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Introduction to Functional Programming
1. An Introduction to Functional Programming
Andreas Pauley – @apauley
Pattern Matched Technologies
Lambda Luminaries @lambdaluminary
September 2, 2013
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 1 / 58
2. Pattern Matched Technologies
Developing financial applications in Erlang.
http://www.patternmatched.com/
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 2 / 58
3. Lambda Luminaries – @lambdaluminary
Local functional programming user group
We meet once a month, on the second Monday of the month.
http://www.meetup.com/lambda-luminaries/
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 3 / 58
4. Introduction
Table of Contents
1 Introduction
2 Definition of Functional Programming
3 Function Recap
4 Common FP Idioms
Recursion
Pattern Matching
Higher-order Functions
5 Higher-order Functions and Lists
6 Advantages of Functional Programming
7 Disdvantages of Functional Programming
8 Companies using Functional Programming
9 Where do we go from here?
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 4 / 58
5. Introduction
A word from the wise
“ No matter what language you work in, programming in
a functional style provides benefits. You should do it
whenever it is convenient, and you should think hard
about the decision when it isn’t convenient. ”
— John Carmack, ID Software [2]
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 5 / 58
6. Introduction
Quake
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 6 / 58
7. Introduction
A Few Functional Programming Languages
Haskell Strong focus on functional purity. Lazy evaluation.
Advanced static type system. Native-code compiler.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 7 / 58
8. Introduction
A Few Functional Programming Languages
Haskell Strong focus on functional purity. Lazy evaluation.
Advanced static type system. Native-code compiler.
Erlang Focused around concurrency and distributed programming.
Strict evaluation. Dynamic typing. Runs on the BEAM VM.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 7 / 58
9. Introduction
A Few Functional Programming Languages
Haskell Strong focus on functional purity. Lazy evaluation.
Advanced static type system. Native-code compiler.
Erlang Focused around concurrency and distributed programming.
Strict evaluation. Dynamic typing. Runs on the BEAM VM.
Clojure A modern Lisp language. Focus on concurrency. Lazy
evaluation. Dynamic typing. Runs on the JVM.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 7 / 58
10. Introduction
A Few Functional Programming Languages
Haskell Strong focus on functional purity. Lazy evaluation.
Advanced static type system. Native-code compiler.
Erlang Focused around concurrency and distributed programming.
Strict evaluation. Dynamic typing. Runs on the BEAM VM.
Clojure A modern Lisp language. Focus on concurrency. Lazy
evaluation. Dynamic typing. Runs on the JVM.
Scala FP and OO. Strict evaluation by default, but supports lazy
evaluation. Advanced static type system. Runs on the JVM.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 7 / 58
11. Introduction
A Few Functional Programming Languages
Haskell Strong focus on functional purity. Lazy evaluation.
Advanced static type system. Native-code compiler.
Erlang Focused around concurrency and distributed programming.
Strict evaluation. Dynamic typing. Runs on the BEAM VM.
Clojure A modern Lisp language. Focus on concurrency. Lazy
evaluation. Dynamic typing. Runs on the JVM.
Scala FP and OO. Strict evaluation by default, but supports lazy
evaluation. Advanced static type system. Runs on the JVM.
OCaml FP and OO. Part of the ML family. Sometimes claimed to
be “faster than C”. Strict evaluation. Advanced static type
system. Native-code compiler.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 7 / 58
12. Introduction
A Few Functional Programming Languages
Haskell Strong focus on functional purity. Lazy evaluation.
Advanced static type system. Native-code compiler.
Erlang Focused around concurrency and distributed programming.
Strict evaluation. Dynamic typing. Runs on the BEAM VM.
Clojure A modern Lisp language. Focus on concurrency. Lazy
evaluation. Dynamic typing. Runs on the JVM.
Scala FP and OO. Strict evaluation by default, but supports lazy
evaluation. Advanced static type system. Runs on the JVM.
OCaml FP and OO. Part of the ML family. Sometimes claimed to
be “faster than C”. Strict evaluation. Advanced static type
system. Native-code compiler.
F# FP and OO. Based on OCaml. Strict evaluation by default,
but supports lazy evaluation. Advanced static type system.
Runs on the .NET CLR.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 7 / 58
13. Definition of Functional Programming
Table of Contents
1 Introduction
2 Definition of Functional Programming
3 Function Recap
4 Common FP Idioms
Recursion
Pattern Matching
Higher-order Functions
5 Higher-order Functions and Lists
6 Advantages of Functional Programming
7 Disdvantages of Functional Programming
8 Companies using Functional Programming
9 Where do we go from here?
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 8 / 58
14. Definition of Functional Programming
So what exactly is Functional Programming?
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 9 / 58
15. Definition of Functional Programming
Functional Programming, noun:
“ Functional Programming is a list
of things you CAN’T do. ”
[7]
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 10 / 58
16. Definition of Functional Programming
When programming in a functional style/language:
You can’t vary your variables.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 11 / 58
17. Definition of Functional Programming
When programming in a functional style/language:
You can’t vary your variables.
You can’t mutate or change your state.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 11 / 58
18. Definition of Functional Programming
When programming in a functional style/language:
You can’t vary your variables.
You can’t mutate or change your state.
No while/for loops, sorry.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 11 / 58
19. Definition of Functional Programming
When programming in a functional style/language:
You can’t vary your variables.
You can’t mutate or change your state.
No while/for loops, sorry.
You can’t have side-effects.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 11 / 58
20. Definition of Functional Programming
When programming in a functional style/language:
You can’t vary your variables.
You can’t mutate or change your state.
No while/for loops, sorry.
You can’t have side-effects.
You can’t control the order of execution (lazy evaluated languages).
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 11 / 58
21. Definition of Functional Programming
Are you kidding me?
How can anyone program like this???
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 12 / 58
22. Definition of Functional Programming
GOTO 10
This sounds like
“You can’t have GOTO statements”
See Hughes and Dijkstra [1, 3]
Also framed in the negative (you can’t).
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 13 / 58
23. Definition of Functional Programming
GOTO 10
This sounds like
“You can’t have GOTO statements”
See Hughes and Dijkstra [1, 3]
Also framed in the negative (you can’t).
In hindsight we don’t really need GOTO’s.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 13 / 58
24. Definition of Functional Programming
GOTO 10
This sounds like
“You can’t have GOTO statements”
See Hughes and Dijkstra [1, 3]
Also framed in the negative (you can’t).
In hindsight we don’t really need GOTO’s.
In hindsight it is not about what you cannot do.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 13 / 58
25. Definition of Functional Programming
Structured Programming and Functional Programming
Structured Programming introduced subroutines with fixed entry/exit
points (instead of GOTO’s), resulting in improved
modularity.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 14 / 58
26. Definition of Functional Programming
Structured Programming and Functional Programming
Structured Programming introduced subroutines with fixed entry/exit
points (instead of GOTO’s), resulting in improved
modularity.
Functional Programming provides similar important benefits – more about
this later.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 14 / 58
27. Definition of Functional Programming
We need a better definition for Functional Programming.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 15 / 58
28. Definition of Functional Programming
Functional Programming, noun:
“ Functional programming is so called because a program
consists entirely of functions. ”
— John Hughes, Why Functional Programming Matters [1, p. 1]
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 16 / 58
29. Definition of Functional Programming
OK... so what exactly is a function?
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 17 / 58
30. Function Recap
Table of Contents
1 Introduction
2 Definition of Functional Programming
3 Function Recap
4 Common FP Idioms
Recursion
Pattern Matching
Higher-order Functions
5 Higher-order Functions and Lists
6 Advantages of Functional Programming
7 Disdvantages of Functional Programming
8 Companies using Functional Programming
9 Where do we go from here?
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 18 / 58
31. Function Recap
An example function
f (x) = 2x + 3
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 19 / 58
32. Function Recap
Variables in functions
f (x) = 2x + 3
When we evaluate the function:
f (4) = 2 ∗ 4 + 3 = 11
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 20 / 58
33. Function Recap
Variables in functions
f (x) = 2x + 3
When we evaluate the function:
f (4) = 2 ∗ 4 + 3 = 11
The value of x will not change inside the function body.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 20 / 58
34. Function Recap
Variables in functions
f (x) = 2x + 3
When we evaluate the function:
f (4) = 2 ∗ 4 + 3 = 11
The value of x will not change inside the function body.
No x = 4 and later x = 21 in the same function body.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 20 / 58
35. Function Recap
Variables in functions
f (x) = 2x + 3
When we evaluate the function:
f (4) = 2 ∗ 4 + 3 = 11
The value of x will not change inside the function body.
No x = 4 and later x = 21 in the same function body.
Same input, same output. Every time.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 20 / 58
36. Function Recap
Variables in functions
f (x) = 2x + 3
When we evaluate the function:
f (4) = 2 ∗ 4 + 3 = 11
The value of x will not change inside the function body.
No x = 4 and later x = 21 in the same function body.
Same input, same output. Every time.
In other words, we can replace any occurrence of f (4) with 11
(Referential Transparency)
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 20 / 58
37. Function Recap
Functions can call other functions
g(x) = f (x) + 1
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 21 / 58
38. Function Recap
Values are functions
Constant values are just functions with no input parameters
k = 42
def k():
return 42
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 22 / 58
39. Function Recap
Functions can be combined
h(x) = f (g(x))
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 23 / 58
40. Function Recap
Higher-order Functions
Functions can take functions as input and/or return
functions as the result.
h(p, q, x) = p(x) + q(2)
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 24 / 58
41. Function Recap
Higher-order Functions
Functions can take functions as input and/or return
functions as the result.
h(p, q, x) = p(x) + q(2)
h(f , g, 3) = f (3) + g(2)
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 24 / 58
42. Function Recap
Higher-order Functions
The derivative of cos(x) returns another function.
d
dx cos(x) = − sin(x)
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 25 / 58
43. Function Recap
A functional program consists entirely of functions
def main(args):
result = do_something_with_args(args)
print result
def do_something_with_args(args):
return ’-’.join(args[1:])
./justfunctions.py hello functional programming
hello-functional-programming
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 26 / 58
44. Function Recap
A functional program consists entirely of functions
main :: IO()
main = do
args <- getArgs
let result = do_something_with_args args
putStrLn result
do_something_with_args :: [String] -> String
do_something_with_args args = intercalate "-" args
./justfunctions hello functional programming
hello-functional-programming
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 27 / 58
45. Common FP Idioms
Table of Contents
1 Introduction
2 Definition of Functional Programming
3 Function Recap
4 Common FP Idioms
Recursion
Pattern Matching
Higher-order Functions
5 Higher-order Functions and Lists
6 Advantages of Functional Programming
7 Disdvantages of Functional Programming
8 Companies using Functional Programming
9 Where do we go from here?
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 28 / 58
46. Common FP Idioms Recursion
Recursive function: Haskell
doubleAll :: Num a => [a] -> [a]
doubleAll [] = []
doubleAll (x:xs) = x*2 : doubleAll xs
Example use in the interactive interpreter:
Prelude Main> doubleAll [8,2,3]
[16,4,6]
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 29 / 58
47. Common FP Idioms Recursion
Recursive function: Python
def doubleAll(numbers):
if numbers == []:
return []
else:
first = numbers[0]
rest = numbers[1:]
return [first * 2] + doubleAll(rest)
Example use in the interactive interpreter:
>>> doubleAll([8,2,3])
[16, 4, 6]
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 30 / 58
48. Common FP Idioms Recursion
An iterative version in Python
def doubleAll(numbers):
doubled = []
for num in numbers:
doubled.append(num * 2)
return doubled
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 31 / 58
49. Common FP Idioms Pattern Matching
Pattern Matching: Haskell
doubleAll :: Num a => [a] -> [a]
doubleAll [] = []
doubleAll (x:xs) = x*2 : doubleAll xs
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 32 / 58
51. Common FP Idioms Higher-order Functions
Higher-order functions: Haskell
f (x) = 2x + 3
g(x) = f (x) + 1
h(p, q, x) = p(x) + q(2)
f x = (2*x) + 3
g x = (f x) + 1
h :: (Int->Int) -> (Int->Int) -> Int -> Int
h func_a func_b x = (func_a x) + (func_b 2)
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 34 / 58
52. Higher-order Functions and Lists
Table of Contents
1 Introduction
2 Definition of Functional Programming
3 Function Recap
4 Common FP Idioms
Recursion
Pattern Matching
Higher-order Functions
5 Higher-order Functions and Lists
6 Advantages of Functional Programming
7 Disdvantages of Functional Programming
8 Companies using Functional Programming
9 Where do we go from here?
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 35 / 58
53. Higher-order Functions and Lists
3 Basic List Operations
Map Convert each element of a list into some other value.
Example: Convert a list of students to a list of exam scores.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 36 / 58
54. Higher-order Functions and Lists
3 Basic List Operations
Map Convert each element of a list into some other value.
Example: Convert a list of students to a list of exam scores.
Filter Get a subset of a list based on some condition. Example:
Filter the entire list of students down to only those that
passed the exam.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 36 / 58
55. Higher-order Functions and Lists
3 Basic List Operations
Map Convert each element of a list into some other value.
Example: Convert a list of students to a list of exam scores.
Filter Get a subset of a list based on some condition. Example:
Filter the entire list of students down to only those that
passed the exam.
Fold Reduce a list of items to a single value. Example: Reduce
the list of students to a single string of all names.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 36 / 58
56. Higher-order Functions and Lists
Map
doubleAll :: Num a => [a] -> [a]
doubleAll [] = []
doubleAll (x:xs) = x*2 : doubleAll xs
Looks very similar to the builtin map function:
map :: (a -> b) -> [a] -> [b]
map _ [] = []
map f (x:xs) = f x : map f xs
So our doubleAll can actually be simplified as:
doubleAll = map (*2)
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 37 / 58
57. Higher-order Functions and Lists
Student Data
data Student = Student { firstName :: String
, lastName :: String
, finalExamScore :: Double}
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 38 / 58
58. Higher-order Functions and Lists
Student Data
[Student {firstName="John",
lastName="Deer",
finalExamScore=60},
Student {firstName="Billy",
lastName="Bob",
finalExamScore=49.1},
Student {firstName="Jane",
lastName="Doe",
finalExamScore=89},
Student {firstName="Jack",
lastName="Johnson",
finalExamScore=29.3}]
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 39 / 58
59. Higher-order Functions and Lists
Map
Map type signature:
map :: (a -> b) -> [a] -> [b]
Map on student data:
allscores :: [Student] -> [Double]
allscores students = map finalExamScore students
finalExamScore type signature:
finalExamScore :: Student -> Double
Output:
Final Exam Scores: [60.0,49.1,89.0,29.3]
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 40 / 58
60. Higher-order Functions and Lists
Filter
Filter type signature:
filter :: (a -> Bool) -> [a] -> [a]
Filter on student data:
passed :: [Student] -> [Student]
passed students = filter has_passed students
has_passed :: Student -> Bool
has_passed student = finalExamScore student >= 60
Output:
Students that have passed:
[John Deer (60.0),Jane Doe (89.0)]
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 41 / 58
61. Higher-order Functions and Lists
Fold
Fold type signature:
foldl :: (a -> b -> a) -> a -> [b] -> a
Fold on student data:
namecat :: [Student] -> String
namecat students = foldl catfun "" students
catfun :: String -> Student -> String
catfun acc student = acc ++ (firstName student) ++ "n"
Output:
"JohnnBillynJanenJackn"
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 42 / 58
63. Higher-order Functions and Lists
Imperative Filter Example
class Student:
def __init__(self, firstname, lastname, finalexamscore):
self.firstname = firstname
self.lastname = lastname
self.finalexamscore = finalexamscore
def has_passed(self):
return self.finalexamscore >= 60
def passed(students):
passed_students = []
for student in students:
if student.has_passed():
passed_students.append(student)
return passed_students
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 44 / 58
64. Advantages of Functional Programming
Table of Contents
1 Introduction
2 Definition of Functional Programming
3 Function Recap
4 Common FP Idioms
Recursion
Pattern Matching
Higher-order Functions
5 Higher-order Functions and Lists
6 Advantages of Functional Programming
7 Disdvantages of Functional Programming
8 Companies using Functional Programming
9 Where do we go from here?
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 45 / 58
65. Advantages of Functional Programming
Perlisism #19
“ A language that doesn’t affect the way you think about
programming, is not worth knowing. ”
— Alan Perlis[5]
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 46 / 58
66. Advantages of Functional Programming
Advantages of Functional Programming
Changes the way you think about programming and problem solving.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 47 / 58
67. Advantages of Functional Programming
Advantages of Functional Programming
Changes the way you think about programming and problem solving.
Improvements on the types of abstractions we can do with eg.
higher-order functions.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 47 / 58
68. Advantages of Functional Programming
Advantages of Functional Programming
Changes the way you think about programming and problem solving.
Improvements on the types of abstractions we can do with eg.
higher-order functions.
Lock-free concurrency.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 47 / 58
69. Advantages of Functional Programming
Advantages of Functional Programming
Changes the way you think about programming and problem solving.
Improvements on the types of abstractions we can do with eg.
higher-order functions.
Lock-free concurrency.
Improved ways of testing - QuickCheck.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 47 / 58
70. Advantages of Functional Programming
Advantages of Functional Programming
Changes the way you think about programming and problem solving.
Improvements on the types of abstractions we can do with eg.
higher-order functions.
Lock-free concurrency.
Improved ways of testing - QuickCheck.
More effective reasoning about code.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 47 / 58
71. Advantages of Functional Programming
Advantages of Functional Programming
Changes the way you think about programming and problem solving.
Improvements on the types of abstractions we can do with eg.
higher-order functions.
Lock-free concurrency.
Improved ways of testing - QuickCheck.
More effective reasoning about code.
Declare possible Null values explicitly if you need them. Goodbye
NullPointerException (mostly).
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 47 / 58
72. Disdvantages of Functional Programming
Table of Contents
1 Introduction
2 Definition of Functional Programming
3 Function Recap
4 Common FP Idioms
Recursion
Pattern Matching
Higher-order Functions
5 Higher-order Functions and Lists
6 Advantages of Functional Programming
7 Disdvantages of Functional Programming
8 Companies using Functional Programming
9 Where do we go from here?
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 48 / 58
73. Disdvantages of Functional Programming
Disadvantages of Functional Programming
Steep learning curve.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 49 / 58
74. Disdvantages of Functional Programming
Disadvantages of Functional Programming
Steep learning curve.
There are some very cryptic concepts.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 49 / 58
75. Disdvantages of Functional Programming
Disadvantages of Functional Programming
Steep learning curve.
There are some very cryptic concepts.
Tools/IDE’s are not as advanced as the mainstream equivalents.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 49 / 58
76. Disdvantages of Functional Programming
Disadvantages of Functional Programming
Steep learning curve.
There are some very cryptic concepts.
Tools/IDE’s are not as advanced as the mainstream equivalents.
Order of execution may be difficult to reason about in a lazy language.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 49 / 58
77. Disdvantages of Functional Programming
Unfamiliar Territory
Functional Programming is unfamiliar territory for most.
“ If you want everything to be familiar you will never learn
anything new. ”
— Rich Hickey, author of Clojure[6]
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 50 / 58
78. Companies using Functional Programming
Table of Contents
1 Introduction
2 Definition of Functional Programming
3 Function Recap
4 Common FP Idioms
Recursion
Pattern Matching
Higher-order Functions
5 Higher-order Functions and Lists
6 Advantages of Functional Programming
7 Disdvantages of Functional Programming
8 Companies using Functional Programming
9 Where do we go from here?
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 51 / 58
79. Companies using Functional Programming
Companies In South Africa
Pattern Matched Technologies, Midrand Using Erlang for all systems, eg.
processing high volumes of financial transactions.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 52 / 58
80. Companies using Functional Programming
Companies In South Africa
Pattern Matched Technologies, Midrand Using Erlang for all systems, eg.
processing high volumes of financial transactions.
Eldo Energy, Johannesburg Using Clojure for automated meter reading
and intelligent monitoring of consumer energy.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 52 / 58
81. Companies using Functional Programming
Companies In South Africa
Pattern Matched Technologies, Midrand Using Erlang for all systems, eg.
processing high volumes of financial transactions.
Eldo Energy, Johannesburg Using Clojure for automated meter reading
and intelligent monitoring of consumer energy.
Rheo Systems, Pretoria Using Clojure for supply chain integration.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 52 / 58
82. Companies using Functional Programming
Companies In South Africa
Pattern Matched Technologies, Midrand Using Erlang for all systems, eg.
processing high volumes of financial transactions.
Eldo Energy, Johannesburg Using Clojure for automated meter reading
and intelligent monitoring of consumer energy.
Rheo Systems, Pretoria Using Clojure for supply chain integration.
Yuppiechef, Cape Town Using Clojure for their Warehouse Management
System.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 52 / 58
83. Companies using Functional Programming
Companies In South Africa
Pattern Matched Technologies, Midrand Using Erlang for all systems, eg.
processing high volumes of financial transactions.
Eldo Energy, Johannesburg Using Clojure for automated meter reading
and intelligent monitoring of consumer energy.
Rheo Systems, Pretoria Using Clojure for supply chain integration.
Yuppiechef, Cape Town Using Clojure for their Warehouse Management
System.
Effective Control Systems, Kyalami Using Erlang for printer management.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 52 / 58
84. Companies using Functional Programming
Companies In South Africa
Pattern Matched Technologies, Midrand Using Erlang for all systems, eg.
processing high volumes of financial transactions.
Eldo Energy, Johannesburg Using Clojure for automated meter reading
and intelligent monitoring of consumer energy.
Rheo Systems, Pretoria Using Clojure for supply chain integration.
Yuppiechef, Cape Town Using Clojure for their Warehouse Management
System.
Effective Control Systems, Kyalami Using Erlang for printer management.
Mira Networks, Somerset West Using Erlang for billing administration and
mobile development.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 52 / 58
85. Companies using Functional Programming
Companies In South Africa
Pattern Matched Technologies, Midrand Using Erlang for all systems, eg.
processing high volumes of financial transactions.
Eldo Energy, Johannesburg Using Clojure for automated meter reading
and intelligent monitoring of consumer energy.
Rheo Systems, Pretoria Using Clojure for supply chain integration.
Yuppiechef, Cape Town Using Clojure for their Warehouse Management
System.
Effective Control Systems, Kyalami Using Erlang for printer management.
Mira Networks, Somerset West Using Erlang for billing administration and
mobile development.
Amazon.com, Cape Town Using Scala in EC2.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 52 / 58
86. Where do we go from here?
Table of Contents
1 Introduction
2 Definition of Functional Programming
3 Function Recap
4 Common FP Idioms
Recursion
Pattern Matching
Higher-order Functions
5 Higher-order Functions and Lists
6 Advantages of Functional Programming
7 Disdvantages of Functional Programming
8 Companies using Functional Programming
9 Where do we go from here?
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 53 / 58
87. Where do we go from here?
Lambda Luminaries – @lambdaluminary
Local functional programming user group
We meet once a month, on the second Monday of the month.
http://www.meetup.com/lambda-luminaries/
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 54 / 58
88. Where do we go from here?
Online Courses
Functional Programming Principles in Scala
EPFL University
https://www.coursera.org/course/progfun
School of Haskell
FP Complete
https://www.fpcomplete.com/school
Programming Languages
University of Washington
https://www.coursera.org/course/proglang
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 55 / 58
89. Where do we go from here?
Books
Miran Lipovaˇca
Learn You a Haskell for Great Good!
http://learnyouahaskell.com/
Fred H´ebert
Learn You Some Erlang for Great Good!
http://learnyousomeerlang.com/
Yaron Minski, Anil Madhavapeddy, Jason Hickey
Real World OCaml
https://realworldocaml.org/
Paul Chiusano, R´unar Bjarnason
Functional Programming in Scala
http://www.manning.com/bjarnason/
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 56 / 58
90. Where do we go from here?
References I
John Hughes
Why Functional Programming Matters
http:
//www.cs.kent.ac.uk/people/staff/dat/miranda/whyfp90.pdf
John Carmack
Functional Programming in C++
http://www.altdevblogaday.com/2012/04/26/
functional-programming-in-c/
Edsger W. Dijkstra
Go To Statement Considered Harmful
http://www.u.arizona.edu/~rubinson/copyright_violations/
Go_To_Considered_Harmful.html
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 57 / 58
91. Where do we go from here?
References II
Tweet by Michael Feathers
https://twitter.com/mfeathers/status/29581296216
Alan Jay Perlis
http://www.cs.yale.edu/quotes.html
Rich Hickey
http://www.infoq.com/presentations/Simple-Made-Easy
Andreas Pauley
An Introduction to Functional Programming
https://github.com/apauley/fp_presentation
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 58 / 58