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Functional programming
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- 2. Styles of Programming Thereare many styles of programming, depending on the dimension you look at and the features available in the language ● Imperative vs Functional ● Compiled vs Scripting ● Static vs Dynamic ● Implicit vs Explicit type conversion ● Managed vs Unmanaged (memory)
- 3. Programming Paradigms Imperative -how to solve ● Procedural ● Object-oriented Declarative - what to solve ● Functional ● Logic
- 4. The “Blub Paradox” ●Paul Graham, Beating the Averages ○ http://www.paulgraham.com/avg.html ● Imagine all languages on a line from the left to the right ● Less powerful languages on the left, More powerful languages on the right ● It is not possible to fully understand languages to the right of the “best” language you know. ○ They have features difficult to grasp the usefulness of before you use them (recursion, first-class functions, monads, actors macros, etc…)
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- 6. Object-Oriented Programming ● Encapsulationby classes/objects ● Polymorphism through inheritance, etc. ● Mutable data (object state changes)
- 7. Functional vs Object-Oriented ●They are orthogonal concepts, not opposites ● Alan Kay, inventor of Smalltalk, said OO is about message passing and isolation, not about objects, classes, inheritance, etc. ● Erlang is the “most object-oriented language” ● http://bit.ly/1vFSqdk
- 8. Functional Programming ● Doesn’thave a precise definition ● Is more than a style of programming ○ I.e. you can do functional programming in any language, it’s just that some languages push you toward this style ● Treat computation as evaluation of mathematical functions
- 9. Functional Programming ● Oftenfocuses on immutable data ● Data and Functions ● Declarative programming style ● Expressions (as opposed to statements)
- 10. Functional Programming ● Referentialtransparency ○ (same input, same output) ● Focus on eliminating “side effects” ● Has its origins in the “lambda calculus”
- 11. Lambda Calculus ● Formalsystem in mathematics for expressing computation ● Developed by Alonzo Church in 1930s ● Based on abstraction and application using binding and substitution ● Universal model of computation
- 12. Maxwell’s Equations ● Defineelectromagnetism ● Compact and precise ● Easy to work with ● “Cosmically spiritual” to a physicist ● God is in this
- 13. “Maxwell’s Equations” ofProgramming ● You can implement a LISP from 7 basic primitives ● Hints at the “mathematical” nature of functional programming ● Strip away all the “junk” and this is computation in its “pure” form. ● Mentally relate this to building a computer in Minecraft ● God is in this
- 14. First-Class Functions ● Functionsare no different than data ● They can be ○ assigned to variables ○ passed as arguments ○ returned from functions
- 15. Higher-Order Functions ● Functionsthat operate on functions ● Take a function as input, return a new function as output ● The derivative, d/dx is a familiar example from math
- 16. Pure Functions ● Referentiallytransparent ● Have no side effects ● Memoization ● If value is not use, there is no effect in removing the function ● Since they can’t affect each other, it is trivial to call them in different orders or automatically parallelize their application
- 17. Referential Transparency ● Anexpression is “referentially transparent” if it can be replaced with its corresponding value. ● Substitution-model of computation ● Requires internals of computation to be “side effect free” ○ No screen output ○ No setting of variables elsewhere ○ No writing to disk ○ No launching of missles
- 18. Recursion ● Looping isnot a thing in functional languages ○ looping requires updating a loop value) ● Tail-call optimization ○ Return from function replaced with jump to beginning ● Continuation passing style
- 19. Tail-Call Optimization ● Makesinfinite recursion not blow up ● Converts a recursive call to iteration ● Replaces call to function at “tail” into a “jmp” back to the start of the function
- 20. Currying ● Translating afunction that takes multiple arguments into the composition of functions of one argument. ● Makes use of closures
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- 22. Partial Application ● Passingfewer than all of the arguments to a function ● Results in a function that is “partially applied” ● Can be used to call “half of a function”
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- 24. Pattern Matching ● Likesmart “case” statements in Ruby ● Compiler works to make statement “true” by binding LHS values, as appropriate ● “Destructuring assignment” from javascript, but on steroids
- 25. Pattern Matching (atuple)
- 26. Pattern Matching (alist)
- 27. Piecewise Function Definition ●You may recall piecewise function definitions from math ● We can do this in many functional languages as well
- 28. Piecewise functions (withguards)
- 29. Immutable Data ● Oncea value is set, it cannot be changed ● Makes it really easy to write durable code ○ You can be sure your values won’t change out from under you ● Makes concurrency stupidly-simple ○ Your values can’t change, so read away with abandon
- 30. Immutability : Howdo change state? ● Basically, you pass new state into a new function ● That function can be yourself ● Special values marked as mutable ○ Keep internal to a function or closure, and just be very careful when you update (Clojure, Lisp, etc.) ● Monads (I won’t talk about these today) ○ Haskell ● Actor Model ○ Erlang/Elixir
- 31. Actor Model An actoris a computational entity that, in response to a message it receives, can concurrently: ● send a finite number of messages to other actors ● create a finite number of new actors ● designate the behavior to be used for the next message it receives.
- 32. Actor Model Each actorruns in it’s own thread
- 33. Actor Model ● AnActor has a mailbox ● Actors communicate with other Actors by sending them immutable messages ● Messages are put into the Actor’s mailbox
- 34. Actor Model ● Whenan Actor’s mailbox has a message, code is run with that message as an argument. This code is called serially. ● When an Actor encounters an error, it dies. ○ “Let it crash” ● Actors can supervise other Actors, and if the supervised Actors die, the supervisor is sent a message. If this message isn’t handled, the supervisor dies.
- 35. OTP/Supervisors ● Actors watchother actors ● “Let it crash” ● Supervisor restarts ● Allows for “happy path programming”
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- 43. Elixir (also) Using pureanonymous functions
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