ReactiveX
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The document discusses functional programming in Java 8, focusing on streams, lambda expressions, and various stream operations such as filter, sort, map, and reduce. It also introduces the observer pattern, which creates a one-to-many dependency between objects, and explains reactive programming with ReactiveX, highlighting the use of asynchronous data streams and observables. Key concepts of functional reactive programming (FRP) are presented, along with practical examples and distinctions between concurrent programming models.
ReactiveX
- 2. ReactiveX The best of functional programming and design patterns !
- 3. Agenda ● Functional Programming (Java 8) ○ Getting Started ○ Examples ● Observer Pattern ○ Introduction ○ Real life example ○ UML ● ReactiveX ○ Introduction ○ Getting Started ○ Example ○ Operators
- 4. Getting Started with Functional Programming (Java 8)
- 5. Functional Programming ● Introduction ● Streams and lambda expressions ● Stream operations ⚪ Filter Stream ⚪ Sort Stream ⚪ Map Stream ⚪ Match Stream ⚪ Stream count ● Optionals ● Reduce Stream ● Parallel vs Sequential streams
- 6. Functional Programming ● Introduction ● Streams and lambda expressions ● Stream operations ⚪ Filter Stream ⚪ Sort Stream ⚪ Map Stream ⚪ Match Stream ⚪ Stream count ● Optionals ● Reduce Stream ● Parallel vs Sequential streams
- 7. Introduction ● It is a declarative programming paradigm, which means programming is done with expressions. ● Functional code, the output value of a function depends only on the arguments that are input to the function.
- 8. Functional Programming ● Introduction ● Streams and lambda expressions ● Stream operations ⚪ Filter Stream ⚪ Sort Stream ⚪ Map Stream ⚪ Match Stream ⚪ Stream count ● Optionals ● Reduce Stream ● Parallel vs Sequential streams
- 9. Lambda Expressions & Streams
- 12. Functional Programming ● Introduction ● Streams and lambda expressions ● Stream operations ⚪ Filter Stream ⚪ Sort Stream ⚪ Map Stream ⚪ Match Stream ⚪ Stream count ● Optionals ● Reduce Stream ● Parallel vs Sequential streams
- 13. Filter Stream
- 14. Functional Programming ● Introduction ● Streams and lambda expressions ● Stream operations ⚪ Filter Stream ⚪ Sort Stream ⚪ Map Stream ⚪ Match Stream ⚪ Stream count ● Optionals ● Reduce Stream ● Parallel vs Sequential streams
- 15. Sort Stream - The ordering of stringCollection is untouched.
- 16. Functional programming ● Introduction ● Streams and lambda expressions ● Stream operations ⚪ Filter Stream ⚪ Sort Stream ⚪ Map Stream ⚪ Match Stream ⚪ Stream count ● Optionals ● Reduce Stream ● Parallel vs Sequential streams
- 17. Map Stream
- 18. Functional programming ● Introduction ● Streams and lambda expressions ● Stream operations ⚪ Filter Stream ⚪ Sort Stream ⚪ Map Stream ⚪ Match Stream ⚪ Stream count ● Optionals ● Reduce Stream ● Parallel vs Sequential streams
- 19. Match Stream
- 20. Match Stream
- 21. Match Stream
- 22. Functional programming ● Introduction ● Streams and lambda expressions ● Stream operations ⚪ Filter Stream ⚪ Sort Stream ⚪ Map Stream ⚪ Match Stream ⚪ Stream count ● Optionals ● Reduce Stream ● Parallel vs Sequential streams
- 23. Count
- 24. Functional programming ● Introduction ● Streams and lambda expressions ● Stream operations ⚪ Filter Stream ⚪ Sort Stream ⚪ Map Stream ⚪ Match Stream ⚪ Stream count ● Optionals ● Reduce Stream ● Parallel vs Sequential streams
- 25. Optional in Java 8
- 26. Functional programming ● Introduction ● Streams and lambda expressions ● Stream operations ⚪ Filter Stream ⚪ Sort Stream ⚪ Map Stream ⚪ Match Stream ⚪ Stream count ● Optionals ● Reduce Stream ● Parallel vs Sequential streams
- 27. Reduce Stream
- 28. Functional programming ● Introduction ● Streams and lambda expressions ● Stream operations ⚪ Filter Stream ⚪ Sort Stream ⚪ Map Stream ⚪ Match Stream ⚪ Stream count ● Optionals ● Reduce Stream ● Parallel vs Sequential streams
- 29. Parallel vs Sequential Streams Sequential stream Parallel stream
- 30. Agenda ● Functional Programming (java 8) ○ Getting Started ○ Examples ● Observer Pattern ○ Introduction ○ Real life example ○ UML ● ReactiveX ○ Introduction ○ Getting Started ○ Example ○ Operators
- 31. Observer pattern
- 32. Introduction ● Defines a “one-to-many” dependency between objects so that when one object changes state, all its dependents are notified and updated. ● Subject: the object which will frequently change its state and upon which other objects depend. ● Observer: the object which depends on a subject and updates according to its subject’s state.
- 34. UML
- 35. Agenda ● Functional Programming (java 8) ○ Getting Started ○ Examples ● Observer Pattern ○ Introduction ○ Real life example ○ UML ● ReactiveX ○ Introduction ○ Getting Started ○ Example ○ Operators
- 36. ReactiveX ReactiveX is a combination of the best ideas from the Observer pattern, the Iterator pattern, and functional programming
- 37. Introduction ● Reactive programming is a programming paradigm oriented around data flows and propagation of change. ● Let: a = b + c what about if b or c has been changed?!
- 38. Introduction ● Functional Reactive programming (FRP) is a style of programming based on two keys ideas: continuous time-varying behaviors, and event based reactively. ● Popularized by Erik Meijer when he created the Rx library for .Net while at Microsoft.
- 39. Reactive Programming Reactive programming is programming with asynchronous data streams.
- 40. What Are Reactive Extensions? ● It’s a library that allows you to use FRP at many programming languages. ● Allows you to represent asynchronous data streams with “Observables”. ● And Parametrize the concurrency in those asynchronous data streams using “Schedulers”
- 41. Rx Family ● C#: Rx.NET ● Javascript: RxJS ● RxJava (Java, Scala, Groovy, Clojure, Kotlin). ● Ruby: Rx.rb ● Python: RxPY ● More at http://reactivex.io/
- 42. Why Functional Reactive Programming? ● Writing concurrent programs correctly is difficult. ● You can transform & compose asynchronous operations. ● High-level abstraction. ● Standard error handling.
- 43. Push vs Pull
- 44. Observables and Observer ● In ReactiveX an Observer subscribes to an Observable. ● Then That Observer reacts to whatever item or sequence of items the Observable emits. ● This patterns facilitate concurrent operations because it does not need to block while waiting for the observable.
- 45. Observer onNext, onCompleted, onError An Observer implements a subset of the following methods: ● onNext: We call this method whenever the Observable emits an item. ● onError: Call this method to indicate the the observable has failed and will not make further calls to onNext or onCompleted. ● onCompleted: Call this method after you have called onNext for the final time and if we have not encountered any errors.
- 47. RxJava ● It’s a JVM implementation of Reactive Extensions. ● Started at Netflix but now Open Sourced. ● Supports Java 6+ & Android 2.3+. ● Java 8 lambda support.
- 53. Filtering Observables ● first() ● distinct() ● take() ● skip() ● elementAt() ● sample() ● more … ● More at https://github.com/ReactiveX/RxJava/wiki/Filtering-Observables
- 57. Thanks !