Ruby Functional Programming

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Ruby Functional Programming

Functional Programming by Wikipidia:
“Functional programming is a programming
paradigm that treats computation as the evaluation
of mathematical functions and avoids state and
mutable data". In other words, functional
programming promotes code with no side effects, no
change of value in variables. It oposes to imperative
programming, which enfatizes change of state”.

What this means?
● No mutable data (no side effect).
● No state (no implicit, hidden state).
Once assigned (value binding), a variable (a symbol) does not change its value.
All state is bad? No, hidden, implicit state is bad.
Functional programming do not eliminate state, it just make it visible and explicit (at
least when programmers want it to be).
● Functions are pure functions in the mathematical sense: their output depend only
in their inputs, there is not “environment”.
● Same result returned by functions called with the same inputs.

What are the advantages?
● Cleaner code: "variables" are not modified once defined, so we don't have to
follow the change of state to comprehend what a function, a, method, a class, a
whole project works.
● Referential transparency: Expressions can be replaced by its values. If we call a
function with the same parameters, we know for sure the output will be the same
(there is no state anywhere that would change it).
There is a reason for which Einstein defined insanity as "doing the same thing
over and over again and expecting different results".

Advantages enabled by referential transparence
● Memoization
○ Cache results for previous function calls.
● Idempotence
○ Same results regardless how many times you call a function.
● Modularization
○ We have no state that pervades the whole code, so we build our project with
small, black boxes that we tie together, so it promotes bottom-up
programming.
● Ease of debugging
○ Functions are isolated, they only depend on their input and their output, so
they are very easy to debug.

Advantages enabled by referential
transparence
● Parallelization
○ Functions calls are independent.
○ We can parallelize in different process/CPUs/computers/…
We can execute func1 and func2 in paralell because a won’t be modified.
result = func1(a, b) + func2(a, c)

Advantages enabled by referential
transparence
● Concurrence
a. With no shared data, concurrence gets a lot simpler:
i. No semaphores.
ii. No monitors.
iii. No locks.
iv. No race-conditions.
v. No dead-locks.

Ruby is an imperative programming language.
As a Ruby programmer why uses functional
programming in Ruby?
Ruby is not a functional language but have a lot of features that enables us to applies
functional principles in the development, turning our code more elegant, concise,
maintanable, easier to understand and test.

Don’t Update, Create - Strings
name = “Geison”
name = “#{name} Flores”
FIRSTNAME = “Geison”
LASTNAME = “#{name} Flores”
NAME = “#{FIRSTNAME} #{LASTNAME}”

Don’t Update, Create - Arrays
years = [2001, 2002]
years << 2003
years += [2004, 2005]
years # [2001, 2002, 2003, 2004, 2005]
YEARS = [2001, 2001]
ALL_YEARS = YEARS + [2003] + [2004, 2005]

Don’t Update, Create - Hashes
ages = {“John” => 30}
ages[“Mary”] = 28
ages # {“John” => 30, “Mary” => 28}
AGES = {“John” => 30}
ALL_AGES = AGES.merge(“Mary” => 28)

Immutable Objects
● An OO pattern that was originated in FP world.
● When changing a data structure, don’t modify in place but create a new object.
● In Ruby this is tipically the dafault. Methods that don’t follow this principal are
assumed “dangerous” and are tipically marked with ‘!’.
○ name.reverse => returns a new string that contaings the reversed name.
○ name.reverse! => replaces the name with reversed value.

Everythings is an expression
if num == "one" then val = 1
elsif num == "two" then val = 2
else then val = 3
end
val = if num == "one" then 1
elsif num == "two" then 2
else 3
end

# a trivial example that adds a loop control structure
# it takes a range and yields the passed block.
def loop(x,&b)
for i in x do
b.call(i)
end
end
# use the above defined method
loop(1..10) do |x|
puts x
end
Higher Order Functions
Functions are higher-order when they can take other functions as arguments, and
return them as results. This is done in Ruby using lambda and block logic.

init-empty + each + push = map
dogs = []
["milu", "rantanplan"].each do |name|
dogs << name.upcase
end
dogs # ["MILU", "RANTANPLAN"]
dogs = ["milu", "rantanplan"].map do |name|
name.upcase
end # ["MILU", "RANTANPLAN"]

init-empty + each + conditional push -> select/reject
dogs = []
["milu", "rantanplan"].each do |name|
if name.size == 4
dogs << name
end
end
dogs # ["milu"]
dogs = ["milu", "rantanplan"].select do |name|
name.size == 4
end # ["milu"]

initialize + each + accumulate -> inject
length = 0
["milu", "rantanplan"].each do |dog_name|
length += dog_name.length
end
length # 14
length = ["milu", "rantanplan"].inject(0) do |accumulator, dog_name|
accumulator + dog_name.length
end # 14
# In this particular case, when there is a simple operation between accumulator and element, we
don't need to write the block, just pass the symbol of the binary operation and the initial
value:
length = ["milu", "rantanplan"].map(&:length).inject(0, :+) # 14

init-empty + upto + merge arrays -> zip
xs = [1, 2, 3]
ys = [:a, :b, :c]
output = []
0.upto(xs.length - 1).each do |idx|
output << [xs[idx], ys[idx]]
end
output # [[1, :a], [2, :b], [3, :c]]
xs = [1, 2, 3]
ys = [:a, :b, :c]
output = xs.zip(ys) # [[1, :a], [2, :b], [3, :c]]

Currying and Partial Functions
Higher-order functions enable Currying, which the ability to take a function that accepts n
parameters and turns it into a composition of n functions each of them take 1 parameter. A
direct use of currying is the Partial Functions where if you have a function that accepts n
parameters then you can generate from it one of more functions with some parameter values
already filled in.
plus = lambda {|a,b| a + b} # defining a proc that sums 2 numbers
plus.(3,5) #=> 8
# curring calling partial function by supplying the first parameters with value 1
plus_one = plus.curry.(1)
# I can use the new proc as normal
plus_one.(5) #=> 6

Eager vs Lazy Evaluation
● Eager evaluation: expressions are calculated at the moment that variables is assined,
function called...
● Lazy evaluation: delays the evaluation of the expression until it is needed.
○ Memory efficient: no memory used to store complete structures.
○ CPU efficient: no need to calculate the complete result before returning.
○ Laziness is not a requisite for FP, but it is a strategy that fits nicely on the
paradigm(Haskell).
Ruby uses eager evaluation (but short-circuits && or ||).
Ruby blocks are a mechanism for lazy evaluation.
Ruby arrays are not lazy, use enumarators when necessary.
In Ruby 2.0:
(0..Float::INFINITY).lazy.map { |x| 2*x }.take(5).to_a # [0 2, 4, 6, 8]

Recursion
Looping by calling a function from within itself. When you don’t have access to mutable data,
recursion is used to build up and chain data construction. This is because looping is not a
functional concept, as it requires variables to be passed around to store the state of the loop at a
given time.
● Purely functional languages have no imperative for-loops, so they use recursion a lot.
● If every recursion created an stack, it would blow up very soon.
● Tail-call optimization (TCO) avoids creating a new stack when the last call in a recursion is
the function itself.
● TCO is optional in Ruby: you cannot rely on it in your code if you want to use it everywhere.
● Unfortunarely following recursion style in Ruby has it’s own tax: Performance.

Recursion
To enable TCO in MRI-1.9:
Simple factorial example:
RubyVM::InstructionSequence.compile_option = {
:tailcall_optimization => true,
:trace_instruction => false,
}
def factorial_tco(n, acc=1)
n < 1 ? acc : factorial_tco(n-1, n*acc)
end

FP in OOP?
It is possible do FP in OOP? Yes it is!
● OOP is orthogonal to FP.
● Well, at least in theory, because:
○ Typical OOP tends to emphasize change of state in objects.
○ Typical OOP mixes the concepts of identity and state.
○ Mixture of data and code raises both conceptual and practical problems.
● OOP functional languages: Scala, F#, ...

A Pratical Example
Exercise: "What's the sum of the first 10 natural number whose square value is divisible by 5?"
Imperative:
Functional:
n, num_elements, sum = 1, 0, 0
while num_elements < 10
if n**2 % 5 == 0
sum += n
num_elements += 1
end
n += 1
end
sum #275
Integer::natural.select { |x| x**2 % 5 == 0 }.take(10).inject(:+) #275

The last advice
Learn at least one functional language, it will open your mind to a new paradigm
becoming you a better programmer.
Some Functional Languages:
● Haskell
● ML (Standard ML, Objective Caml, ...)
● Scheme
● Erlang
● Scala
● Closure
● F#

Conclusion
● As you can tell, Ruby helps you write in functional style but it doesn’t force you to
it.
● Writing in functional style enhances your code and makes it more self
documented. Actually it will make it more thread-safe also.
● The main support for FP in ruby comes from the use of blocks and lambdas, also
from the fact that everything is evaluated as an expression.
● Ruby still lack an important aspect of FP: Pattern Matching and Lazy Evaluation.
● There should be more work on tail recursion optimization, to encourage
developers to use recursion.
● Any other thoughts?

References
● http://en.wikipedia.org/wiki/Functional_programming
● http://www.cse.chalmers.se/~rjmh/Papers/whyfp.pdf
● http://khelll.com/blog/ruby/ruby-and-functional-programming/
● http://www.youtube.com/watch?v=FITJMJjASUs
● http://clojure.org/
● http://www.defmacro.org/ramblings/fp.html

Contact me
● Email:
○ geisonfgf@gmail.com
● Skype
○ geisonfgf
● Facebook
○ http://www.facebook.com/geisonfgf
● Twitter
○ http://www.twitter.com/geisonfgf

Ruby Functional Programming

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