INSTALL | TUTORIAL | EXAMPLES |
Affect | əˈfɛkt | verb [with object] have an effect on; make a difference to.
Affect is a tiny Ruby gem providing a way to isolate and handle side-effects in functional programs. Affect implements algebraic effects in Ruby, but can also be used to implement patterns that are orthogonal to object-oriented programming, such as inversion of control and dependency injection.
In addition, Affect includes an alternative implementation of algebraic effects
using Ruby fibers, as well as an implementation of delimited continuations using
callcc
(currently deprecated).
Note: Affect does not pretend to be a complete, theoretically correct implementation of algebraic effects. Affect concentrates on the idea of effect contexts. It does not deal with continuations, asynchrony, or any other concurrency constructs.
# In your Gemfile
gem 'affect'
Or install it manually, you know the drill.
Algebraic effects introduces the concept of effect handlers, little pieces of
code that are provided by the caller, and invoked by the callee using a uniform
interface. An example of algebraic effects might be logging. Normally, if we
wanted to log a certain message to STDOUT
or to a file, we would do the
following:
def mul(x, y)
# assume LOG is a global logger object
LOG.info("called with #{x}, #{y}")
x * y
end
puts "Result: #{ mul(2, 3) }"
The act of logging is a side-effect of our computation. We need to have a global
LOG
object, and we cannot test the functioning of the mul
method in
isolation. What if we wanted to be able to plug-in a custom logger, or intercept
calls to the logger?
Affect provides a solution for such problems by implementing a uniform, composable interface for isolating and handling side effects:
require 'affect'
def mul(x, y)
# assume LOG is a global logger object
Affect.perform :log, "called with #{x}, #{y}"
x * y
end
Affect.capture(
log: { |message| puts "#{Time.now} #{message} (this is a log message)" }
) {
puts "Result: #{ mul(2, 3) }"
In the example above, we replace the call to LOG.info
with the performance of
an intent to log a message. When the intent is passed to Affect
, the
corresponding handler is called in order to perform the effect.
In essence, by separating the performance of side effects into effect intents,
and effect handlers, we have separated the what from the how. The mul
method
is no longer concerned with how to log the message it needs to log. There's no
hardbaked reference to a LOG
object, and no logging API to follow. Instead,
the intent to log a message is passed on to Affect, which in turn runs the
correct handler that actually does the logging.
In Affect, effects are performed and handled using an effect context. The effect context has one or more effect handlers, and is then used to run code that performs effects, handling effect intents by routing them to the correct handler.
Effect contexts are defined using either Affect()
or the shorthand
Affect.capture
:
ctx = Affect(log: -> msg { log_msg(msg) })
ctx.capture { do_something }
# or
Affect.capture(log: -> msg { log_msg(msg) }) { do_something }
The Affect.capture
method can be called in different manners:
Affect.capture(handler_hash) { body }
Affect.capture(handler_proc) { body }
Affect.capture(body, handler_hash)
Affect.capture(body, handler_proc)
... where body
is the code to be executed, handler_hash
is a hash of effect
handling procs, and handler_proc
is a default effect handling proc.
Effect contexts can be nested. When an effect context does not know how to handle a certain effect intent, it passes it on to the parent effect context. If no handler has been found for the effect intent, an error is raised:
# First effect context
Affect.capture(log: ->(msg) { LOG.info(msg) }) {
Affect.perform :log, 'starting'
# Second effect context
Affect.capture(log: ->(msg) { }) {
Affect.perform :log, 'this message will not be logged'
}
Affect.perform :log, 'stopping'
Affect.perform :foo # raises an error, as no handler is given for :foo
}
Effect handlers map different effects to a proc or a callable object. When an effect is performed, Affect will try to find the relevant effect handler by looking at its signature (given as the first argument), and then matching first by value, then by class. Thus, the effect signature can be either a value, or a class (normally used when creating intent classes).
The simplest, most idiomatic way to define effect handlers is to use symbols as effect signatures:
Affect(log: -> msg { ... }, ask: -> { ... })
A catch-all handler can be defined by calling Affect()
with a block:
Affect do |eff, *args|
case eff
when :log
...
when :ask
...
end
end
Note that when using a catch-all handler, no error will be raised for unhandled effects.
Side effects are performed by calling Affect.perform
or simply
Affect.<intent>
along with one or more parameters:
Affect.perform :foo
# or:
Affect.foo
Any parameters will be passed along to the effect handler:
Affect.perform :log, 'my message'
Effects intents can be represented using any Ruby object, but in a relatively complex application might best be represented using classes or structs:
LogIntent = Struct.new(:msg)
Affect.perform LogIntent.new('my message')
When using symbols as effect signatures, Affect provides a shorthand way to
perform effects by calling methods directly on the Affect
module:
Affect.log('my message')
In addition to isolating side-effects, Affect can be used for other purposes:
Affect can also be used for dependency injection. Dependencies can be injected by providing effect handlers:
Affect.on(:db) {
get_db_connection
}.() {
process_users(Affect.db.query('select * from users'))
}
This is especially useful for testing purposes as described below:
One particular benefit of using Affect is the way it facilitates testing. When mutable state and side-effects are pulled out of methods and into effect handlers, testing becomes much easier. Side effects can be mocked or tested in isolation, and dependencies provided through effect handlers can also be mocked. The following section includes an example of testing with algebraic effects.
Algebraic effects have yet to be adopted by any widely used programming language, and they remain a largely theoretical subject in computer science. Their advantages are still to be proven in actual usage. We might discover that they're completely inadequate as a solution for managing side-effects, or we might discover new techniques to be used in conjunction with algebraic effects.
One important principle to keep in mind is that in order to make the best of algebraic effects, effect handlers need to be pushed to the outside of your code. In most cases, the effect context will be defined in the entry-point of your program, rather than somewhere on the inside.
Imagine a program that counts the occurences of a user-defined pattern in a given text file:
require 'affect'
def pattern_count(pattern)
total_count = 0
found_count = 0
while (line = Affect.gets)
total_count += 1
found_count += 1 if line =~ pattern
end
Affect.log "found #{found_count} occurrences in #{total_count} lines"
found_count
end
Affect(
gets: -> { Kernel.gets },
log: -> { |msg| STDERR << "#{Time.now} #{msg}" }
).capture {
pattern = /#{ARGV[0]}/
count = pattern_count(pattern)
puts count
}
In the above example, the pattern_count
method, which does the "hard work",
communicates with the outside world through Affect in order to:
- read a line after line from some input stream
- log an informational message
Note that pattern_count
does not deal directly with I/O. It does so
exclusively through Affect. Testing the method would be much simpler:
require 'minitest'
require 'affect'
class PatternCountTest < Minitest::Test
def test_correct_count
text = StringIO.new("foo\nbar")
Affect(
gets: -> { text.gets },
log: -> |msg| {} # ignore
.capture {
count = pattern_count(/foo/)
assert_equal(1, count)
}
end
end
Affect is a very small library designed to do very little. If you find it compelling, have encountered any problems using it, or have any suggestions for improvements, please feel free to contribute issues or pull requests.