Functional pogramming hl overview
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The document introduces functional programming (FP) principles and features. It discusses how FP promotes modularity, purity, and immutability. FP languages emphasize functions as first-class values, recursion, pattern matching, and algebraic data types. The goal is not to convince readers to abandon object-oriented programming, but to consider additional paradigms and techniques that can be used in any language.
![A
A
An appetizer:
sorted :: [Integer] -> Bool
sorted [] = True
sorted [_] = True
sorted (x:y:zs) = x < y && sorted (y:zs)
So, What Is It All About?
Functional ProgrammingOther programming styles
Classes, proceduresBuilding Blocks
N/AA mustState changes
Function calls,Loops, conditionals, and
function (method) calls
Main control flow](https://image.slidesharecdn.com/functionalpogramminghloverview-150607181331-lva1-app6892/85/Functional-pogramming-hl-overview-6-320.jpg)
![Functions as First-Class Values
You can do with functions whatever you can do
with other data-types. E.g.:
Bind identifier to a function
Store a function in a data structure
let squareIt = fun n -> n * n
let doubleIt = fun n -> 2 * n
let funList = [ squareIt; doubleIt ]](https://image.slidesharecdn.com/functionalpogramminghloverview-150607181331-lva1-app6892/85/Functional-pogramming-hl-overview-21-320.jpg)
![Pattern Matching
factorial :: Integer -> Integer
factorial 0 = 1
factorial n = n * factorial (n - 1)
fib :: Integer -> Integer
fib 0 = 1
fib 1 = 1
fib n = fib (n-1) + fib (n-2)
length' :: (Num b) => [a] -> b
length' [] = 0
length' (_:xs) = 1 + length' xs](https://image.slidesharecdn.com/functionalpogramminghloverview-150607181331-lva1-app6892/85/Functional-pogramming-hl-overview-24-320.jpg)
![Lazy Evaluation
Evaluation is deferred until their results are
needed
Allows using infinite listsnats = [0..]
odds = [1,3..]
ones = 1 : ones
-- What will happen when executing the following?
length odds
take 5 odds](https://image.slidesharecdn.com/functionalpogramminghloverview-150607181331-lva1-app6892/85/Functional-pogramming-hl-overview-26-320.jpg)
Functional pogramming hl overview
- 1. Copyright © SELA Software & Education Labs, Ltd. | 14-18 Baruch Hirsch St., Bnei Brak 51202, Israel | www.selagroup.com Functional Programming High Level Introduction elada@sela.co.il http://il.linkedin.com/in/eladavneri/ http://blogs.microsoft.co.il/elada Elad Avneri Architect, ALM and Software Development
- 2. Agenda The Basics Principles FP Languages Features Comparison Demo: Imperative to FP Evolution
- 3. 3 Software Development Challenges Modern software becomes larger and more complex We’d like to reduce the time and cost of software development We’d like to increase the quality of the developed software
- 4. FP to the Rescue Promotes composition and modularity Promotes simpler code Concise, promotes smaller code Concurrency is not an issue Dramatically reduces number of bugs
- 5. The Goal of this Presentation Is not to convince to abandon OOP Is to open your mind for additional paradigm Learn techniques which you can utilize in your favorite programming language http://theburningmonk.com/2015/04/dont-learn-a-syntax-learn-to-change-the-way-you-think/
- 6. A A An appetizer: sorted :: [Integer] -> Bool sorted [] = True sorted [_] = True sorted (x:y:zs) = x < y && sorted (y:zs) So, What Is It All About? Functional ProgrammingOther programming styles Classes, proceduresBuilding Blocks N/AA mustState changes Function calls,Loops, conditionals, and function (method) calls Main control flow
- 7. FP Principles Immutability Pure functions Modularity and composition Declarative
- 8. Immutability Thread safe Data flow is explicit Cacheable objects "How many Haskell programmers does it take to change a lightbulb?“ "Haskell programmers don't "change" lightbulbs, they "replace" them. And you must also replace the whole house at the same time.”
- 9. Idempotence: Get the same results no matter how many times a function is called We gain the ability to cache results for function calls Insanity: doing the same thing over and over again and expecting different results. Albert Einstein Pure Functions
- 10. A function has no side effect We gain clarity We gain “laziness”: int foo() { bar(); return 0; } Pure Functions
- 11. Function calls are independent Can be parallelized result = func1(x,y) + func2(x,z) Pure Functions
- 12. Pure Functions Encapsulation is in the function level Easier to debug Easier to test in isolation
- 13. Modularity and Composability A function’s output is only its return value We gain: Modularity with light coupling Composability
- 14. Declarative The focus is on what the computer should do rather than how it should do it Think of a spreadsheet: We don’t specify the order of calculations We don’t deal with variables We deal with expressions and not with steps We tell it what we want not how to achieve it Think of SQL… FP is the same but for general purpose
- 15. Imperative List<int> results = new List<int>(); foreach(var num in collection) { if (num % 2 != 0) results.Add(num); } Declarative vs Imperative Declarative var results = collection.Where( num => num % 2 != 0); List<int> collection = new List<int> { 1, 2, 3, 4, 5 }; http://stackoverflow.com/a/1784702/871579
- 16. Myths and Misconceptions It’s difficult It’s not difficult it’s “just” unfamiliar We can do it also in XXX (= your favorite language) Maybe, but “real” FP language is “pushing” you there It’s not practical for real-world applications Simply wrong FP has poor performance Actually some of the features gives great optimization opportunities The quality code vs optimized code tradeoff
- 17. FP is here from the ‘50s At the beginning computers were slow Not enough power to process abstractions Now it’s back! The Retro of FP
- 18. Functional Programming/Language Functional programming is style of programming A functional language is one that supports and encourages the functional style
- 19. (Some) Functional Language Features Separate data from behavior Functions as First-Class Values High-Order Functions Recursion Pattern matching Algebraic data types Lazy evaluation
- 20. Separate Data from Behavior No classes and objects Data passes between functions as parameters and return values
- 21. Functions as First-Class Values You can do with functions whatever you can do with other data-types. E.g.: Bind identifier to a function Store a function in a data structure let squareIt = fun n -> n * n let doubleIt = fun n -> 2 * n let funList = [ squareIt; doubleIt ]
- 22. Functions as First-Class Values High order functions let compose = fun op1 op2 -> // Use a let expression to build the function that will be returned. let funToReturn = fun n -> op1 (op2 n) // Then just return it. funToReturn let squareAndDouble = compose doubleIt squareIt // The following expression squares 3, doubles 9, returns 18, and // then displays 18. System.Console.WriteLine(squareAndDouble 3)
- 23. Recursion No loops factorial n = if n < 2 then 1 else n * factorial (n-1)
- 24. Pattern Matching factorial :: Integer -> Integer factorial 0 = 1 factorial n = n * factorial (n - 1) fib :: Integer -> Integer fib 0 = 1 fib 1 = 1 fib n = fib (n-1) + fib (n-2) length' :: (Num b) => [a] -> b length' [] = 0 length' (_:xs) = 1 + length' xs
- 25. Algebraic Data Types data Bool = False | True data Point = Point Float Float deriving (Show) data Shape = Circle Point Float | Rectangle Point Point deriving (Show) surface :: Shape -> Float surface (Circle _ r) = pi * r ^ 2 surface (Rectangle (Point x1 y1) (Point x2 y2)) = (abs $ x2 - x1) * (abs $ y2 - y1)
- 26. Lazy Evaluation Evaluation is deferred until their results are needed Allows using infinite listsnats = [0..] odds = [1,3..] ones = 1 : ones -- What will happen when executing the following? length odds take 5 odds
- 27. Language Comparison F#ScalaHaskell CLR (.Net)JVMNativeRuntime Medium1High (-)HighFP Adherence Default (but may be not) Default (but may be not) YesImmutability YesNot by default (but can be) YesLazy Evaluation YesYesYesAlgebraic Data Types 1) E.g. functions are not guaranteed to be pure: let tm = DateTime.Now
- 28. Demo Imperative to FP Evolution
- 29. What should you Take? Don’t learn a syntax, learn to change the way you think Add new paradigms to your toolbox Get out of your comfort zone
- 30. Questions
- 31. Copyright © SELA Software & Education Labs, Ltd. | 14-18 Baruch Hirsch St., Bnei Brak 51202, Israel | www.selagroup.com Thank You elada@sela.co.il http://il.linkedin.com/in/eladavneri/ http://blogs.microsoft.co.il/elada Elad Avneri Architect, ALM and Software Development