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Advanced Rails by Brad Ediger

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Chapter 1. Foundational Techniques

Simplicity is prerequisite for reliability.

—Edsger W. Dijkstra

Since its initial release in July 2004, the Ruby on Rails web framework has been steadily growing in popularity. Rails has been converting PHP, Java, and .NET developers to a simpler way: a model-view-controller (MVC) architecture, sensible defaults (“convention over configuration”), and the powerful Ruby programming language.

Rails had somewhat of a bad reputation for a lack of documentation during its first year or two. This gap has since been filled by the thousands of developers who use, contribute to, and write about Ruby on Rails, as well as by the Rails Documentation project (http://railsdocumentation.org/). There are hundreds of blogs that offer tutorials and advice for Rails development.

This book’s goal is to collect and distill the best practices and knowledge embodied by the community of Rails developers and present everything in an easy-to-understand, compact format for experienced programmers. In addition, I seek to present facets of web development that are often undertreated or dismissed by the Rails community.

What Is Metaprogramming?

Rails brought metaprogramming to the masses. Although it was certainly not the first application to use Ruby’s extensive facilities for introspection, it is probably the most popular. To understand Rails, we must first examine the parts of Ruby that make Rails possible. This chapter lays the foundation for the techniques discussed in the remainder of this book.

Metaprogramming is a programming technique in which code writes other code or introspects upon itself. The prefix meta-(from Greek) refers to abstraction; code that uses metaprogramming techniques works at two levels of abstraction simultaneously.

Metaprogramming is used in many languages, but it is most popular in dynamic languages because they typically have more runtime capabilities for manipulating code as data. Though reflection is available in more static languages such as C# and Java, it is not nearly as transparent as in the more dynamic languages such as Ruby because the code and data are on two separate levels at runtime.

Introspection is typically done on one of two levels. Syntactic introspection is the lowest level of introspection—direct examination of the program text or token stream. Template-based and macro based metaprogramming usually operate at the syntactic level.

Lisp encourages this style of metaprogramming by using S-expressions (essentially a direct translation of the program’s abstract syntax tree) for both code and data. Metaprogramming in Lisp heavily involves macros, which are essentially templates for code. This offers the advantage of working on one level; code and data are both represented in the same way, and the only thing that distinguishes code from data is whether it is evaluated. However, there are some drawbacks to metaprogramming at the syntactic level. Variable capture and inadvertent multiple evaluation are direct consequences of having code on two levels of abstraction in the source evaluated in the same namespace. Although there are standard Lisp idioms for dealing with these problems, they represent more things the Lisp programmer must learn and think about.

Syntactic introspection for Ruby is available through the ParseTree library, which translates Ruby source into S-expressions. [1] An interesting application of this library is Heckle, [2] a test-testing framework that parses Ruby source code and mutates it, changing strings and flipping true to false and vice versa. The idea is that if you have good test coverage, any mutation of your code should cause your unit tests to fail.

The higher-level alternative to syntactic introspection is semantic introspection,or examination of a program through the language’s higher-level data structures. Exactly how this looks differs between languages, but in Ruby it generally means working at the class and method level: creating, rewriting, and aliasing methods; intercepting method calls; and manipulating the inheritance chain. These techniques are usually more orthogonal to existing code than syntactic methods, because they tend to treat existing methods as black boxes rather than poking around inside their implementations.

Don’t Repeat Yourself

At a high level, metaprogramming is useful in working toward the DRY principle (Don’t Repeat Yourself). Also referred to as “Once and Only Once,” the DRY principle dictates that you should only need to express a particular piece of information once in a system. Duplication is usually unnecessary, especially in dynamic languages like Ruby. Just as functional abstraction allows us to avoid duplicating code that is the same or nearly the same, metaprogramming allows us to avoid duplicating similar concepts when they recur throughout an application.

Metaprogramming is primarily about simplicity. One of the easiest ways to get a feel for metaprogramming is to look for repeated code and factor it out. Redundant code can be factored into functions; redundant functions or patterns can often be factored out through the use of metaprogramming.


Design patterns cover overlapping territory here; patterns are designed to minimize the number of times you have to solve the same problem. In the Ruby community, design patterns have acquired something of a negative reputation. To some developers, patterns are a common vocabulary for describing solutions to recurring problems. To others, they are overengineered.

To be sure, patterns can be overapplied. However, this need not be the case if they are used judiciously. Design patterns are only useful insofar as they reduce cognitive complexity. In Ruby, some of the fine-grained patterns are so transparent that it would be counterintuitive to call them “patterns”; they are really idioms, and most programmers who “think in Ruby” use them without thinking. Patterns should be thought of as a vocabulary for describing architecture, not as a library of prepackaged implementation solutions. Good Ruby design patterns are vastly different from good C++ design patterns in this regard.

In general, metaprogramming should not be used simply to repeat code. You should always evaluate the options to see if another technique, such as functional abstraction, would better suit the problem. However, in a few cases, repeating code via metaprogramming is the best way to solve a problem. For example, when several very similar methods must be defined on an object, as in ActiveRecord helper methods, metaprogramming can be used.


Code that rewrites itself can be very hard to write and maintain. The programming devices you choose should always serve your needs—they should make your life easier, not more difficult. The techniques illustrated here should be more tools in your toolbox, not the only tools.

Bottom-Up Programming

Bottom-up programming is a concept borrowed from the Lisp world. The primary concept in bottom-up programming is building abstractions from the lowest level. By writing the lowest-level constructs first, you are essentially building your program on top of those abstractions. In a sense, you are writing a domain-specific language in which you build your programs.

This concept is extremely useful in ActiveRecord. After creating your basic schema and model objects, you can begin to build abstractions on top of those objects. Many Rails projects start out by building abstractions on the model like this, before writing a single line of controller code or even designing the web interface:

	class Order < ActiveRecord::Base
	  has_many :line_items

	  def total
	    subtotal + shipping + tax

	  def subtotal

	  def shipping
	    shipping_base_price + line_items.sum(:shipping)

	  def tax
	    subtotal * TAX_RATE

Ruby Foundations

This book relies heavily on a firm understanding of Ruby. This section will explain some aspects of Ruby that are often confusing or misunderstood. Some of this may be familiar, but these are important concepts that form the basis for the metaprogramming techniques covered later in this chapter.

Classes and Modules

Classes and modules are the foundation of object-oriented programming in Ruby. Classes facilitate encapsulation and separation of concerns. Modules can be used as mixins—bundles of functionality that are added onto a class to add behaviors in lieu of multiple inheritance. Modules are also used to separate classes into namespaces.

In Ruby, every class name is a constant. This is why Ruby requires class names to begin with an uppercase letter. The constant evaluates to the class object, which is an object of the class Class. This is distinct from the Class object, which represents the actual class Class. [3] When we refer to a “class object” (with a lowercase C), we mean any object that represents a class (including Class itself). When we refer to the “Class object” (uppercase C), we mean the class Class, which is the superclass of all class objects.

The class Class inherits from Module; every class is also a module. However, there is an important distinction. Classes cannot be mixed in to other classes, and classes cannot extend objects; only modules can.

Method Lookup

Method lookup in Ruby can be very confusing, but it is quite regular. The easiest way to understand complicated situations is to visualize the data structures that Ruby creates behind the scenes.

Every Ruby object[4] has a set of fields in memory:


A pointer to the class object of this object. (It is klass instead of class because the latter is a reserved word in C++ and Ruby; if it were called class, Ruby would compile with a C compiler but not with a C++ compiler. This deliberate misspelling is used everywhere in Ruby.)


“Instance Variable Table,” a hashtable containing the instance variables belonging to this object.


A bitfield of Boolean flags with some status information, such as the object’s taint status, garbage collection mark bit, and whether the object is frozen.

Every Ruby class or module has the same fields, plus two more:


“Method Table,” a hashtable of this class or module’s instance methods.


A pointer to this class or module’s superclass.

These fields play a huge role in method lookup, and it is important that you understand them. In particular, you should pay close attention to the difference between the klass and super pointers of a class object.

The rules

The method lookup rules are very simple, but they depend on an understanding of how Ruby’s data structures work. When a message is sent to an object, [5] the following steps occur:

  1. Ruby follows the receiver’s klass pointer and searches the m_tbl of that class object for a matching method. (The target of a klass pointer will always be a class object.)

  2. If no method is found, Ruby follows that class object’s super pointer and continues the search in the superclass’s m_tbl.

  3. Ruby progresses in this manner until the method is found or the top of the super chain is reached.

  4. If the method is not found in any object on the chain, Ruby invokes method_ missing on the receiver of the original method. This starts the process over again, this time looking for method_missing rather than the original method.

These rules apply universally. All of the interesting things that method lookup involves (mixins, class methods, and singleton classes) are consequences of the structure of the klass and super pointers. We will now examine this process in detail.

Class inheritance

The method lookup process can be confusing, so we’ll start simple. Here is the simplest possible class definition in Ruby:

	class A

This code generates the following data structures in memory (see Figure 1-1).

Data structures for a single class
Figure 1-1. Data structures for a single class

The double-bordered boxes represent class objects—objects whose klass pointer points to the Class object. A’s super pointer refers to the Object class object, indicating that A inherits from Object. For clarity, from now on we will omit default klass pointers to Class, Module, and Object where there is no ambiguity.

The next-simplest case is inheritance from one class. Class inheritance simply follows the super pointers. For example, we will create a B class that descends from A:

	class B < A 

The resulting data structures are shown in Figure 1-2.

One level of inheritance
Figure 1-2. One level of inheritance

The super keyword always delegates along the method lookup chain, as in the following example:

	class B
	  def initialize
	    logger.info "Creating B object"

The call to super in initialize will follow the standard method lookup chain, beginning with A#initialize.

Class instantiation

Now we get a chance to see how method lookup is performed. We first create an instance of class B:

obj = B.new

This creates a new object, and sets its klass pointer to B’s class object (see Figure 1-3).

Class instantiation
Figure 1-3. Class instantiation

The single-bordered box around obj represents a plain-old object instance. Note that each box in this diagram is an object instance. However, the double-bordered boxes represent objects that are instances of the Class class (hence their klass pointer points to the Class object).

When we send obj a message:


this chain is followed:

  1. obj's klass pointer is followed to B; B’s methods (in m_tbl) are searched for a matching method.

  2. No methods are found in B. B’s super pointer is followed, and A is searched for methods.

  3. No methods are found in A. A’s super pointer is followed, and Object is searched for methods.

  4. The Object class contains a to_s method in native code (rb_any_to_s). This is invoked, yielding a value like "#<B:0x1cd3c0>“. The rb_any_to_s method examines the receiver’s klass pointer to determine what class name to display; therefore, B is shown even though the method invoked resides in Object.

Including modules

Things get more complicated when we start mixing in modules. Ruby handles module inclusion with ICLASSes,[6] which are proxies for modules. When you include a module into a class, Ruby inserts an ICLASS representing the included module into the including class object’s super chain.

For our module inclusion example, let’s simplify things a bit by ignoring B for now. We define a module and mix it in to A, which results in data structures shown in Figure 1-4:

	module Mixin
	  def mixed_method
	    puts "Hello from mixin"
	class A
	  include Mixin
Inclusion of a module into the lookup chain
Figure 1-4. Inclusion of a module into the lookup chain

Here is where the ICLASS comes into play. The super link pointing from A to Object is intercepted by a new ICLASS (represented by the box with the dashed line). The ICLASS is a proxy for the Mixin module. It contains pointers to Mixin’s iv_tbl (instance variables) and m_tbl (methods).

From this diagram, it is easy to see why we need proxy classes: the same module may be mixed in to any number of different classes—classes that may inherit from different classes (thus having different super pointers). We could not directly insert Mixin into the lookup chain, because its super pointer would have to point to two different things if it were mixed in to two classes with different parents.

When we instantiate A, the structures are as shown in Figure 1-5:

	objA = A.new
Method lookup for a class with an included module
Figure 1-5. Method lookup for a class with an included module

We invoke the mixed_method method from the mixin, with objA as the receiver:

	# >> Hello from mixin

The following method-lookup process takes place:

  1. objA’s class, A, is searched for a matching method. None is found.

  2. A’s super pointer is followed to the ICLASS that proxies Mixin. This proxy object is searched for a matching method. Because the proxy’s m_tbl is the same as Mixin’s m_tbl, the mixed_method method is found and invoked.

Many languages with multiple inheritance suffer from the diamond problem, which is ambiguity in resolving method calls on objects whose classes have a diamond-shaped inheritance graph, as shown in Figure 1-6.

Given this diagram, if an object of class D calls a method defined in class A that has been overridden in both B and C, there is ambiguity about which method should be called. Ruby resolves this by linearizing the order of inclusion. Upon a method call, the lookup chain is searched linearly, including any ICLASSes that have been inserted into the chain.

First of all, Ruby does not support multiple inheritance; however, multiple modules can be mixed into classes and other modules. Therefore, A, B, and C must be modules. We see that there is no ambiguity here; the method chosen is the latest one that was inserted into the lookup chain:

	module A
	  def hello
	    "Hello from A"
The diamond problem of multiple inheritance
Figure 1-6. The diamond problem of multiple inheritance
	module B
	  include A
	  def hello
	    "Hello from B"

	module C
	  include A
	  def hello
	    "Hello from C"

	class D
	  include B
	  include C

	D.new.hello # => "Hello from C"

And if we change the order of inclusion, the result changes correspondingly:

	class D
	  include C
	  include B
	D.new.hello # => "Hello from B"

In this last example, where B is included last, the object graph looks like Figure 1-7 (for simplicity, pointers to Object and Class have been elided).

Ruby’s solution for the diamond problem: linearization
Figure 1-7. Ruby’s solution for the diamond problem: linearization

The singleton class

Singleton classes (also metaclasses or eigenclasses; see the upcoming sidebar, “Single-ton Class Terminology”) allow an object’s behavior to be different from that of other objects of its class. You’ve probably seen the notation to open up a singleton class before:

	class A

	objA = A.new
	objB = A.new
	objA.to_s # => "#<A:0x1cd0a0>"
	objB.to_s # => "#<A:0x1c4e28>"

	class <<objA # Open the singleton class of objA
	  def to_s; "Object A"; end

	objA.to_s # => "Object A"
	objB.to_s # => "#<A:0x1c4e28>"

The class <<objA notation opens objA’s singleton class. Instance methods added to the singleton class function as instance methods in the lookup chain. The resulting data structures are shown in Figure 1-8.

Singleton class of an object
Figure 1-8. Singleton class of an object

The objB instance is of class A, as usual. And if you ask Ruby, it will tell you that objA is also of class A:

	objA.class # => A

However, something different is going on behind the scenes. Another class object has been inserted into the lookup chain. This object is the singleton class of objA.We refer to it as "Class:objA" in this documentation. Ruby calls it a similar name: #<Class:#<A:0x1cd0a0>>. Like all classes, the singleton class’s klass pointer (not shown) points to the Class object.

The singleton class is marked as a virtual class (one of the flags is used to indicate that a class is virtual). Virtual classes cannot be instantiated, and we generally do not see them from Ruby unless we take pains to do so. When we ask Ruby for objA’s class, it traverses the klass and super pointers up the hierarchy until it finds the first nonvirtual class.

Therefore, it tells us that objA’s class is A. This is important to remember: an object’s class (from Ruby’s perspective) may not match the object pointed to by klass.

Singleton classes are called singleton for a reason: there can only be one singleton class per object. Therefore, we can refer unambiguously to "objA’s singleton class” or Class:objA. In our code, we can assume that the singleton class exists; in reality, for efficiency, Ruby creates it only when we first mention it.

Ruby allows singleton classes to be defined on any object except Fixnums or symbols. Fixnums and symbols are immediate values (for efficiency, they’re stored as themselves in memory, rather than as a pointer to a data structure). Because they’re stored on their own, they don’t have klass pointers, so there’s no way to alter their method lookup chain.

You can open singleton classes for true, false, and nil, but the singleton class returned will be the same as the object’s class. These values are singleton instances (the only instances) of TrueClass, FalseClass, and NilClass, respectively. When you ask for the singleton class of true, you will get TrueClass, as the immediate value true is the only possible instance of that class. In Ruby:

	true.class # => TrueClass
	class << true; self; end # => TrueClass
	true.class == (class << true; self; end) # => true

Singleton classes of class objects

Here is where it gets complicated. Keep in mind the basic rule of method lookup: first Ruby follows an object’s klass pointer and searches for methods; then Ruby keeps following super pointers all the way up the chain until it finds the appropriate method or reaches the top.

The important thing to remember is that classes are objects, too. Just as a plain-old object can have a singleton class, class objects can also have their own singleton classes. Those singleton classes, like all other classes, can have methods. Since the singleton class is accessed through the klass pointer of its owner’s class object, the singleton class’s instance methods are class methods of the singleton’s owner.

The full set of data structures for the following code is shown in Figure 1-9:

	class A

Class A inherits from Object. The A class object is of type Class. Class inherits from Module, which inherits from Object. The methods stored in A’s m_tbl are instance methods of A. So what happens when we call a class method on A?

	A.to_s # => "A"

The same method lookup rules apply, with A as the receiver. (Remember, A is a constant that evaluates to A’s class object.) First, Ruby follows A’s klass pointer to Class. Class’s m_tbl is searched for a function named to_s. Finding none, Ruby follows Class's super pointer to Module, where the to_s function is found (in native code, rb_mod_to_s).

Full set of data structures for a single class
Figure 1-9. Full set of data structures for a single class

This should not be a surprise. There is no magic here. Class methods are found in the exact same way as instance methods—the only difference is whether the receiver is a class or an instance of a class.

Now that we know how class methods are looked up, it would seem that we could define class methods on any class by defining instance methods on the Class object (to insert them into Class’s m_tbl). Indeed, this works:

	class A; end
	# from Module#to_s
	A.to_s # => "A"

	class Class
	  def to_s; "Class#to_s"; end
	A.to_s # => "Class#to_s"

That is an interesting trick, but it is of very limited utility. Usually we want to define unique class methods on each class. This is where singleton classes of class objects are used. To open up a singleton class on a class, simply pass the class’s name as the object to the singleton class notation:

	class A; end
	class B; end

	class <<A
	  def to_s; "Class A"; end

	A.to_s # => "Class A"
	B.to_s # => "B"

The resulting data structures are shown in Figure 1-10. Class B is omitted for brevity.

Singleton class of a class
Figure 1-10. Singleton class of a class

The to_s method has been added to A’s singleton class, or Class:A. Now, when A.to_s is called, Ruby will follow A's klass pointer to Class:A and invoke the appropriate method there.

There is one more wrinkle in method definition. In a class or module definition, self always refers to the class or module object:

	class A
	  self # => A

So, inside A’s class definition, class<<A can also be written class<<self, since inside that definition A and self refer to the same object. This idiom is used everywhere in Rails to define class methods. This example shows all of the ways to define class methods:

	class A
	  def A.class_method_one; "Class method"; end

	  def self.class_method_two; "Also a class method"; end

	  class <<A
	    def class_method_three; "Still a class method";

	  class <<self
	    def class_method_four; "Yet another class method"; end

	  def A.class_method_five
	    "This works outside of the class definition"

	  class <<A
	    def A.class_method_six
	      "You can open the metaclass outside of the class definition"

	  # Print the result of calling each method in turn
	  %w(one two three four five six).each do |number|
	    puts A.send(:"class_method_#{number}")

	  # >> Class method
	  # >> Also a class method
	  # >> Still a class method
	  # >> Yet another class method
	  # >> This works outside of the class definition
	  # >> You can open the metaclass outside of the class definition

This also means that inside a singleton class definition—as in any other class definition—self refers to the class object being defined. When we remember that the value of a block or class definition is the value of the last statement executed, we can see that the value of class <<objA; self; end is objA’s singleton class. The class <<objA construct opens up the singleton class, and self (the singleton class) is returned from the class definition.

Putting this together, we can open up the Object class and add an instance method to every object that returns that object’s singleton class:

	class Object
   	  def metaclass
	    class <<self

This method forms the basis of Metaid, which is described shortly.

Method missing

After all of that confusion, method_missing is remarkably simple. There is one rule: if the whole method lookup procedure fails all the way up to Object, method lookup is tried again, looking for a method_missing method rather than the original method. If the method is found, it is called with the same arguments as the original method, with the method name prepended. Any block given is also passed through.

The default method_missing function in Object (rb_method_missing) raises an exception.


why the lucky stiff has created a tiny library for Ruby metaprogramming called metaid.rb. This snippet is useful enough to include in any project in which meta-programming is needed:[7]

	class Object
	  # The hidden singleton lurks behind everyone
	  def metaclass; class << self; self; end; end
	  def meta_eval &blk; metaclass.instance_eval &blk; end

	  # Adds methods to a metaclass
	  def meta_def name, &blk
	    meta_eval { define_method name, &blk }

	  # Defines an instance method within a class
	  def class_def name, &blk
	    class_eval { define_method name, &blk }

This library defines four methods on every object:


Refers to the singleton class of the receiver (self).


The equivalent of class_eval for singleton classes. Evaluates the given block in the context of the receiver’s singleton class.


Defines a method within the receiver’s singleton class. If the receiver is a class or module, this will create a class method (instance method of the receiver’s singleton class).


Defines an instance method in the receiver (which must be a class or module).

Metaid’s convenience lies in its brevity. By using a shorthand for referring to and augmenting metaclasses, your code will become clearer rather than being littered with constructs like class << self; self; end. The shorter and more readable these techniques are, the more likely you are to use them appropriately in your programs.

This example shows how we can use Metaid to examine and simplify our singleton class hacking:

	class Person
	  def name; "Bob"; end
	  def self.species; "Homo sapiens"; end

Class methods are added as instance methods of the singleton class:

	Person.instance_methods(false)            # => ["name"]
	Person.metaclass.instance_methods -
	  Object.metaclass.instance_methods       # => ["species"]

Using the methods from Metaid, we could have written the method definitions as:

Person.class_def(:name) { "Bob" }
Person.meta_def(:species) { "Homo sapiens" }

Variable Lookup

There are four types of variables in Ruby: global variables, class variables, instance variables, and local variables.[8] Global variables are stored globally, and local variables are stored lexically, so neither of them is relevant to our discussion now, as they do not interact with Ruby’s class system.

Instance variables are specific to a certain object. They are prefixed with one @ symbol: @price is an instance variable. Because every Ruby object has an iv_tbl structure, any object can have instance variables.

Since a class is also an object, a class can have instance variables. The following code accesses an instance variable of a class:

	class A
	  @ivar = "Instance variable of A"

	A.instance_variable_get(:@ivar) # => "Instance variable of A"

Instance variables are always resolved based on the object pointed to by self. Because self is A’s class object in the class A … end definition, @ivar belongs to A’s class object.

Class variables are different. Any instance of a class can access its class variables (which start with @@). Class variables can also be referenced from the class definition itself. While class variables and instance variables of a class are similar, they’re not the same:

	class A
	  @var = "Instance variable of A"
	  @@var = "Class variable of A"

	  def A.ivar

	  def A.cvar

	A.ivar # => "Instance variable of A"
	A.cvar # => "Class variable of A"

In this code sample, @var and @@var are stored in the same place: in A’s iv_tbl. However, they are different variables, because they have different names (the @ symbols are included in the variable’s name as stored). Ruby’s functions for accessing instance variables and class variables check to ensure that the names passed are in the proper format:

	# ~> -:17:in 'instance_variable_get': '@@var' is not allowed as an instance
	    variable name (NameError)

Class variables can be somewhat confusing to use. They are shared all the way down the inheritance hierarchy, so subclasses that modify a class variable will modify the parent’s class variable as well.

	>> class A; @@x = 3 end
	=> 3
	>> class B < A; @@x = 4 end
	=> 4
	>> class A; @@x end
	=> 4

This may be useful, but it may also be confusing. Generally, you either want class instance variables—which are independent of the inheritance hierarchy—or the class inheritable attributes provided by ActiveSupport, which propagate values in a controlled, well-defined manner.

Blocks, Methods, and Procs

One powerful feature of Ruby is the ability to work with pieces of code as objects. There are three classes that come into play, as follows:


A Proc represents a code block: a piece of code that can be called with arguments and has a return value.


This is similar to a Proc; it represents an instance method of a particular class. (Remember that class methods are instance methods of a class object, so UnboundMethods can represent class methods, too.) An UnboundMethod must be bound to a class before it can be invoked.


Method objects are UnboundMethods that have been bound to an object with UnboundMethod#bind. Alternatively, they can be obtained with Object#method.

Let’s examine some ways to get Proc and Method objects. We’ll use the Fixnum#+ method as an example. We usually invoke it using the dyadic syntax:

	3 + 5 # => 8

However, it can be invoked as an instance method of a Fixnum object, like any other instance method:

	3.+(5) # => 8

We can use the Object#method method to get an object representing this instance method. The method will be bound to the object that method was called on, 3.

	add_3 = 3.method(:+)
	add_3 # => #<Method: Fixnum#+>

This method can be converted to a Proc, or called directly with arguments:

	add_3.to_proc # => #<Proc:0x00024b08@-:6>
	add_3.call(5) # => 8
	# Method#[] is a handy synonym for Method#call.
	add_3[5] # => 8

There are two ways to obtain an unbound method. We can call instance_method on the class object:

	add_unbound = Fixnum.instance_method(:+)
	add_unbound # => #<UnboundMethod: Fixnum#+>

We can also unbind a method that has already been bound to an object:

	add_unbound == 3.method(:+).unbind # => true
	add_unbound.bind(3).call(5) # => 8

We can bind the UnboundMethod to any other object of the same class:

	add_unbound.bind(15)[4] # => 19

However, the object we bind to must be an instance of the same class, or else we get a TypeError:

	add_unbound.bind(1.5)[4] # =>
	# ~> -:16:in 'bind': bind argument must be an instance of Fixnum (TypeError)
	# ~> from -:16

We get this error because + is defined in Fixnum; therefore, the UnboundMethod object we receive must be bound to an object that is a kind_of?(Fixnum). Had the + method been defined in Numeric (from which both Fixnum and Float inherit), the preceding code would have returned 5.5.

Blocks to Procs and Procs to blocks

One downside to the current implementation of Ruby: blocks are not always Procs, and vice versa. Ordinary blocks (created with do…end or {}) must be attached to a method call, and are not automatically objects. For example, you cannot say code_ block ={puts"abc"}. This is what the Kernel#lambda and Proc.new functions are for: converting blocks to Procs. [9]

	block_1 = lambda { puts "abc" } # => #<Proc:0x00024914@-:20>
	block_2 = Proc.new { puts "abc" } # => #<Proc:0x000246a8@-:21>

There is a slight difference between Kernel#lambda and Proc.new. Returning from a Proc created with Kernel#lambda returns the given value to the calling function; returning from a Proc created with Proc.new attempts to return from the calling function, raising a LocalJumpError if that is impossible. Here is an example:

	def block_test
	  lambda_proc = lambda { return 3 }
	  proc_new_proc = Proc.new { return 4 }

	  lambda_proc.call # => 3
	  proc_new_proc.call # =>

	  puts "Never reached"
	block_test # => 4

The return statement in lambda_proc returns the value 3 from the lambda. Conversely, the return statement in proc_new_proc returns from the calling function, block_test— thus, the value 4 is returned from block_test. The puts statement is never executed, because the proc_new_proc.call statement returns from block_test first.

Blocks can also be converted to Procs by passing them to a function, using & in the function’s formal parameters:

	def some_function(&b)
	  puts "Block is a #{b} and returns #{b.call}"

	some_function { 6 + 3 }
	# >> Block is a #<Proc:0x00025774@-:7> and returns 9

Conversely, you can also substitute a Proc with & when a function expects a block:

	add_3 = lambda {|x| x+3}
	(1..5).map(&add_3) # => [4, 5, 6, 7, 8]


Closures are created when a block or Proc accesses variables defined outside of its scope. Even though the containing block may go out of scope, the variables are kept around until the block or Proc referencing them goes out of scope. A simplistic example, though not practically useful, demonstrates the idea:

	def get_closure
	  data = [1, 2, 3]
	  lambda { data }
	block = get_closure
	block.call # => [1, 2, 3]

The anonymous function (the lambda) returned from get_closure references the local variable data, which is defined outside of its scope. As long as the block variable is in scope, it will hold its own reference to data, and that instance of data will not be destroyed (even though the get_closure function returns). Note that each time get_closure is called, data references a different variable (since it is function-local):

	block = get_closure
	block2 = get_closure

	block.call.object_id # => 76200
	block2.call.object_id # => 76170

A classic example of closures is the make_counter function, which returns a counter function (a Proc) that, when executed, increments and returns its counter. In Ruby, make_counter can be implemented like this:

	def make_counter(i=0)
	  lambda { i += 1 }

	x = make_counter
	x.call # => 1
	x.call # => 2

	y = make_counter
	y.call # => 1
	y.call # => 2

The lambda function creates a closure that closes over the current value of the local variable i. Not only can the variable be accessed, but its value can be modified. Each closure gets a separate instance of the variable (because it is a variable local to a particular instantiation of make_counter). Since x and y contain references to different instances of the local variable i, they have different state.

Metaprogramming Techniques

Now that we’ve covered the fundamentals of Ruby, we can examine some of the common metaprogramming techniques that are used in Rails.

Although we write examples in Ruby, most of these techniques are applicable to any dynamic programming language. In fact, many of Ruby’s metaprogramming idioms are shamelessly stolen from either Lisp, Smalltalk, or Perl.

Delaying Method Lookup Until Runtime

Often we want to create an interface whose methods vary depending on some piece of runtime data. The most prominent example of this in Rails is ActiveRecord’s attribute accessor methods. Method calls on an ActiveRecord object (like person.name) are translated at runtime to attribute accesses. At the class-method level, ActiveRecord offers extreme flexibility: Person.find_all_by_user_id_and_active(42, true) is translated into the appropriate SQL query, raising the standard NoMethodError exception should those attributes not exist.

The magic behind this is Ruby’s method_missing method. When a nonexistent method is called on an object, Ruby first checks that object’s class for a method_missing method before raising a NoMethodError. method_missing’s first argument is the name of the method called; the remainder of the arguments correspond to the arguments passed to the method. Any block passed to the method is passed through to method_missing. So, a complete method signature is:

	def method_missing(method_id, *args, &block)

There are several drawbacks to using method_missing:

  • It is slower than conventional method lookup. Simple tests indicate that method dispatch with method_missing is at least two to three times as expensive in time as conventional dispatch.

  • Since the methods being called never actually exist—they are just intercepted at the last step of the method lookup process—they cannot be documented or introspected as conventional methods can.

  • Because all dynamic methods must go through the method_missing method, the body of that method can become quite large if there are many different aspects of the code that need to add methods dynamically.

  • Using method_missing restricts compatibility with future versions of an API. Once you rely on method_missing to do something interesting with undefined methods, introducing new methods in a future API version can break your users’ expectations.

A good alternative is the approach taken by ActiveRecord’s generate_read_methods feature. Rather than waiting for method_missing to intercept the calls, ActiveRecord generates an implementation for the attribute setter and reader methods so that they can be called via conventional method dispatch.

This is a powerful method in general, and the dynamic nature of Ruby makes it possible to write methods that replace themselves with optimized versions of themselves when they are first called. This is used in Rails routing, which needs to be very fast; we will see that in action later in this chapter.

Generative Programming: Writing Code On-the-Fly

One powerful technique that encompasses some of the others is generative programming—code that writes code.

This technique can manifest in the simplest ways, such as writing a shell script to automate some tedious part of programming. For example, you may want to populate your test fixtures with a sample project for each user:

	  id: 1
	  owner_id: 1
	  billing_status_id: 12

	  id: 2
	  owner_id: 2
	  billing_status_id: 4


If this were a language without scriptable test fixtures, you might be writing these by hand. This gets messy when the data starts growing, and is next to impossible when the fixtures have strange dependencies on the source data. Naïve generative programming would have you writing a script to generate this fixture from the source. Although not ideal, this is a great improvement over writing the complete fixtures by hand. But this is a maintenance headache: you have to incorporate the script into your build process, and ensure that the fixture is regenerated when the source data changes.

This is rarely, if ever, needed in Ruby or Rails (thankfully). Almost every aspect of Rails application configuration is scriptable, due in large part to the use of internal domain-specific languages (DSLs). In an internal DSL, you have the full power of the Ruby language at your disposal, not just the particular interface the library author decided you should have.

Returning to the preceding example, ERb makes our job a lot easier. We can inject arbitrary Ruby code into the YAML file above using ERb’s <% %> and <%= %> tags, including whatever logic we need:

	<% User.find_all_by_active(true).each_with_index do |user, i| %>
	<%= user.login %>_project:
	     id: <%= i %>
	     owner_id: <%= user.id %>
	     billing_status_id: <%= user.billing_status.id %>
	<% end %>

ActiveRecord’s implementation of this handy trick couldn’t be simpler:

	yaml = YAML::load(erb_render(yaml_string))

using the helper method erb_render:

	def erb_render(fixture_content)

Generative programming often uses either Module#define_method or class_eval and def to create methods on-the-fly. ActiveRecord uses this technique for attribute accessors; the generate_read_methods feature defines the setter and reader methods as instance methods on the ActiveRecord class in order to reduce the number of times method_missing (a relatively expensive technique) is needed.


Continuations are a very powerful control-flow mechanism. A continuation represents a particular state of the call stack and lexical variables. It is a snapshot of a point in time when evaluating Ruby code. Unfortunately, the Ruby 1.8 implementation of continuations is so slow as to be unusable for many applications. The upcoming Ruby 1.9 virtual machines may improve this situation, but you should not expect good performance from continuations under Ruby 1.8. However, they are useful constructs, and continuation-based web frameworks provide an interesting alternative to frameworks like Rails, so we will survey their use here.

Continuations are powerful for several reasons:

  • Continuations are just objects; they can be passed around from function to function.

  • Continuations can be invoked from anywhere. If you hold a reference to a continuation, you can invoke it.

  • Continuations are re-entrant. You can use continuations to return from a function multiple times.

Continuations are often described as “structured GOTO.” As such, they should be treated with the same caution as any kind of GOTO construct. Continuations have little or no place inside application code; they should usually be encapsulated within libraries. I don’t say this because I think developers should be protected from themselves. Rather, continuations are general enough that it makes more sense to build abstractions around them than to use them directly. The idea is that a programmer should think “external iterator” or “coroutine” (both abstractions built on top of continuations) rather than “continuation” when building the application software.

Seaside [10] is a Smalltalk web application framework built on top of continuations. Continuations are used in Seaside to manage session state. Each user session corresponds to a server-side continuation. When a request comes in, the continuation is invoked and more code is run. The upshot is that entire transactions can be written as a single stream of code, even if they span multiple HTTP requests. This power comes from the fact that Smalltalk’s continuations are serializable; they can be written out to a database or to the filesystem, then thawed and reinvoked upon a request. Ruby’s continuations are nonserializable. In Ruby, continuations are in-memory only and cannot be transformed into a byte stream.

Borges (http://borges.rubyforge.org/) is a straightforward port of Seaside 2 to Ruby. The major difference between Seaside and Borges is that Borges must store all current continuations in memory, as they are not serializable. This is a huge limitation that unfortunately prevents Borges from being successful for web applications with any kind of volume. If serializable continuations are implemented in one of the Ruby implementations, this limitation can be removed.

The power of continuations is evident in the following Borges sample code, which renders a list of items from an online store:

	class SushiNet::StoreItemList < Borges::Component

	  def choose(item)
	    call SushiNet::StoreItemView.new(item)

	  def initialize(items)
	    @batcher = Borges::BatchedList.new items, 8

	  def render_content_on(r)
	    r.list_do @batcher.batch do |item|
	      r.anchor item.title do choose item end

	    r.render @batcher

  end # class SushiNet::StoreItemList

The bulk of the action happens in the render_content_on method, which uses a BatchedList (a paginator) to render a paginated list of links to products. But the fun happens in the call to anchor, which stores away the call to choose, to be executed when the corresponding link is clicked.

However, there is still vast disagreement on how useful continuations are for web programming. HTTP was designed as a stateless protocol, and continuations for web transactions are the polar opposite of statelessness. All of the continuations must be stored on the server, which takes additional memory and disk space. Sticky sessions are required, to direct a user’s traffic to the same server. As a result, if one server goes down, all of its sessions are lost. The most popular Seaside application, DabbleDB (http://dabbledb.com/), actually uses continuations very little.


Bindings provide context for evaluation of Ruby code. A binding is the set of variables and methods that are available at a particular (lexical) point in the code. Any place in Ruby code where statements may be evaluated has a binding, and that binding can be obtained with Kernel#binding. Bindings are just objects of class Binding, and they can be passed around as any objects can:

	class C
	  binding # => #<Binding:0x2533c>
	  def a_method
	binding # => #<Binding:0x252b0>
	C.new.a_method # => #<Binding:0x25238>

The Rails scaffold generator provides a good example of the use of bindings:

	class ScaffoldingSandbox
	  include ActionView::Helpers::ActiveRecordHelper
	  attr_accessor :form_action, :singular_name, :suffix, :model_instance

	  def sandbox_binding

	  # ...

ScaffoldingSandbox is a class that provides a clean environment from which to render a template. ERb can render templates within the context of a binding, so that an API is available from within the ERb templates.

	part_binding = template_options[:sandbox].call.sandbox_binding
	# ...

Earlier I mentioned that blocks are closures. A closure’s binding represents its state—the set of variables and methods it has access to. We can get at a closure’s binding with the Proc#binding method:

	def var_from_binding(&b)
	  eval("var", b.binding)
	var = 123
	var_from_binding {} # => 123
	var = 456
	var_from_binding {} # => 456

Here we are only using the Proc as a method by which to get the binding. By accessing the binding (context) of those blocks, we can access the local variable var with a simple eval against the binding.

Introspection and ObjectSpace: Examining Data and Methods at Runtime

Ruby provides many methods for looking into objects at runtime. There are object methods to access instance variables. These methods break encapsulation, so use them with care.

	class C
	  def initialize
	    @ivar = 1

	c = C.new
	c.instance_variables              # => ["@ivar"]
	c.instance_variable_get(:@ivar)   # => 1
	c.instance_variable_set(:@ivar, 3) # => 3
	c.instance_variable_get(:@ivar)    # => 3

The Object#methods method returns an array of instance methods, including singleton methods, defined on the receiver. If the first parameter to methods is false, only the object’s singleton methods are returned.

	class C
	  def inst_method

	  def self.cls_method

	c = C.new

	class << c
	  def singleton_method

	c.methods - Object.methods # => ["inst_method", "singleton_method"]
	c.methods(false) # => ["singleton_method"]

Module#instance_methods returns an array of the class or module’s instance methods. Note that instance_methods is called on the class, while methods is called on an instance. Passing false to instance_methods skips the superclasses’ methods:

	C.instance_methods(false) # => ["inst_method"]

We can also use Metaid’s metaclass method to examine C’s class methods:

	C.metaclass.instance_methods(false) # => ["new", "allocate", "cls_method",

In my experience, most of the value from these methods is in satisfying curiosity. With the exception of a few well-established idioms, there is rarely a need in production code to reflect on an object’s methods. Far more often, these techniques can be used at a console prompt to find methods available on an object—it’s usually quicker than reaching for a reference book:

	Array.instance_methods.grep /sort/ # => ["sort!", "sort", "sort_by"]


ObjectSpace is a module used to interact with Ruby’s object system. It has a few useful module methods that can make low-level hacking easier:

  • Garbage-collection methods: define_finalizer (sets up a callback to be called just before an object is destroyed), undefine_finalizer (removes those call-backs), and garbage_collect (starts garbage collection).

  • _id2ref converts an object’s ID to a reference to that Ruby object.

  • each_object iterates through all objects (or all objects of a certain class) and yields them to a block.

As always, with great power comes great responsibility. Although these methods can be useful, they can also be dangerous. Use them judiciously.

An example of the proper use of ObjectSpace is found in Ruby’s Test::Unit frame-work. This code uses ObjectSpace.each_object to enumerate all classes in existence that inherit from Test::Unit::TestCase:

	test_classes = []
	ObjectSpace.each_object(Class) {
	  | klass |
	  test_classes << klass if (Test::Unit::TestCase > klass)

ObjectSpace, unfortunately, greatly complicates some Ruby virtual machines. In particular, JRuby performance suffers tremendously when ObjectSpace is enabled, because the Ruby interpreter cannot directly examine the JVM’s heap for extant objects. Instead, JRuby must keep track of objects manually, which adds a great amount of overhead. As the same tricks can be achieved with methods like Module.extended and Class.inherited, there are not many cases where ObjectSpace is genuinely necessary.

Delegation with Proxy Classes

Delegation is a form of composition. It is similar to inheritance, except with more conceptual “space” between the objects being composed. Delegation implies a “has-a” rather than an “is-a” relationship. When one object delegates to another, there are two objects in existence, rather than the one object that would result from an inheritance hierarchy.

Delegation is used in ActiveRecord’s associations. The AssociationProxy class delegates most methods (including class) to its target. In this way, associations can be lazily loaded (not loaded until their data is needed) with a completely transparent interface.

DelegateClass and Forwardable

Ruby’s standard library includes facilities for delegation. The simplest is DelegateClass. By inheriting from DelegateClass(klass) and calling super(instance) in the constructor, a class delegates any unknown method calls to the provided instance of the class klass. As an example, consider a Settings class that delegates to a hash:

	require 'delegate'
	class Settings < DelegateClass(Hash)
	  def initialize(options = {})
	    super({:initialized_at => Time.now - 5}.merge(options))

	  def age
	    Time.now - self[:initialized_at]

	settings = Settings.new :use_foo_bar => true
	# Method calls are delegated to the object
	settings[:use_foo_bar] # => true
	settings.age # => 5.000301

The Settings constructor calls super to set the delegated object to a new hash. Note the difference between composition and inheritance: if we had inherited from Hash, then Settings would be a hash; in this case, Settings has a hash and delegates to it. This composition relationship offers increased flexibility, especially when the object to be delegated to may change (a function provided by SimpleDelegator).

The Ruby standard library also includes Forwardable, which provides a simple interface by which individual methods, rather than all undefined methods, can be delegated to another object. ActiveSupport in Rails provides similar functionality with a cleaner API through Module#delegate:

	class User < ActiveRecord::Base
	  belongs_to :person

	  delegate :first_name, :last_name, :phone, :to => :person


In Ruby, all classes are open. Any object or class is fair game to be modified at any time. This gives many opportunities for extending or overriding existing functionality. This extension can be done very cleanly, without modifying the original definitions.

Rails takes advantage of Ruby’s open class system extensively. Opening classes and adding code is referred to as monkeypatching (a term from the Python community). Though it sounds derogatory, this term is used in a decidedly positive light; monkey-patching is, on the whole, seen as an incredibly useful technique. Almost all Rails plugins monkeypatch the Rails core in some way or another.

Disadvantages of monkeypatching

There are two primary disadvantages to monkeypatching. First, the code for one method call may be spread over several files. The foremost example of this is in ActionController’s process method. This method is intercepted by methods in up to five different files during the course of a request. Each of these methods adds another feature: filters, exception rescue, components, and session management. The end result is a net gain: the benefit gained by separating each functional component into a separate file outweighs the inflated call stack.

Another consequence of the functionality being spread around is that it can be difficult to properly document a method. Because the function of the process method can change depending on which code has been loaded, there is no good place to document what each of the methods is adding. This problem exists because the actual identity of the process method changes as the methods are chained together.

Adding Functionality to Existing Methods

Because Rails encourages the philosophy of separation of concerns, you often will have the need to extend the functionality of existing code. Many times you will want to “patch” a feature onto an existing function without disturbing that function’s code. Your addition may not be directly related to the function’s original purpose: it may add authentication, logging, or some other important cross-cutting concern.

We will examine several approaches to the problem of cross-cutting concerns, and explain the one (method chaining) that has acquired the most momentum in the Ruby and Rails communities.


In traditional object-oriented programming, a class can be extended by inheriting from it and changing its data or behavior. This paradigm works for many purposes, but it has drawbacks:

  • The changes you want to make may be small, in which case setting up a new class may be overly complex. Each new class in an inheritance hierarchy adds to the mental overhead required to understand the code.

  • You may need to make a series of related changes to several otherwise-unrelated classes. Subclassing each one individually would be overkill and would separate functionality that should be kept together.

  • The class may already be in use throughout an application, and you want to change its behavior globally.

  • You may want to add or remove a feature at runtime, and have it take effect globally. (We will explore this technique with a full example later in the chapter.)

In more traditional object-oriented languages, these features would require complex code. Not only would the code be complex, it would be tightly coupled to either the existing code or the code that calls it.

Aspect-oriented programming

Aspect-oriented programming (AOP) is one technique that attempts to solve the issues of cross-cutting concerns. There has been much talk about the applicability of AOP to Ruby, since many of the advantages that AOP provides can already be obtained through metaprogramming. There is a Ruby proposal for cut-based AOP, [11] but it may be months or years before this is incorporated.

In cut-based AOP, cuts are sometimes called "transparent subclasses” because they extend a class’s functionality in a modular way. Cuts act as subclasses but without the need to instantiate the subclass rather than the parent class.

The Ruby Facets library (facets.rubyforge.org) includes a pure-Ruby cut-based AOP library. http://facets.rubyforge.org/api/more/classes/Cut.html It has some limitations due to being written purely in Ruby, but the usage is fairly clean:

	class Person
	  def say_hi
	    puts "Hello!"

	cut :Tracer < Person do
	  def say_hi
	    puts "Before method"
	    puts "After method"

	# >> Before method
	# >> Hello!
	# >> After method

Here we see that the Tracer cut is a transparent subclass: when we create an instance of Person, it is affected by Tracer without having to know about Tracer. We can also change Person#say_hi without disrupting our cut.

For whatever reason, Ruby AOP techniques have not taken off. We will now introduce the standard way to deal with separation of concerns in Ruby.

Method chaining

The standard Ruby solution to this problem is method chaining: aliasing an existing method to a new name and overwriting its old definition with a new body. This new body usually calls the old method definition by referring to the aliased name (the equivalent of calling super in an inherited overriden method). The effect is that a feature can be patched around an existing method. Due to Ruby’s open class nature, features can be added to almost any code from anywhere. Needless to say, this must be done wisely so as to retain clarity.

There is a standard Ruby idiom for chaining methods. Assume we have some library code that grabs a Person object from across the network:

	class Person
	  def refresh
	    # (get data from server)

This operation takes quite a while, and we would like to time it and log the results. Leveraging Ruby’s open classes, we can just open up the Person class again and monkeypatch the logging code into refresh:

	class Person
	  def refresh_with_timing
	    start_time = Time.now.to_f
	    retval = refresh_without_timing
	    end_time = Time.now.to_f
	    logger.info "Refresh: #{"%.3f" % (end_time-start_time)} s."
	  alias_method :refresh_without_timing, :refresh
	  alias_method :refresh, :refresh_with_timing

We can put this code in a separate file (perhaps alongside other timing code), and, as long as we require it after the original definition of refresh, the timing code will be properly added around the original method call. This aids in separation of concerns because we can separate code into different files based on its functional concern, not necessarily based on the area that it modifies.

The two alias_method calls patch around the original call to refresh, adding our timing code. The first call aliases the original method as refresh_without_timing (giving us a name by which to call the original method from refresh_with_timing); the second method points refresh at our new method.

This paradigm of using a two alias_method calls to add a feature is common enough that it has a name in Rails: alias_method_chain. It takes two arguments: the name of the original method and the name of the feature.

Using alias_method_chain, we can now collapse the two alias_method calls into one simple line:

	alias_method_chain :refresh, :timing


Monkeypatching affords us a lot of power, but it pollutes the namespace of the patched class. Things can often be made cleaner by modulizing the additions and inserting the module in the class’s lookup chain. Tobias Lütke’s Active Merchant Rails plugin uses this approach for the view helpers. First, a module is created with the helper method:

	module ActiveMerchant
	  module Billing
	    module Integrations
	      module ActionViewHelper
	        def payment_service_for(order, account, options = {}, &proc)

Then, in the plugin’s init.rb script, the module is included in ActionView::Base:

	require 'active_merchant/billing/integrations/action_view_helper' 

It certainly would be simpler in code to directly open ActionView::Base and add the method, but this has the advantage of modularity. All Active Merchant code is contained within the ActiveMerchant module.

There is one caveat to this approach. Because any included modules are searched for methods after the class’s own methods are searched, you cannot directly overwrite a class’s methods by including a module:

	module M
	  def test_method
	    "Test from M"

	class C
	  def test_method
	    "Test from C"

	C.send(:include, M)
	C.new.test_method # => "Test from C"

Instead, you should create a new name in the module and use alias_method_chain:

	module M
	  def test_method_with_module
	    "Test from M"

	class C
	  def test_method
	    "Test from C"

	# for a plugin, these two lines would go in init.rb
	C.send(:include, M)
	C.class_eval { alias_method_chain :test_method, :module }

	C.new.test_method # => "Test from M"

Functional Programming

The paradigm of functional programming focuses on values rather than the side effects of evaluation. In contrast to imperative programming, the functional style deals with the values of expressions in a mathematical sense. Function application and composition are first-class concepts, and mutable state (although it obviously exists at a low level) is abstracted away from the programmer.

This is a somewhat confusing concept, and it is often unfamiliar even to experienced programmers. The best parallels are drawn from mathematics, from which functional programming is derived.

Consider the mathematical equation x = 3. The equals sign in that expression indicates equivalence: "x is equal to 3.” On the contrary, the Ruby statement x = 3 is of a completely different nature. That equals sign denotes assignment: “assign 3 to x.” In a functional programming language, equals usually denotes equality rather than assignment. The key difference here is that functional programming languages specify what is to be calculated; imperative programming languages tend to specify how to calculate it.

Higher-Order Functions

The cornerstone of functional programming, of course, is functions. The primary way that the functional paradigm influences mainstream Ruby programming is in the use of higher-order functions (also called first-class functions, though these two terms are not strictly equivalent). Higher-order functions are functions that operate on other functions. Higher-order functions usually either take one or more functions as an argument or return a function.

Ruby supports functions as mostly first-class objects; they can be created, manipulated, passed, returned, and called. Anonymous functions are represented as Proc objects, created with Proc.new or Kernel#lambda:

	add = lambda{|a,b| a + b}
	add.class # => Proc
	add.arity # => 2

	# call a Proc with Proc#call
	add.call(1,2) # => 3

	# alternate syntax
	add[1,2] # => 3

The most common use for blocks in Ruby is in conjunction with iterators. Many programmers who come to Ruby from other, more imperative-style languages start out writing code like this:

	collection = (1..10).to_a
	for x in collection
	  puts x

The more Ruby-like way to express this is using an iterator, Array#each, and passing it a block. This is second nature to seasoned Ruby programmers:

	collection.each {|x| puts x}

This method is equivalent to creating a Proc object and passing it to each:

	print_me = lambda{|x| puts x}

All of this is to show that functions are first-class objects and can be treated as any other object.


Ruby’s Enumerable module provides several convenience methods to be mixed in to classes that are “enumerable,” or can be iterated over. These methods rely on an each instance method, and optionally the <=> (comparison or “spaceship”) method. Enumerable’s methods fall into several categories.


These represent properties of a collection that may be true or false.


Returns true if the given block evaluates to true for all items in the collection.


Returns true if the given block evaluates to true for any item in the collection.

include?(x), member?(x)

Returns true if x is a member of the collection.


These methods return a subset of the items in the collection.

detect, find

Returns the first item in the collection for which the block evaluates to true,or nil if no such item was found.

select, find_all

Returns an array of all items in the collection for which the block evaluates to true.


Returns an array of all items in the collection for which the block evaluates to false.


Returns an array of all items in the collection for which x === item is true. This usage is equivalent to select{|item| x === item}.


These methods transform a collection into another collection by one of several rules.

map, collect

Returns an array consisting of the result of the given block being applied to each element in turn.


Equivalent to [select(&block), reject(&block)].


Returns a new array of the elements in this collection, sorted by either the given block (treated as the <=> method) or the elements’ own <=> method.


Like sort, but yields to the given block to obtain the values on which to sort. As array comparison is performed in element order, you can sort on multiple fields with person.sort_by{|p| [p.city, p.name]}. Internally, sort_by performs a Schwartzian transform, so it is more efficient than sort when the block is expensive to compute.


Returns an array of tuples, built up from one element each from self and others:

	puts [1,2,3].zip([4,5,6],[7,8,9]).inspect
	# >> [[1, 4, 7], [2, 5, 8], [3, 6, 9]]

When the collections are all of the same size, zip(*others) is equivalent to ([self]+others).transpose:

	puts [[1,2,3],[4,5,6],[7,8,9]].transpose.inspect
	# >> [[1, 4, 7], [2, 5, 8], [3, 6, 9]]

When a block is given, it is executed once for each item in the resulting array:

	[1,2,3].zip([4,5,6],[7,8,9]) {|x| puts x.inspect}
	# >> [1, 4, 7]
	# >> [2, 5, 8]
	# >> [3, 6, 9]


These methods aggregate or summarize the data.


Folds an operation across a collection. Initially, yields an accumulator (initial provides the first value) and the first object to the block. The return value is used as the accumulator for the next iteration. Collection sum is often defined thus:

	module Enumerable
	  def sum
		inject(0){|total, x| total + x}

If no initial value is given, the first iteration yields the first two items.


Returns the maximum value in the collection, as mined by the same logic as the sort method.


Like max, but returns the minimum value in the collection.



Like each, but also yields the 0-based index of each element.

entries, to_a

Pushes each element in turn onto an array, then returns the array.

The Enumerable methods are fun, and you can usually find a customized method to do exactly what you are looking for, no matter how obscure. If these methods fail you, visit Ruby Facets (http://facets.rubyforge.org) for some inspiration.


Ruby has yet another little-known trick up its sleeve, and that is Enumerator from the standard library. (As it is in the standard library and not the core language, you must require "enumerator" to use it.)

Enumerable provides many iterators that can be used on any enumerable object, but it has one limitation: all of the iterators are based on the each instance method. If you want to use some iterator other than each as the basis for map, inject, or any of the other functions in Enumerable, you can use Enumerator as a bridge.

The signature of Enumerator.new is Enumerator.new(obj, method,*args), where obj is the object to enumerate over, method is the base iterator, and args are any arguments that the iterator receives. As an example, you could write a map_with_index function (a version of map that passes the object and its index to the given block) with the following code:

	require "enumerator"
	module Enumerable
	  def map_with_index &b

	puts ("a".."f").map_with_index{|letter, i| [letter, i]}.inspect
	# >> [["a", 0], ["b", 1], ["c", 2], ["d", 3], ["e", 4], ["f", 5]]

The enum_for method returns an Enumerator object whose each method functions like the each_with_index method of the original object. That Enumerator object has already been extended with the instance methods from Enumerable, so we can just call map on it, passing the given block.

Enumerator also adds some convenience methods to Enumerable, which are useful to have. Enumerable#each_slice(n) iterates over slices of the array, n-at-a-time:

	(1..10).each_slice(3){|slice| puts slice.inspect}
	# >> [1, 2, 3]
	# >> [4, 5, 6]
	# >> [7, 8, 9]
	# >> [10]

Similarly, Enumerable#each_cons(n) moves a “sliding window” of size n over the col-lection, one at a time:

	(1..10).each_cons(3){|slice| puts slice.inspect}
	# >> [1, 2, 3]
	# >> [2, 3, 4]
	# >> [3, 4, 5]
	# >> [4, 5, 6]
	# >> [5, 6, 7]
	# >> [6, 7, 8]
	# >> [7, 8, 9]
	# >> [8, 9, 10]

Enumeration is getting a facelift in Ruby 1.9. Enumerator is becoming part of the core language. In addition, iterators return an Enumerator object automatically if they are not given a block. In Ruby 1.8, you would usually do the following to map over the values of a hash:

	hash.values.map{|value| ... }

This takes the hash, builds an array of values, and maps over that array. To remove the intermediate step, you could use an Enumerator:

	hash.enum_for(:each_value).map{|value| ... }

That way, we have a small Enumerator object whose each method behaves just as hash’s each_value method does. This is preferable to creating a potentially large array and releasing it moments later. In Ruby 1.9, this is the default behavior if the iterator is not given a block. This simplifies our code:

	hash.each_value.map{|value| ... }


Runtime Feature Changes

This example ties together several of the techniques we have seen in this chapter. We return to the Person example, where we want to time several expensive methods:

	class Person
	  def refresh
	    # ... 

	  def dup 
	    # ... 

In order to deploy this to a production environment, we may not want to leave our timing code in place all of the time because of overhead. However, we probably want to have the option to enable it when debugging. We will develop code that allows us to add and remove features (in this case, timing code) at runtime without touching the original source.

First, we set up methods wrapping each of our expensive methods with timing commands. As usual, we do this by monkeypatching the timing methods into Person from another file to separate the timing code from the actual model logic: [12].

	class Person
	  TIMED_METHODS = [:refresh, :dup]
	  TIMED_METHODS.each do |method|
	    # set up _without_timing alias of original method
	    alias_method :"#{method}_without_timing", method

	    # set up _with_timing method that wraps the original in timing code
	    define_method :"#{method}_with_timing" do
	      start_time = Time.now.to_f
	      returning(self.send(:"#{method}_without_timing")) do
	        end_time = Time.now.to_f

	        puts "#{method}: #{"%.3f" % (end_time-start_time)} s."

We add singleton methods to Person to enable or disable tracing:

	class << Person
	  def start_trace
	    TIMED_METHODS.each do |method|
	      alias_method method, :"#{method}_with_timing"

	  def end_trace
	    TIMED_METHODS.each do |method|
	      alias_method method, :"#{method}_without_timing"

To enable tracing, we wrap each method call in the timed method call. To disable it, we simply point the method call back to the original method (which is now only accessible by its _without_timing alias).

To use these additions, we simply call the Person.trace method:

	p = Person.new
	p.refresh # => (...)

	p.refresh # => (...)
	# -> refresh: 0.500 s.

	p.refresh # => (...)

Now that we have the ability to add and remove the timing code during execution, we can expose this through our application; we could give the administrator or developer an interface to trace all or specified functions without restarting the application. This approach has several advantages over adding logging code to each function separately:

  • The original code is untouched; it can be changed or upgraded without affecting the tracing code.

  • When tracing is disabled, the code performs exactly as it did before tracing; the tracing code is invisible in stack traces. There is no performance overhead when tracing is disabled.

However, there are some disadvantages to writing what is essentially self-modifying code:

  • Tracing is only available at the function level. More detailed tracing would require changing or patching the original code. Rails code tends to address this by making methods small and their names descriptive.

  • Stack traces do become more complicated when tracing is enabled. With tracing, a stack trace into the Person#refresh method would have an extra level: #refresh_with_timing, then #refresh_without_timing (the original method).

  • This approach may break when using more than one application server, as the functions are aliased in-memory. The changes will not propagate between servers, and will revert when the server process is restarted. However, this can actually be a feature in production; typically, you will not want to profile all traffic in a high-traffic production environment, but only a subset of it.

Rails Routing Code

The Rails routing code is perhaps some of the most conceptually difficult code in Rails. The code faces several constraints:

  • Path segments may capture multiple parts of the URL:

    — Controllers may be namespaced, so the route ":controller/:action/:id" can match the URL "/store/product/edit/15", with the controller being "store/product".

    — Routes may contain path_info segments that destructure multiple URL seg-ments: the route "page/*path_info" can match the URL "/page/products/ top_products/15", with the path_info segment capturing the remainder of the URL.

  • Routes can be restricted by conditions that must be met in order for the route to match.

  • The routing system must be bidirectional; it is run forward to recognize routes and in reverse to generate them.

  • Route recognition must be fast because it is run once per HTTP request. Route generation must be lightning fast because it may be run tens of times per HTTP request (once per outgoing link) when generating a page.


Michael Koziarski’s new routing_optimisation code in Rails 2.0 (actionpack/lib/action_controller/routing_optimisation.rb) addresses the complexity of Rails routing. This new code optimizes the simple case of generation of named routes with no extra :requirements.

Because of the speed needed in both generation and recognition, the routing code modifies itself at runtime. The ActionController::Routing::Route class represents a single route (one entry in config/routes.rb). The Route#recognize method rewrites itself:

	class Route
	  def recognize(path, environment={})
	    recognize path, environment

The recognize method calls write_recognition, which processes the route logic and creates a compiled version of the route. The write_recognition method then over-writes the definition of recognize with that definition. The last line in the original recognize method then calls recognize (which has been replaced by the compiled version) with the original arguments. This way, the route is compiled on the first call to recognize. Any subsequent calls use the compiled version, rather than having to reparse the routing DSL and go through the routing logic again.

Here is the body of the write_recognition method:

	def write_recognition
	  # Create an if structure to extract the params from a match if it occurs.
	  body = "params = parameter_shell.dup\n#{recognition_extraction * "\n"}\nparams" 
	  body = "if #{recognition_conditions.join(" && ")}\n#{body}\nend"

	  # Build the method declaration and compile it
	  method_decl = "def recognize(path, env={})\n#{body}\nend"
	  instance_eval method_decl, "generated code (#{__FILE__}:#{__LINE__})"

The local variable body is built up with the compiled route code. It is wrapped in a method declaration that overwrites recognize. For the default route:

	map.connect ':controller/:action/:id'

write_recognition generates code looking like this:

	def recognize(path, env={})
	  if (match = /(long regex)/.match(path))
	    params = parameter_shell.dup 
	    params[:controller] = match[1].downcase if match[1]
	    params[:action] = match[2] || "index"
	    params[:id] = match[3] if match[3]

The parameter_shell method returns the default set of parameters associated with the route. This method body simply tests against the regular expression, populating and returning the params hash if the regular expression matches. If there is no match, the method returns nil.

Once this method body is created, it is evaluated in the context of the route using instance_eval. This overwrites that particular route’s recognize method.

Further Reading

Minero AOKI’s Ruby Hacking Guide is an excellent introduction to Ruby’s internals. It is being translated into English at http://rhg.rubyforge.org/.

Eigenclass (http://eigenclass.org/) has several more technical articles on Ruby.

Evil.rb is a library for accessing the internals of Ruby objects. It can change objects’ internal state, traverse and examine the klass and super pointers, change an object’s class, and cause general mayhem. Use with caution. It is available at http:// rubyforge.org/projects/evil/. Mauricio Fernández gives a taste of Evil at http://eigenclass. org/hiki.rb?evil.rb+dl+and+unfreeze.

Jamis Buck has a very detailed exploration of the Rails routing code, as well as several other difficult parts of Rails, at http://weblog.jamisbuck.org/under-the-hood.

One of the easiest-to-understand, most well-architectured pieces of Ruby software I have seen is Capistrano 2, also developed by Jamis Buck. Not only does Capistrano have a very clean API, it is extremely well built from the bottom up. If you haven’t been under Capistrano’s hood, it will be well worth your time. The source is available via Subversion from http://svn.rubyonrails.org/rails/tools/capistrano/.

Mark Jason Dominus’s book Higher-Order Perl (Morgan Kaufmann Publishers) was revolutionary in introducing functional programming concepts into Perl. When Higher-Order Perl was released in 2005, Perl was a language not typically known for its functional programming support. Most of the examples in the book can be translated fairly readily into Ruby; this is a good exercise if you are familiar with Perl. James Edward Gray II has written up his version in his “Higher-Order Ruby” series, at http://blog.grayproductions.net/categories/higherorder_ruby.

The Ruby Programming Language, by David Flanagan and Yukihiro Matsumoto (O’Reilly), is a book covering both Ruby 1.8 and 1.9. It is due out in January 2008. The book includes a section on functional programming techniques in Ruby.

[3] If that weren’t confusing enough, the Class object has class Class as well.

[4] Except immediate objects (Fixnums, symbols, true, false, and nil); we’ll get to those later.

[5] Ruby often co-opts Smalltalk’s message-passing terminology: when a method is called, it is said that one is sending a message. The receiver is the object that the message is sent to.

[6] ICLASS is Mauricio Fernández’s term for these proxy classes. They have no official name but are of type T_ICLASS in the Ruby source.

[8] There are also constants, but they shouldn’t vary. (They can, but Ruby will complain.)

[9] Kernel#proc is another name for Kernel#lambda, but its usage is deprecated.

[12] This code sample uses variable interpolation inside a symbol literal. Because the symbol is defined using a double-quoted string, variable interpolation is just as valid as in any other double-quoted string: the symbol :”sym#{2+2}" is the same symbol as :sym4

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