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An Introduction to Functional Programming
Andreas Pauley – @apauley
Pattern Matched TechnologiesLambda Luminaries @lambdaluminary
September 2, 2013
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 1 / 58
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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
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Lambda Luminaries – @lambdaluminaryLocal 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
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Introduction
Table of Contents
1 Introduction
2 Definition of Functional Programming
3 Function Recap
4 Common FP IdiomsRecursionPattern MatchingHigher-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
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Introduction
A word from the wise
“ No matter what language you work in, programming ina functional style provides benefits. You should do itwhenever it is convenient, and you should think hardabout 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
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Introduction
Quake
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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. Lazyevaluation. Dynamic typing. Runs on the JVM.
Scala FP and OO. Strict evaluation by default, but supports lazyevaluation. Advanced static type system. Runs on the JVM.
OCaml FP and OO. Part of the ML family. Sometimes claimed tobe “faster than C”. Strict evaluation. Advanced static typesystem. 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
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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. Lazyevaluation. Dynamic typing. Runs on the JVM.
Scala FP and OO. Strict evaluation by default, but supports lazyevaluation. Advanced static type system. Runs on the JVM.
OCaml FP and OO. Part of the ML family. Sometimes claimed tobe “faster than C”. Strict evaluation. Advanced static typesystem. 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
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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. Lazyevaluation. Dynamic typing. Runs on the JVM.
Scala FP and OO. Strict evaluation by default, but supports lazyevaluation. Advanced static type system. Runs on the JVM.
OCaml FP and OO. Part of the ML family. Sometimes claimed tobe “faster than C”. Strict evaluation. Advanced static typesystem. 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
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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. Lazyevaluation. Dynamic typing. Runs on the JVM.
Scala FP and OO. Strict evaluation by default, but supports lazyevaluation. Advanced static type system. Runs on the JVM.
OCaml FP and OO. Part of the ML family. Sometimes claimed tobe “faster than C”. Strict evaluation. Advanced static typesystem. 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
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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. Lazyevaluation. Dynamic typing. Runs on the JVM.
Scala FP and OO. Strict evaluation by default, but supports lazyevaluation. Advanced static type system. Runs on the JVM.
OCaml FP and OO. Part of the ML family. Sometimes claimed tobe “faster than C”. Strict evaluation. Advanced static typesystem. 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
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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. Lazyevaluation. Dynamic typing. Runs on the JVM.
Scala FP and OO. Strict evaluation by default, but supports lazyevaluation. Advanced static type system. Runs on the JVM.
OCaml FP and OO. Part of the ML family. Sometimes claimed tobe “faster than C”. Strict evaluation. Advanced static typesystem. 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
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Definition of Functional Programming
Table of Contents
1 Introduction
2 Definition of Functional Programming
3 Function Recap
4 Common FP IdiomsRecursionPattern MatchingHigher-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
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Definition of Functional Programming
So what exactly is Functional Programming?
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Definition of Functional Programming
Functional Programming, noun:
“ Functional Programming is a listof things you CAN’T do. ”
[7]
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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
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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
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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
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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
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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
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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
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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
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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
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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
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Definition of Functional Programming
Structured Programming and Functional Programming
Structured Programming introduced subroutines with fixed entry/exitpoints (instead of GOTO’s), resulting in improvedmodularity.
Functional Programming provides similar important benefits – more aboutthis later.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 14 / 58
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Definition of Functional Programming
Structured Programming and Functional Programming
Structured Programming introduced subroutines with fixed entry/exitpoints (instead of GOTO’s), resulting in improvedmodularity.
Functional Programming provides similar important benefits – more aboutthis later.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 14 / 58
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Definition of Functional Programming
We need a better definition for Functional Programming.
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Definition of Functional Programming
Functional Programming, noun:
“ Functional programming is so called because a programconsists entirely of functions. ”
— John Hughes, Why Functional Programming Matters [1, p. 1]
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Definition of Functional Programming
OK... so what exactly is a function?
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Function Recap
Table of Contents
1 Introduction
2 Definition of Functional Programming
3 Function Recap
4 Common FP IdiomsRecursionPattern MatchingHigher-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
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Function Recap
An example function
f (x) = 2x + 3
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Function Recap
Variables in functions
f (x) = 2x + 3When 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
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Function Recap
Variables in functions
f (x) = 2x + 3When 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
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Function Recap
Variables in functions
f (x) = 2x + 3When 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
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Function Recap
Variables in functions
f (x) = 2x + 3When 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
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Function Recap
Variables in functions
f (x) = 2x + 3When 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
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Function Recap
Functions can call other functions
g(x) = f (x) + 1
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Function Recap
Values are functions
Constant values are just functions with no input parameters
k = 42def k():
return 42
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Function Recap
Functions can be combined
h(x) = f (g(x))
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Function Recap
Higher-order Functions
Functions can take functions as input and/or returnfunctions as the result.
h(p, q, x) = p(x) + q(2)
h(f , g , 3) = f (3) + g(2)
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Function Recap
Higher-order Functions
Functions can take functions as input and/or returnfunctions as the result.
h(p, q, x) = p(x) + q(2)h(f , g , 3) = f (3) + g(2)
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Function Recap
Higher-order Functions
The derivative of cos(x) returns another function.
ddx cos(x) = − sin(x)
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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
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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
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Common FP Idioms
Table of Contents
1 Introduction
2 Definition of Functional Programming
3 Function Recap
4 Common FP IdiomsRecursionPattern MatchingHigher-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
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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]
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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]
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Common FP Idioms Recursion
An iterative version in Python
def doubleAll(numbers):
doubled = []
for num in numbers:
doubled.append(num * 2)
return doubled
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Common FP Idioms Pattern Matching
Pattern Matching: Haskell
doubleAll :: Num a => [a] -> [a]
doubleAll [] = []
doubleAll (x:xs) = x*2 : doubleAll xs
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Common FP Idioms Higher-order Functions
Higher-order functions: Python
f (x) = 2x + 3g(x) = f (x) + 1h(p, q, x) = p(x) + q(2)
def f(x):
return (2*x) + 3
def g(x):
return f(x) + 1
def h(func_a, func_b, x):
return func_a(x) + func_b(2)
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Common FP Idioms Higher-order Functions
Higher-order functions: Haskell
f (x) = 2x + 3g(x) = f (x) + 1h(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)
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Higher-order Functions and Lists
Table of Contents
1 Introduction
2 Definition of Functional Programming
3 Function Recap
4 Common FP IdiomsRecursionPattern MatchingHigher-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?
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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 thatpassed the exam.
Fold Reduce a list of items to a single value. Example: Reducethe list of students to a single string of all names.
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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 thatpassed the exam.
Fold Reduce a list of items to a single value. Example: Reducethe list of students to a single string of all names.
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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 thatpassed the exam.
Fold Reduce a list of items to a single value. Example: Reducethe 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
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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)
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Higher-order Functions and Lists
Student Data
data Student = Student { firstName :: String
, lastName :: String
, finalExamScore :: Double}
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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}]
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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]
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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)]
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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:
"John\nBilly\nJane\nJack\n"
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Higher-order Functions and Lists
Shortened Map, Filter, Fold
allscores = map finalExamScore
passed = filter has_passed
has_passed student = finalExamScore student >= 60
namecat = foldl catfun ""
where catfun = (\acc student ->
acc ++ (firstName student) ++ "\n")
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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
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Advantages of Functional Programming
Table of Contents
1 Introduction
2 Definition of Functional Programming
3 Function Recap
4 Common FP IdiomsRecursionPattern MatchingHigher-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?
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Advantages of Functional Programming
Perlisism #19
“ A language that doesn’t affect the way you think aboutprogramming, is not worth knowing. ”
— Alan Perlis[5]
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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. GoodbyeNullPointerException (mostly).
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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. GoodbyeNullPointerException (mostly).
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 47 / 58
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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. GoodbyeNullPointerException (mostly).
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 47 / 58
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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. GoodbyeNullPointerException (mostly).
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 47 / 58
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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. GoodbyeNullPointerException (mostly).
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 47 / 58
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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. GoodbyeNullPointerException (mostly).
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 47 / 58
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Disdvantages of Functional Programming
Table of Contents
1 Introduction
2 Definition of Functional Programming
3 Function Recap
4 Common FP IdiomsRecursionPattern MatchingHigher-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?
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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.
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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
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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
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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
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Disdvantages of Functional Programming
Unfamiliar Territory
Functional Programming is unfamiliar territory for most.
“ If you want everything to be familiar you will never learnanything new. ”
— Rich Hickey, author of Clojure[6]
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 50 / 58
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Companies using Functional Programming
Table of Contents
1 Introduction
2 Definition of Functional Programming
3 Function Recap
4 Common FP IdiomsRecursionPattern MatchingHigher-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?
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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 readingand intelligent monitoring of consumer energy.
Rheo Systems, Pretoria Using Clojure for supply chain integration.
Yuppiechef, Cape Town Using Clojure for their Warehouse ManagementSystem.
Effective Control Systems, Kyalami Using Erlang for printer management.
Mira Networks, Somerset West Using Erlang for billing administration andmobile development.
Amazon.com, Cape Town Using Scala in EC2.
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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 readingand intelligent monitoring of consumer energy.
Rheo Systems, Pretoria Using Clojure for supply chain integration.
Yuppiechef, Cape Town Using Clojure for their Warehouse ManagementSystem.
Effective Control Systems, Kyalami Using Erlang for printer management.
Mira Networks, Somerset West Using Erlang for billing administration andmobile development.
Amazon.com, Cape Town Using Scala in EC2.
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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 readingand intelligent monitoring of consumer energy.
Rheo Systems, Pretoria Using Clojure for supply chain integration.
Yuppiechef, Cape Town Using Clojure for their Warehouse ManagementSystem.
Effective Control Systems, Kyalami Using Erlang for printer management.
Mira Networks, Somerset West Using Erlang for billing administration andmobile development.
Amazon.com, Cape Town Using Scala in EC2.
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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 readingand intelligent monitoring of consumer energy.
Rheo Systems, Pretoria Using Clojure for supply chain integration.
Yuppiechef, Cape Town Using Clojure for their Warehouse ManagementSystem.
Effective Control Systems, Kyalami Using Erlang for printer management.
Mira Networks, Somerset West Using Erlang for billing administration andmobile development.
Amazon.com, Cape Town Using Scala in EC2.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 52 / 58
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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 readingand intelligent monitoring of consumer energy.
Rheo Systems, Pretoria Using Clojure for supply chain integration.
Yuppiechef, Cape Town Using Clojure for their Warehouse ManagementSystem.
Effective Control Systems, Kyalami Using Erlang for printer management.
Mira Networks, Somerset West Using Erlang for billing administration andmobile development.
Amazon.com, Cape Town Using Scala in EC2.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 52 / 58
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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 readingand intelligent monitoring of consumer energy.
Rheo Systems, Pretoria Using Clojure for supply chain integration.
Yuppiechef, Cape Town Using Clojure for their Warehouse ManagementSystem.
Effective Control Systems, Kyalami Using Erlang for printer management.
Mira Networks, Somerset West Using Erlang for billing administration andmobile development.
Amazon.com, Cape Town Using Scala in EC2.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 52 / 58
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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 readingand intelligent monitoring of consumer energy.
Rheo Systems, Pretoria Using Clojure for supply chain integration.
Yuppiechef, Cape Town Using Clojure for their Warehouse ManagementSystem.
Effective Control Systems, Kyalami Using Erlang for printer management.
Mira Networks, Somerset West Using Erlang for billing administration andmobile development.
Amazon.com, Cape Town Using Scala in EC2.
Andreas Pauley – @apauley (Pattern Matched TechnologiesLambda Luminaries @lambdaluminary)Functional Programming September 2, 2013 52 / 58
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Where do we go from here?
Table of Contents
1 Introduction
2 Definition of Functional Programming
3 Function Recap
4 Common FP IdiomsRecursionPattern MatchingHigher-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?
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Where do we go from here?
Lambda Luminaries – @lambdaluminaryLocal functional programming user group
We meet once a month, on the second Monday of the month.http://www.meetup.com/lambda-luminaries/
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Where do we go from here?
Online Courses
Functional Programming Principles in ScalaEPFL Universityhttps://www.coursera.org/course/progfun
School of HaskellFP Completehttps://www.fpcomplete.com/school
Programming LanguagesUniversity of Washingtonhttps://www.coursera.org/course/proglang
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Where do we go from here?
Books
Miran LipovacaLearn You a Haskell for Great Good!http://learnyouahaskell.com/
Fred HebertLearn You Some Erlang for Great Good!http://learnyousomeerlang.com/
Yaron Minski, Anil Madhavapeddy, Jason HickeyReal World OCamlhttps://realworldocaml.org/
Paul Chiusano, Runar BjarnasonFunctional Programming in Scalahttp://www.manning.com/bjarnason/
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Where do we go from here?
References I
John HughesWhy Functional Programming Mattershttp:
//www.cs.kent.ac.uk/people/staff/dat/miranda/whyfp90.pdf
John CarmackFunctional Programming in C++http://www.altdevblogaday.com/2012/04/26/
functional-programming-in-c/
Edsger W. DijkstraGo To Statement Considered Harmfulhttp://www.u.arizona.edu/~rubinson/copyright_violations/
Go_To_Considered_Harmful.html
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Where do we go from here?
References II
Tweet by Michael Feathershttps://twitter.com/mfeathers/status/29581296216
Alan Jay Perlishttp://www.cs.yale.edu/quotes.html
Rich Hickeyhttp://www.infoq.com/presentations/Simple-Made-Easy
Andreas PauleyAn Introduction to Functional Programminghttps://github.com/apauley/fp_presentation
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