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Introduction to reactive programming

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Leapfrog Technology Inc.
Leapfrog Technology Inc.

Reactive programming is quite a popular topic these days. For a long time, reactive programming was constrained to interactive user interface designs. With the advancement of hardware (multi-core CPU’s) and the internet, the scale, complexity, and responsiveness of software began to rise which led to reactive programming being regarded as a major programming paradigm. Read more from here: https://blog.lftechnology.com/introduction-to-reactive-programming-part-1-5b7c63685586 By: Subash Poudel (Software Engineer @ Leapfrog Technology, Inc.)

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INTRODUCTION TO REACTIVE PROGRAMMING BY: SUBASH POUDEL
CONTENTS Introduction to Reactive programming Imperative Programming Reactive Programming Why should you care Four Reactive Principles RxExtensions Marble Diagrams and common operators Observable Observer Subscriber Questions
What is Reactive Programming? 3 Imperative programming programming paradigm that uses statements that change a program's state Example: Buying newspaper in a shop var a = 5 var b = 6 var sum = a + b a = 7 // sum is still 11 Reactive Programming: programming paradigm oriented around data flows and the propagation of change Examples: Spreadsheets User Interface Menus Example: Subscribing to newspapers
WHY SHOULD YOU CARE • Easy to read/reason and understand • Cross platform/language concept • Less error prone • Open source • To avoid Spaghetti / Boilerplate code • A lot of very popular library have rx wrappers • Eg: RxAlamofire for networking in swift
4 REACTIVE PRINCIPLES Image courtesy: Suraj Vaidya
• Fast • Should provide feedback to user input • Notify that an error has occurred RESPONSIVE RESILIENT • Ability to recover from failure/exceptions • Eg: retrying network calls
• Scalable • Able to handle growing amount of work ELASTIC MESSAGE DRIVEN • Reacts to events that happen not blocked waiting for them • Data (events) flow throughout the system
RX EXTENSIONS RX = Reactive Extensions Reactive Extensions (Rx) is a library for composing asynchronous and event-based programs using observable sequences RX = Iterator Pattern + Observer Pattern + Schedulers TECHNICALLY
• Provide a way to access the elements of an collection sequentially without exposing its underlying representation • For any collection we get the iterator from which each element can be traversed / accessed • Pull based mechanism i.e. consumer is responsible for creating the iterator to access each element at a time from the producer (collection) ITERATOR PATTERN
• The observer pattern is a software design pattern in which an object, called the subject, maintains a list of its dependents, called observers, and notifies them automatically of any state changes, usually by calling one of their methods. It is mainly used to implement distributed event handling systems. • The producer is responsible for providing the consumer with data push mechanism OBSERVABLE PATTERN
SCHEDULERS • By default observable sequences will observe events and react to them in the same thread. Schedulers are a way to change this behavior as a way to distribute tasks across threads. • Thread abstractions for concurrent and asynchronous work • Especially useful in mobile devices where there is a dedicated thread called Main/UI thread for handling ui changes • Specifies in which thread the computations will occur e.g. io, computation, Main
AVAILABLE FOR: RxJAVA RxSwift Rx.net RxPHP RxJS RxCPP and more… PLATFORM EXTENSIONS RxAndroid RxCocoa
MARBLE DIAGRAMS AND COMMON OPERATORS http://rxmarbles.com/
OBSERVABLE // skeleton public class Observable<T> { // many rx operators Subscription subscribe(final Observer<T> observer) {} } • Data source i.e. creates events • Provides data to observer using onNext() function • Notify that an error has occurred using onError() function • Notify completion of stream/data using onComplete() function
OBSERVER public interface Observer<T> { void onCompleted(); void onError(Throwable e); void onNext(T t); } • Observer subscribes to an Observable • Get notified/react to next, error and completion events • Primary reason why threads are not blocked in reactive programming • onNext(): An Observable calls this method whenever the Observable emits an item. This method takes as a parameter the item emitted by the Observable. • onError(): An Observable calls this method to indicate that it has failed to generate the expected data or has encountered some other error. It will not make further calls to onNext or onCompleted. The onError method takes as its parameter an indication of what caused the error. • onCompleted(): An Observable calls this method after it has called onNext for the final time, if it has not encountered any errors.
SUBSCRIBERS public interface Subscription { void unsubscribe(); boolean isUnsubscribed(); } class Subscriber<T> implements Observer<T>, Subscription { } • A Subscriber is an Observer that can also unsubscribe from that data source (through the Subscription interface).
QUESTIONS???

More Related Content

Introduction to reactive programming

  • 2. CONTENTS Introduction to Reactive programming Imperative Programming Reactive Programming Why should you care Four Reactive Principles RxExtensions Marble Diagrams and common operators Observable Observer Subscriber Questions
  • 3. What is Reactive Programming? 3 Imperative programming programming paradigm that uses statements that change a program's state Example: Buying newspaper in a shop var a = 5 var b = 6 var sum = a + b a = 7 // sum is still 11 Reactive Programming: programming paradigm oriented around data flows and the propagation of change Examples: Spreadsheets User Interface Menus Example: Subscribing to newspapers
  • 4. WHY SHOULD YOU CARE • Easy to read/reason and understand • Cross platform/language concept • Less error prone • Open source • To avoid Spaghetti / Boilerplate code • A lot of very popular library have rx wrappers • Eg: RxAlamofire for networking in swift
  • 5. 4 REACTIVE PRINCIPLES Image courtesy: Suraj Vaidya
  • 6. • Fast • Should provide feedback to user input • Notify that an error has occurred RESPONSIVE RESILIENT • Ability to recover from failure/exceptions • Eg: retrying network calls
  • 7. • Scalable • Able to handle growing amount of work ELASTIC MESSAGE DRIVEN • Reacts to events that happen not blocked waiting for them • Data (events) flow throughout the system
  • 8. RX EXTENSIONS RX = Reactive Extensions Reactive Extensions (Rx) is a library for composing asynchronous and event-based programs using observable sequences RX = Iterator Pattern + Observer Pattern + Schedulers TECHNICALLY
  • 9. • Provide a way to access the elements of an collection sequentially without exposing its underlying representation • For any collection we get the iterator from which each element can be traversed / accessed • Pull based mechanism i.e. consumer is responsible for creating the iterator to access each element at a time from the producer (collection) ITERATOR PATTERN
  • 10. • The observer pattern is a software design pattern in which an object, called the subject, maintains a list of its dependents, called observers, and notifies them automatically of any state changes, usually by calling one of their methods. It is mainly used to implement distributed event handling systems. • The producer is responsible for providing the consumer with data push mechanism OBSERVABLE PATTERN
  • 11. SCHEDULERS • By default observable sequences will observe events and react to them in the same thread. Schedulers are a way to change this behavior as a way to distribute tasks across threads. • Thread abstractions for concurrent and asynchronous work • Especially useful in mobile devices where there is a dedicated thread called Main/UI thread for handling ui changes • Specifies in which thread the computations will occur e.g. io, computation, Main
  • 13. MARBLE DIAGRAMS AND COMMON OPERATORS http://rxmarbles.com/
  • 14. OBSERVABLE // skeleton public class Observable<T> { // many rx operators Subscription subscribe(final Observer<T> observer) {} } • Data source i.e. creates events • Provides data to observer using onNext() function • Notify that an error has occurred using onError() function • Notify completion of stream/data using onComplete() function
  • 15. OBSERVER public interface Observer<T> { void onCompleted(); void onError(Throwable e); void onNext(T t); } • Observer subscribes to an Observable • Get notified/react to next, error and completion events • Primary reason why threads are not blocked in reactive programming • onNext(): An Observable calls this method whenever the Observable emits an item. This method takes as a parameter the item emitted by the Observable. • onError(): An Observable calls this method to indicate that it has failed to generate the expected data or has encountered some other error. It will not make further calls to onNext or onCompleted. The onError method takes as its parameter an indication of what caused the error. • onCompleted(): An Observable calls this method after it has called onNext for the final time, if it has not encountered any errors.
  • 16. SUBSCRIBERS public interface Subscription { void unsubscribe(); boolean isUnsubscribed(); } class Subscriber<T> implements Observer<T>, Subscription { } • A Subscriber is an Observer that can also unsubscribe from that data source (through the Subscription interface).