings. Perhaps this could be considered a con!

The static analysis in this simple version is fairly rudimentary, although that said it will quite happily analyse the Zend framework source code. I tried this out and then made my date factory ask the service injector for a new Zend_Date object. This all worked fine – simply by changing one line of code.

The source code

So I’ve written this tool purely as a way to learn about the ideas involved and also to see if I could find a structure that I thought was useful for my application. It’s been done pretty quickly but if you’d like to have a closer look you can browse the source code here.

Other implementations for PHP

• Fabien Potencier has written a Dependency Injection Container for the Symfony project, although it will apparently work just as well as a stand-alone component
• Benjamin Eberlei has written not one but two!
• Federico Cargnelutti has proposed and is working on Zend_DI – a DI component for the Zend framework

Conclusions

Through this process of research I have come to the following conclusions:

• I prefer DI over a service locator because the individual modules are cleaner; dependencies are passed in rather than the object itself going and asking for them
• A DI framework seems the way to go, simply to reduce the complexity involved in manually creating complex object graphs
• I like Factory classes because they serve a clear purpose and make code easy to understand
• I want a DI framework to be able to work (almost) completely from the source code

My next step is to look more closely at existing implementations to see if they could work in a production project.