Functional reactive programming
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Functional reactive programming combines functional programming and reactive programming. Functional programming avoids mutable state and side effects through referential transparency and reusable functions. Reactive programming builds reactive systems through asynchronous data streams and treating everything as a stream. Observables are the core component, representing a stream of data over time, and operators allow querying, transforming, and combining observables. RxJS is a popular library for implementing functional reactive programming.
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Functional reactive programming
- 1. Functional Reactive Programming BY: AHMED KAMEL TAHA
- 2. Functional Programming Evaluation of mathematical functions ■ Avoid mutable state ■ Referential transparency ■ Avoid side-effects ■ Reusable functions over reusable object ■ Function composition over object composition
- 3. Reactive Programming A programming paradigm that helps you to build ‘Reactive Systems’. E.g.: Google Spreadsheet • In a reactive world, we can't just wait for a function result, a network call, or a database query to return. • Every moment we wait for something, we lose the opportunity to do other things in parallel. • Reactive programming can be done in several ways ◦ • Akka Actors ◦ • Reactive Extensions (Rx) – reactive + functional
- 4. Why Reactive Programming? Why another programming paradigm? • Things are different now! • Conventional software applications won’t be able to fulfill the modern enterprise needs. • Its time to rethink about our software architecture patterns and programming techniques.
- 5. What it actually means to be Reactive? “Readily responsive to a stimulus” - merriam-webster Reactive Systems : •responds in a timely manner •stays responsive in the face of failure •stays responsive under varying workload •rely on asynchronous message-passing
- 6. Functional Programming map filter mergeAll reduce zip
- 7. Map
- 8. Filter
- 9. Map & Filter
- 10. MergeAll
- 11. FlatMap
- 12. Reduce
- 13. Zip
- 14. Reactive Programming Asynchronous data streams Everything is a stream click events user inputs data from a server
- 15. Observables o Stream of data over time o Hot vs Cold Observables o Asynchronous o Lazy o queryable, bufferable, pausable… o more than 120 operations
- 20. Cold Observables • Hot observables are pushing even when we are not subscribed to them (e.g., UI events).
- 21. Hot Observables • Cold observables start pushing only when we subscribe. They start over if we subscribe again.
- 22. Autocomplete
- 23. Autocomplete
- 24. RxJS Supported ◦ IE6+ ◦ Chrome 4+ ◦ FireFox 1+ ◦ Node.js v0.4+ Size (minified & gzipped): ◦ all - 23,1k ◦ lite - 13,5k ◦ compat - 12,5k ◦ ES5 core - 12k
- 25. Framework Bridges AngularJS ReactJS jQuery ExtJS NodeJS Backbone
- 26. Alternatives to RxJS BaconJS Kefir (Elm)
- 27. Conclusion There is a learning curve Great abstraction for async & events Improves Readability Reusability Scalability Both on the front- and backend