Functional Reactive Programming with RxJSstefanmayer13
Talk by @mzupzup and @stefanmayer13 about Functional Reactive Programming in JavaScript at the 4th grazjs meetup (http://www.meetup.com/grazjs/).
The document provides an introduction to RxJS (Reactive Extensions for JavaScript), which is a reactive programming library for asynchronous operations. It discusses key RxJS concepts like Observables, operators, and functional reactive programming. It also provides examples of using RxJS to handle events asynchronously and processing streams of data.
서버 개발자가 바라 본 Functional Reactive Programming with RxJava - SpringCamp2015NAVER / MusicPlatform
youtube : https://youtu.be/E_Bgv9upahI
비동기 이벤트 기반의 라이브러리로만 생각 했던 RxJava가 지금 이 시대 프로그래머에게 닥쳐 올 커다란 메시지라는 사실을 알게 된 지금. 현장에서 직접 느낀 RxJava의 본질인 Function Reactive Programming(FRP)에 대해 우리가 잘 아는 Java 이야기로 풀어 보고 ReactiveX(RxJava) 개발을 위한 서버 환경에 대한 이해와 SpringFramework, Netty에서의 RxJava를 어떻게 이용 하고 개발 했는지 공유 하고자 합니다.
The document discusses Rx.js, a library for reactive programming using Observables. It begins by introducing Rx.js and some of its key benefits over other approaches to asynchronous programming like callbacks and Promises. It then provides examples of using Observables to represent asynchronous data streams and operations like DOM events. Key points made include that Observables allow for lazy execution, cancellation, composition of existing event streams, and treating asynchronous values as collections. The document concludes by demonstrating how Rx.js allows building a Morse code parser by modeling DOM events and signals as Observable streams.
RxJS - The Reactive extensions for JavaScriptViliam Elischer
RxJS is a library for composing asynchronous and event-based programs using observable sequences and functional style operators. It provides developers with Observables to represent asynchronous data streams, operators to query those streams, and Schedulers to parameterize concurrency. Some key operators include map to project values, filter to select values, reduce to aggregate values, and flatMap to flatten nested observables. RxJS supports both hot and cold observables, and is used for tasks like DOM event handling, API communication, and state management in applications.
Video and slides synchronized, mp3 and slide download available at URL http://bit.ly/2a2Djbp.
Gerard Sans explains RxJS' data architecture based on reactive programming, exploring Observables API using RxJS koans and unit tests. RxJS 5 focuses on performance and usability. Filmed at qconlondon.com.
Gerard Sans is a multi-talented Computer Science Engineer specialised in Web. He has lived and worked for all sorts of companies in Germany, Brazil, UK and Spain. He enjoys running AngularJS Labs London, mentoring AngularJS students, participating in the community, giving talks and writing technical articles at Medium.
This document summarizes the new features and goals of RxJS version 5, which aims to improve the modularity, performance, debugging, and extensibility of the RxJS library. Key changes include making RxJS fully modular, improving performance by reducing allocations and call stack sizes, enhancing debugging with simpler operator implementations, and allowing better extensibility through subclassing Observables and maintaining Subject bi-directionality. Simpler unit tests using marble diagrams are also highlighted.
This document discusses functional reactive programming and reactive programming concepts. It compares imperative programming to declarative and reactive programming. Functional programming uses pure functions to create immutable programs without side effects. Reactive programming involves asynchronous data streams that are sequences of ongoing events ordered over time. The document provides code examples demonstrating pure vs impure functions, referential transparency, and reactive programming with RxSwift.
Add Some Fun to Your Functional Programming With RXJSRyan Anklam
This document discusses using RxJS (Reactive Extensions for JavaScript) to add interactivity and animation to an autocomplete search widget. Key events are turned into observables and used to make AJAX requests and trigger animations. Observables are merged, concatenated, and flattened to coordinate the asynchronous events and animations over time. Functional programming concepts like map, filter, and reduce are used to transform and combine the observable streams.
RxJS is a library for composing asynchronous and event-based programs by using observable sequences. It provides operators that allow transforming, filtering, and combining streams of data from diverse sources. Key features include:
- Representing asynchronous data streams with Observables
- Providing LINQ-like operators for querying and transforming streams
- Using Schedulers to control concurrency and synchronize streams with other asynchronous operations like user interactions, server requests, etc.
This document discusses Apache Storm, an open-source distributed real-time computation system for processing streaming data. Storm provides fault tolerance and can scale to large clusters. It uses a spout and bolt programming model where spouts emit streams of data tuples that are processed by bolts. Storm guarantees that every tuple will be fully processed through message tracking and retries. It can scale horizontally by adding machines and increasing parallelism across workers, executors, and tasks.
W3C HTML5 KIG-How to write low garbage real-time javascriptChanghwan Yi
This document summarizes techniques for writing low-garbage real-time JavaScript code. It discusses how to avoid object allocation using syntax like {} and [] instead of the new keyword. It also recommends reusing objects by wiping their properties instead of creating new ones. Functions should be created at startup instead of during runtime. Vector objects should be returned as individual values instead of vector objects. While avoiding garbage entirely is difficult, these techniques can help craft responsive real-time JavaScript with minimal garbage collector overhead.
Streams are Node’s best and most misunderstood idea. In this talk, I try to explain the concept of streams as simple as possible. We also do live coding and solve some real time problems using streams.
The document describes methods for getting quadrants of a quadtree data structure:
- The southWest method returns a new quadtree representing the southwestern quadrant, with origins and sizes set accordingly.
- The southEast method similarly returns a new quadtree for the southeastern quadrant, with origins and sizes of that region.
- Both methods take the existing quadtree as an argument and return a new subtree quadtree representing the specified quadrant region.
The document discusses how to use RxJS (Reactive Extensions library for JavaScript) to treat events like arrays by leveraging Observable types and operators. It explains key differences between Observables and Promises/Arrays, how Observables are lazy and cancelable unlike Promises. Various RxJS operators like map, filter, interval and fromEvent are demonstrated for transforming and composing Observable streams. The document aims to illustrate how RxJS enables treating events as collections that can be processed asynchronously over time.
This document provides best practices for embedded firmware design to make the development process less painful. It recommends using C instead of C++ for firmware programming due to its portability, speed, and clear behavior. State machines should be used everywhere to manage complexity, avoid rare bugs, and make code more testable and reusable. A modular design separates behavior from hardware to enable faster desktop debugging. A hardware abstraction layer isolates hardware interfaces from behavior for portability. On-device debugging should only be used as a last resort due to its slowness compared to desktop debugging.
Sujet bac info 2013 g1, g2 et g3 avec correctionborhen boukthir
This document contains the code for 3 Pascal programs related to numerical analysis exercises:
1. The first program calculates the area under a curve using the rectangle and trapezoid methods, outputting the results to a file.
2. The second program takes user input of phrases and encrypts each phrase by shifting the letters based on their position in the phrase. The original and encrypted phrases are written to files.
3. The third program takes a matrix as input and finds the longest consecutive sequence of nonzero elements in each row, recording the results. It identifies the longest overall sequence and outputs the details.
RxJS101 - What you need to know to get started with RxJS tomorrowViliam Elischer
This document provides an overview of RxJS, a library for composing asynchronous and event-based programs using observable sequences. It discusses key RxJS concepts like Observables, Observers, Operators, and how to create and use Observables. It also provides learning resources and highlights improvements in RxJS 5 like compliance with the Observable specification and better performance.
This document discusses the event loop in JavaScript. It begins by explaining the call stack and memory heap in JavaScript's execution environment. It then discusses how JavaScript is single-threaded and uses an event loop to handle asynchronous tasks and callbacks. Examples are given of how setTimeout is used to illustrate the non-blocking nature of JavaScript and how the event loop processes tasks and callbacks in the queue. It concludes by mentioning how tasks like rendering and animations are handled by the event loop and discusses alternatives like web workers.
This document discusses integrating Google Maps with tilt input from a laptop. It provides code examples in C++, Ruby and Perl for reading tilt sensor data on Windows. It also shows how to combine Google Maps JavaScript API with Perl code to update the map based on tilt input detected by Perl.
Priority queues are data structures that allow efficient retrieval of the maximum or minimum element based on some ordering criteria. A binary heap implementation provides efficient insert and delete-min operations in O(log N) time on average. Elements are stored in a complete binary tree structure in array form. The insert operation bubbles the element up the tree until the heap property is satisfied. Delete-min removes the root and sinks the last element into its place, maintaining the heap property. Building the initial heap from a unsorted list takes O(N) time using the buildHeap algorithm.
This document discusses common software issues that can occur with high altitude balloon (HAB) flights and provides recommendations to help avoid problems. Some key points include:
- Software defects are common, with typical defect rates of 2-4 per thousand lines of code, so HAB software needs thorough testing.
- Real issues seen on HAB flights include computer crashes, incorrect sensor readings, premature cutdown triggers, and transmission/camera failures.
- HAB environments are harsh and software must be able to handle potential hardware failures.
- Common errors include assuming code works without testing, last-minute changes, being too clever in code, overlooking odd behaviors, copying code without understanding it, and thinking finding one bug fixes all
The document discusses using formal methods to formally construct all possible outcomes for an instruction set during program execution. It describes defining events with guards and actions to model normal operation and failure conditions. It explains how the top-level abstraction of an instruction set architecture can be iteratively refined through 32 refinements to model individual instructions like NOP. The refinements generate proof obligations to verify properties are maintained. Tool support like RODIN and event-B is used to develop the models and generate target code like C. Future work includes expanding event-B for more rigorous modeling and model checking, and applying the techniques to existing instruction set architectures.
The document discusses methods for getting the preferred MIME type for a file from its extension or path. It defines a category on NSString to initialize a string from NSData using an IANA character set name. It also shows code for getting the preferred MIME type by calling UTTypeCopyPreferredTagWithClass on the file's UTI, determined from its extension using UTTypeCreatePreferredIdentifierForTag, or from its path using LSCopyItemAttributes.
This document provides an overview of functional reactive programming (FRP) and compositional event systems (CES). It discusses how FRP approaches handling time-varying values like regular values. It presents an example of modeling game movements reactively using key press events. It also demonstrates how CES can be used to handle asynchronous workflows by turning network responses into observable streams. The document compares CES to other approaches like core.async and discusses benefits of CES like supporting multiple subscribers.
Daniel Sikar: Hadoop MapReduce - 06/09/2010 Skills Matter
This document discusses using Hadoop MapReduce on Amazon Web Services for parallel processing of large datasets in a distributed manner. It provides an example of counting word frequencies from log files using Hadoop Streaming to run MapReduce jobs with scripts. The steps shown include launching an Elastic MapReduce cluster, uploading data and scripts to S3, running a MapReduce job to count word frequencies from Wikipedia log files, and then terminating the cluster.
Ganga: an interface to the LHC computing gridMatt Williams
Ganga is a tool, designed and used by the large particle physics experiments at CERN. Written in pure Python, it delivers a clean, usable interface to allow thousands of physicists to interact with the huge computing resources available to them.
Video at https://www.youtube.com/watch?v=SSdluuVNU3Y
Running Containerized Node.js Services on AWS Elastic Beanstalkzupzup.org
The document discusses running containerized Node.js services on AWS Elastic Beanstalk (EB). It provides an overview of Docker containers, AWS, and AWS EB. It describes how to run containerized Node.js microservices on AWS EB, including using Dockerfiles, environment variables, and the AWS EB CLI. It discusses some trade-offs around setup time and costs for using this approach.
Functional Programming Patterns for the Pragmatic ProgrammerRaúl Raja Martínez
In this talk we will see a pragmatic approach to building a purely functional architecture that delivers cohesive functional components.
We will cover functional patterns such as Free Monads, Transformers, Kleisli arrows, dependently typed checked exceptions
and types as well as how they can be glued together to achieve pure functions that are composable, context free, dependently injectable and testable.
Dome project and code with instructions to run it can be found at:
https://github.com/47deg/func-architecture
Add Some Fun to Your Functional Programming With RXJSRyan Anklam
This document discusses using RxJS (Reactive Extensions for JavaScript) to add interactivity and animation to an autocomplete search widget. Key events are turned into observables and used to make AJAX requests and trigger animations. Observables are merged, concatenated, and flattened to coordinate the asynchronous events and animations over time. Functional programming concepts like map, filter, and reduce are used to transform and combine the observable streams.
RxJS is a library for composing asynchronous and event-based programs by using observable sequences. It provides operators that allow transforming, filtering, and combining streams of data from diverse sources. Key features include:
- Representing asynchronous data streams with Observables
- Providing LINQ-like operators for querying and transforming streams
- Using Schedulers to control concurrency and synchronize streams with other asynchronous operations like user interactions, server requests, etc.
This document discusses Apache Storm, an open-source distributed real-time computation system for processing streaming data. Storm provides fault tolerance and can scale to large clusters. It uses a spout and bolt programming model where spouts emit streams of data tuples that are processed by bolts. Storm guarantees that every tuple will be fully processed through message tracking and retries. It can scale horizontally by adding machines and increasing parallelism across workers, executors, and tasks.
W3C HTML5 KIG-How to write low garbage real-time javascriptChanghwan Yi
This document summarizes techniques for writing low-garbage real-time JavaScript code. It discusses how to avoid object allocation using syntax like {} and [] instead of the new keyword. It also recommends reusing objects by wiping their properties instead of creating new ones. Functions should be created at startup instead of during runtime. Vector objects should be returned as individual values instead of vector objects. While avoiding garbage entirely is difficult, these techniques can help craft responsive real-time JavaScript with minimal garbage collector overhead.
Streams are Node’s best and most misunderstood idea. In this talk, I try to explain the concept of streams as simple as possible. We also do live coding and solve some real time problems using streams.
The document describes methods for getting quadrants of a quadtree data structure:
- The southWest method returns a new quadtree representing the southwestern quadrant, with origins and sizes set accordingly.
- The southEast method similarly returns a new quadtree for the southeastern quadrant, with origins and sizes of that region.
- Both methods take the existing quadtree as an argument and return a new subtree quadtree representing the specified quadrant region.
The document discusses how to use RxJS (Reactive Extensions library for JavaScript) to treat events like arrays by leveraging Observable types and operators. It explains key differences between Observables and Promises/Arrays, how Observables are lazy and cancelable unlike Promises. Various RxJS operators like map, filter, interval and fromEvent are demonstrated for transforming and composing Observable streams. The document aims to illustrate how RxJS enables treating events as collections that can be processed asynchronously over time.
This document provides best practices for embedded firmware design to make the development process less painful. It recommends using C instead of C++ for firmware programming due to its portability, speed, and clear behavior. State machines should be used everywhere to manage complexity, avoid rare bugs, and make code more testable and reusable. A modular design separates behavior from hardware to enable faster desktop debugging. A hardware abstraction layer isolates hardware interfaces from behavior for portability. On-device debugging should only be used as a last resort due to its slowness compared to desktop debugging.
Sujet bac info 2013 g1, g2 et g3 avec correctionborhen boukthir
This document contains the code for 3 Pascal programs related to numerical analysis exercises:
1. The first program calculates the area under a curve using the rectangle and trapezoid methods, outputting the results to a file.
2. The second program takes user input of phrases and encrypts each phrase by shifting the letters based on their position in the phrase. The original and encrypted phrases are written to files.
3. The third program takes a matrix as input and finds the longest consecutive sequence of nonzero elements in each row, recording the results. It identifies the longest overall sequence and outputs the details.
RxJS101 - What you need to know to get started with RxJS tomorrowViliam Elischer
This document provides an overview of RxJS, a library for composing asynchronous and event-based programs using observable sequences. It discusses key RxJS concepts like Observables, Observers, Operators, and how to create and use Observables. It also provides learning resources and highlights improvements in RxJS 5 like compliance with the Observable specification and better performance.
This document discusses the event loop in JavaScript. It begins by explaining the call stack and memory heap in JavaScript's execution environment. It then discusses how JavaScript is single-threaded and uses an event loop to handle asynchronous tasks and callbacks. Examples are given of how setTimeout is used to illustrate the non-blocking nature of JavaScript and how the event loop processes tasks and callbacks in the queue. It concludes by mentioning how tasks like rendering and animations are handled by the event loop and discusses alternatives like web workers.
This document discusses integrating Google Maps with tilt input from a laptop. It provides code examples in C++, Ruby and Perl for reading tilt sensor data on Windows. It also shows how to combine Google Maps JavaScript API with Perl code to update the map based on tilt input detected by Perl.
Priority queues are data structures that allow efficient retrieval of the maximum or minimum element based on some ordering criteria. A binary heap implementation provides efficient insert and delete-min operations in O(log N) time on average. Elements are stored in a complete binary tree structure in array form. The insert operation bubbles the element up the tree until the heap property is satisfied. Delete-min removes the root and sinks the last element into its place, maintaining the heap property. Building the initial heap from a unsorted list takes O(N) time using the buildHeap algorithm.
This document discusses common software issues that can occur with high altitude balloon (HAB) flights and provides recommendations to help avoid problems. Some key points include:
- Software defects are common, with typical defect rates of 2-4 per thousand lines of code, so HAB software needs thorough testing.
- Real issues seen on HAB flights include computer crashes, incorrect sensor readings, premature cutdown triggers, and transmission/camera failures.
- HAB environments are harsh and software must be able to handle potential hardware failures.
- Common errors include assuming code works without testing, last-minute changes, being too clever in code, overlooking odd behaviors, copying code without understanding it, and thinking finding one bug fixes all
The document discusses using formal methods to formally construct all possible outcomes for an instruction set during program execution. It describes defining events with guards and actions to model normal operation and failure conditions. It explains how the top-level abstraction of an instruction set architecture can be iteratively refined through 32 refinements to model individual instructions like NOP. The refinements generate proof obligations to verify properties are maintained. Tool support like RODIN and event-B is used to develop the models and generate target code like C. Future work includes expanding event-B for more rigorous modeling and model checking, and applying the techniques to existing instruction set architectures.
The document discusses methods for getting the preferred MIME type for a file from its extension or path. It defines a category on NSString to initialize a string from NSData using an IANA character set name. It also shows code for getting the preferred MIME type by calling UTTypeCopyPreferredTagWithClass on the file's UTI, determined from its extension using UTTypeCreatePreferredIdentifierForTag, or from its path using LSCopyItemAttributes.
This document provides an overview of functional reactive programming (FRP) and compositional event systems (CES). It discusses how FRP approaches handling time-varying values like regular values. It presents an example of modeling game movements reactively using key press events. It also demonstrates how CES can be used to handle asynchronous workflows by turning network responses into observable streams. The document compares CES to other approaches like core.async and discusses benefits of CES like supporting multiple subscribers.
Daniel Sikar: Hadoop MapReduce - 06/09/2010 Skills Matter
This document discusses using Hadoop MapReduce on Amazon Web Services for parallel processing of large datasets in a distributed manner. It provides an example of counting word frequencies from log files using Hadoop Streaming to run MapReduce jobs with scripts. The steps shown include launching an Elastic MapReduce cluster, uploading data and scripts to S3, running a MapReduce job to count word frequencies from Wikipedia log files, and then terminating the cluster.
Ganga: an interface to the LHC computing gridMatt Williams
Ganga is a tool, designed and used by the large particle physics experiments at CERN. Written in pure Python, it delivers a clean, usable interface to allow thousands of physicists to interact with the huge computing resources available to them.
Video at https://www.youtube.com/watch?v=SSdluuVNU3Y
Running Containerized Node.js Services on AWS Elastic Beanstalkzupzup.org
The document discusses running containerized Node.js services on AWS Elastic Beanstalk (EB). It provides an overview of Docker containers, AWS, and AWS EB. It describes how to run containerized Node.js microservices on AWS EB, including using Dockerfiles, environment variables, and the AWS EB CLI. It discusses some trade-offs around setup time and costs for using this approach.
Functional Programming Patterns for the Pragmatic ProgrammerRaúl Raja Martínez
In this talk we will see a pragmatic approach to building a purely functional architecture that delivers cohesive functional components.
We will cover functional patterns such as Free Monads, Transformers, Kleisli arrows, dependently typed checked exceptions
and types as well as how they can be glued together to achieve pure functions that are composable, context free, dependently injectable and testable.
Dome project and code with instructions to run it can be found at:
https://github.com/47deg/func-architecture
In this first lecture, we discuss software quality, introduce the quality characteristic of maintainability, and argue that maintainability can be studied from four different points of view: (1) quality models, (2) good practices, (3) social studies, and (4) developers' studies. We discuss major works and results for these four points of view and show the last three can be used in the first one to build better quality models. We show that quality models are mandatory to make sense of any quality evaluation.
The document discusses various software development methodologies and life cycle models that have been used since the 1950s. It provides detailed descriptions of the waterfall model, spiral model, evolutionary prototyping, and staged delivery approaches. Each methodology takes different approaches to requirements analysis, design, development, testing, and deployment. The document emphasizes the importance of choosing a life cycle model that fits the needs of the specific project.
Functional Programming Patterns (NDC London 2014)Scott Wlaschin
(video of these slides available here http://fsharpforfunandprofit.com/fppatterns/)
In object-oriented development, we are all familiar with design patterns such as the Strategy pattern and Decorator pattern, and design principles such as SOLID.
The functional programming community has design patterns and principles as well.
This talk will provide an overview of some of these, and present some demonstrations of FP design in practice.
The document discusses the software design process. It begins by explaining that software design is an iterative process that translates requirements into a blueprint for constructing the software. It then describes the main steps and outputs of the design process, which include transforming specifications into design models, reviewing designs for quality, and producing a design document. The document also covers key concepts in software design like abstraction, architecture, patterns, modularity, and information hiding.
[DevDay 2019] Reactive Programming with JavaScript - By Pham Nguyen Duc, Web ...DevDay Da Nang
A quick introduction to Reactive Programming which is programming with asynchronous data streams. With RxJS you are given an amazing toolbox of functions to combine, create and filter any of those streams.
Functional Reactive Programming (FRP): Working with RxJSOswald Campesato
Functional Reactive Programming (FRP) combines functional programming and reactive programming by treating asynchronous data streams as basic elements. FRP uses Observables to represent these streams, which emit values over time that can be composed together using operators like map and filter. Popular libraries for FRP include RxJS, which supports asynchronous and event-based programs by modeling push-based data streams with Observables. Operators allow transforming and combining Observable streams to build reactive applications.
This document introduces reactive programming and RxJS. It defines reactive systems as being responsive, resilient, elastic, and message-driven. Reactive programming uses asynchronous data streams and is more declarative, reusable, and testable. RxJS uses Observables to represent push-based collections of multiple values over time. Observables can be subscribed to and provide notifications for next events, errors, and completion. More than 120 operators allow manipulating Observable streams similarly to arrays. The document advocates for using RxJS to represent asynchronous data from various sources to build modern web applications in a reactive way.
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.
This document provides an introduction to reactive programming and RxJS. It begins by explaining the benefits of the reactive approach for asynchronous and event-driven code. It then contrasts reactive and functional programming, noting that reactive programming deals with asynchronous data streams. The document introduces RxJS and how it handles promises and observables. It defines observables and operators. Examples are provided to demonstrate reactive concepts. Resources for further learning are included at the end.
RxJS - The Reactive Extensions for JavaScriptViliam Elischer
RxJS is a library for composing asynchronous and event-based programs using observable sequences and LINQ-style query operators. It offers a language neutral approach to reactive programming using observables that asynchronously push values to observers. Some key benefits of RxJS include clean asynchronous code, error handling, composable observables, and abstraction. The core concepts include observables, observers, and operators to process and transform streams of data over time.
This document introduces Functional Reactive Programming (FRP) using RxJS. FRP is a programming paradigm for reactive programming with asynchronous data streams. RxJS is a library for FRP in JavaScript that allows programming with asynchronous data streams from various sources like files, web services, and user events. The document provides an overview of RxJS, demonstrates its usage, and discusses why FRP is useful for creating cleaner and more maintainable code when dealing with asynchronous processes and events.
This document provides an overview of Rxjs (Reactive Extensions for JavaScript). It begins by explaining why Rxjs is useful for dealing with asynchronous code in a synchronous way and provides one paradigm for asynchronous operations. It then discusses the history of callbacks and promises for asynchronous code. The bulk of the document explains key concepts in Rxjs including Observables, Operators, error handling, testing with Schedulers, and compares Promises to Rxjs. It provides examples of many common Rxjs operators and patterns.
The document discusses Tracy Lee's presentation on reactive programming with RxJS. It provides an agenda for topics to be covered, including reactive programming in standards, frameworks and libraries, how to think reactively, what RxJS is, and how reactive programming makes development easier. Key points mentioned are promises and observables in standards, reactive programming support in Angular, React, Vue, and D3, treating all applications and data as event-driven and represented as sets of values over time, and that RxJS is the most popular library for reactive programming that provides observables as a way to react to and handle events.
RxJs - demystified provides an overview of reactive programming and RxJs. The key points covered are:
- Reactive programming focuses on propagating changes without explicitly specifying how propagation happens.
- Observables are at the heart of RxJs and emit values in a push-based manner. Operators allow transforming, filtering, and combining observables.
- Common operators include map, filter, reduce, buffer, and switchMap. Over 120 operators exist for tasks like error handling, multicasting, and conditional logic.
- Marble diagrams visually demonstrate how operators transform observable streams.
- Creating observables from events, promises, arrays and iterables allows wrapping different data sources in a uniform API
The document discusses reactive programming and how it can help solve issues with asynchronous programming. Reactive programming uses observable data streams and asynchronous operations to make asynchronous code more readable and maintainable. It introduces reactive programming concepts like observables, operators, and schedulers. Examples are given of how reactive extensions like RxJS can simplify asynchronous tasks like autocomplete and handling click events. The benefits of building reactive systems and microservices using a reactive approach are also covered.
Rx.js allows for asynchronous programming using Observables that provide a stream of multiple values over time. The document discusses how Observables can be created from events, combined using operators like map, filter, and flatMap, and subscribed to in order to handle the stream of values. A drag and drop example is provided that creates an Observable stream of mouse drag events by combining mouse down, mouse move, and mouse up event streams. This allows treating the sequence of mouse events as a collection that can be transformed before handling the drag behavior.
Predictable reactive state management - ngrxIlia Idakiev
This document provides an overview and introduction to Predictable Reactive State Management using NGRX. It begins with an introduction to the speaker and then outlines the schedule which includes topics like functional programming, RxJS, Angular change detection, Redux, and NGRX. It then discusses how functional programming concepts like pure functions, immutable data, and declarative programming relate to Angular and libraries like RxJS and NGRX. Specific NGRX concepts like actions, reducers, and selectors are introduced. Examples are provided for building an NGRX application with a single reducer handling the state updates. Additional resources are listed at the end.
Reactive programming with RxJS - ByteConf 2018Tracy Lee
Reactive programming paradigms are all around us. So why does is it awesome? We'll explore reactive programming in standards, frameworks and libraries and talk about how to think reactively.
Then we'll take a more practical approach and talk about how to utilize reactive programming patterns with an abstraction like RxJS, a domain specific language for reacting to events and how using this abstraction can make your development life much easier in React Native.
Functional Reactive Programming in ClojurescriptLeonardo Borges
The document discusses functional reactive programming (FRP) and how it can be used to handle asynchronous workflows and time-varying values. It introduces reactive extensions (Rx) as an implementation of FRP and shows examples of using Rx to turn server results into an observable event stream. This allows processing the stream without explicitly managing state, including accessing the previous and current results with no local variables by zipping a stream with itself while skipping one element. Code examples are provided to demonstrate polling an API continuously to update displayed results reactively as the questions or results change over time.
The document discusses application state in various frameworks and architectures. It covers what constitutes application state, examples of state in REST and client-server apps, and state management in approaches like data in the DOM, Backbone collections, Angular scopes, in-memory databases, FRP, and more persistent solutions. It also discusses related topics like reactivity, consistency, performance, transactions, accountability of changes, and manipulating and saving state.
The document discusses reactive programming and provides examples using RxJS. It defines reactive programming as working with asynchronous data streams. Streams can represent events like user inputs or API responses. Key concepts discussed include:
- Observables represent streams of data that can be subscribed to. Common stream operations like map, filter, and scan can transform streams.
- An example demonstrates creating a stream for a "Who to follow" API, making a request on startup and refresh, and rendering responses.
- Other operators like merge, startWith, and combineLatest are used to combine multiple streams of events and responses.
This document provides an overview of reactive programming with RxJava. It begins with introductions to reactive programming and RxJava. It then discusses operators like map, filter, and flatMap that allow transforming and combining observable streams. It covers topics like error handling, threading with schedulers, subscriptions, and backpressure. The document includes examples of how to use various RxJava operators and concepts like transforming streams, handling errors, and improving performance with techniques like throttling.
This document provides an introduction to RxJS, a library for reactive programming using streams. It discusses how RxJS solves problems with asynchronous code using callbacks by introducing the concept of observable streams. Streams can represent dynamic data sources and allow declarative specification of computations on stream values. The key components in RxJS are Observables, which wrap data sources, and Observers, which consume observable streams and react to emitted events. Common ways of creating observables from sources like arrays or events are demonstrated.
Artificial Intelligence Applications Across IndustriesSandeepKS52
Artificial Intelligence is a rapidly growing field that influences many aspects of modern life, including transportation, healthcare, and finance. Understanding the basics of AI provides insight into how machines can learn and make decisions, which is essential for grasping its applications in various industries. In the automotive sector, AI enhances vehicle safety and efficiency through advanced technologies like self-driving systems and predictive maintenance. Similarly, in healthcare, AI plays a crucial role in diagnosing diseases and personalizing treatment plans, while in financial services, it helps in fraud detection and risk management. By exploring these themes, a clearer picture of AI's transformative impact on society emerges, highlighting both its potential benefits and challenges.
AI and Deep Learning with NVIDIA TechnologiesSandeepKS52
Artificial intelligence and deep learning are transforming various fields by enabling machines to learn from data and make decisions. Understanding how to prepare data effectively is crucial, as it lays the foundation for training models that can recognize patterns and improve over time. Once models are trained, the focus shifts to deployment, where these intelligent systems are integrated into real-world applications, allowing them to perform tasks and provide insights based on new information. This exploration of AI encompasses the entire process from initial concepts to practical implementation, highlighting the importance of each stage in creating effective and reliable AI solutions.
Top 5 Task Management Software to Boost Productivity in 2025Orangescrum
In this blog, you’ll find a curated list of five powerful task management tools to watch in 2025. Each one is designed to help teams stay organized, improve collaboration, and consistently hit deadlines. We’ve included real-world use cases, key features, and data-driven insights to help you choose what fits your team best.
Eliminate the complexities of Event-Driven Architecture with Domain-Driven De...SheenBrisals
The distributed nature of modern applications and their architectures brings a great level of complexity to engineering teams. Though API contracts, asynchronous communication patterns, and event-driven architecture offer assistance, not all enterprise teams fully utilize them. While adopting cloud and modern technologies, teams are often hurried to produce outcomes without spending time in upfront thinking. This leads to building tangled applications and distributed monoliths. For those organizations, it is hard to recover from such costly mistakes.
In this talk, Sheen will explain how enterprises should decompose by starting at the organizational level, applying Domain-Driven Design, and distilling to a level where teams can operate within a boundary, ownership, and autonomy. He will provide organizational, team, and design patterns and practices to make the best use of event-driven architecture by understanding the types of events, event structure, and design choices to keep the domain model pure by guarding against corruption and complexity.
Bonk coin airdrop_ Everything You Need to Know.pdfHerond Labs
The Bonk airdrop, one of the largest in Solana’s history, distributed 50% of its total supply to community members, significantly boosting its popularity and Solana’s network activity. Below is everything you need to know about the Bonk coin airdrop, including its history, eligibility, how to claim tokens, risks, and current status.
https://blog.herond.org/bonk-coin-airdrop/
Revolutionize Your Insurance Workflow with Claims Management SoftwareInsurance Tech Services
Claims management software enhances efficiency, accuracy, and satisfaction by automating processes, reducing errors, and speeding up transparent claims handling—building trust and cutting costs. Explore More - https://www.damcogroup.com/insurance/claims-management-software
How Insurance Policy Administration Streamlines Policy Lifecycle for Agile Op...Insurance Tech Services
A modern Policy Administration System streamlines workflows and integrates with core systems to boost speed, accuracy, and customer satisfaction across the policy lifecycle. Visit https://www.damcogroup.com/insurance/policy-administration-systems for more details!
In a tight labor market and tighter economy, PMOs and resource managers must ensure that every team member is focused on the highest-value work. This session explores how AI reshapes resource planning and empowers organizations to forecast capacity, prevent burnout, and balance workloads more effectively, even with shrinking teams.
Providing Better Biodiversity Through Better DataSafe Software
This session explores how FME is transforming data workflows at Ireland’s National Biodiversity Data Centre (NBDC) by eliminating manual data manipulation, incorporating machine learning, and enhancing overall efficiency. Attendees will gain insight into how NBDC is using FME to document and understand internal processes, make decision-making fully transparent, and shine a light on underlying code to improve clarity and reduce silent failures.
The presentation will also outline NBDC’s future plans for FME, including empowering staff to access and query data independently, without relying on external consultants. It will also showcase ambitions to connect to new data sources, unlock the full potential of its valuable datasets, create living atlases, and place its valuable data directly into the hands of decision-makers across Ireland—ensuring that biodiversity is not only protected but actively enhanced.
The Future of Open Source Reporting Best Alternatives to Jaspersoft.pdfVarsha Nayak
In recent years, organizations have increasingly sought robust open source alternative to Jasper Reports as the landscape of open-source reporting tools rapidly evolves. While Jaspersoft has been a longstanding choice for generating complex business intelligence and analytics reports, factors such as licensing changes and growing demands for flexibility have prompted many businesses to explore other options. Among the most notable alternatives to Jaspersoft, Helical Insight stands out for its powerful open-source architecture, intuitive analytics, and dynamic dashboard capabilities. Designed to be both flexible and budget-friendly, Helical Insight empowers users with advanced features—such as in-memory reporting, extensive data source integration, and customizable visualizations—making it an ideal solution for organizations seeking a modern, scalable reporting platform. This article explores the future of open-source reporting and highlights why Helical Insight and other emerging tools are redefining the standards for business intelligence solutions.
Join the Denver Marketo User Group, Captello and Integrate as we dive into the best practices, tools, and strategies for maintaining robust, high-performing databases. From managing vendors and automating orchestrations to enriching data for better insights, this session will unpack the key elements that keep your data ecosystem running smoothly—and smartly.
We will hear from Steve Armenti, Twelfth, and Aaron Karpaty, Captello, and Frannie Danzinger, Integrate.
Design by Contract - Building Robust Software with Contract-First DevelopmentPar-Tec S.p.A.
In the fast-paced world of software development, code quality and reliability are paramount. This SlideShare deck, presented at PyCon Italia 2025 by Antonio Spadaro, DevOps Engineer at Par-Tec, introduces the “Design by Contract” (DbC) philosophy and demonstrates how a Contract-First Development approach can elevate your projects.
Beginning with core DbC principles—preconditions, postconditions, and invariants—these slides define how formal “contracts” between classes and components lead to clearer, more maintainable code. You’ll explore:
The fundamental concepts of Design by Contract and why they matter.
How to write and enforce interface contracts to catch errors early.
Real-world examples showcasing how Contract-First Development improves error handling, documentation, and testability.
Practical Python demonstrations using libraries and tools that streamline DbC adoption in your workflow.
How AI Can Improve Media Quality Testing Across Platforms (1).pptxkalichargn70th171
Media platforms, from video streaming to OTT and Smart TV apps, face unprecedented pressure to deliver seamless, high-quality experiences across diverse devices and networks. Ensuring top-notch Quality of Experience (QoE) is critical for user satisfaction and retention.
Integration Ignited Redefining Event-Driven Architecture at Wix - EventCentricNatan Silnitsky
At Wix, we revolutionized our platform by making integration events the backbone of our 4,000-microservice ecosystem. By abandoning traditional domain events for standardized Protobuf events through Kafka, we created a universal language powering our entire architecture.
We'll share how our "single-aggregate services" approach—where every CUD operation triggers semantic events—transformed scalability and extensibility, driving efficient event choreography, data lake ingestion, and search indexing.
We'll address our challenges: balancing consistency with modularity, managing event overhead, and solving consumer lag issues. Learn how event-based data prefetches dramatically improved performance while preserving the decoupling that makes our platform infinitely extensible.
Key Takeaways:
- How integration events enabled unprecedented scale and extensibility
- Practical strategies for event-based data prefetching that supercharge performance
- Solutions to common event-driven architecture challenges
- When to break conventional architectural rules for specific contexts
19. F + R + P
■ Powerful Composition and Aggregation of
streams
■ Good fit for concurrent and event-driven
systems
■ Declarative
■ Easy to test
20. Observables
■ Stream of data over time
■ Hot vs Cold Observables
■ Asynchronous
■ Lazy
■ queryable, bufferable, pausable…
■ more than 120 operations
28. .distinctUntilChanged() // only if changes
.flatMapLatest(doAsyncSearch() // do async search on server
.retry(3))
.takeUntil(cancelStream) // chancel stream
.subscribe(
function (data) { // do UI stuff },
function (error) { // do error handling }
);
Autocomplete 2/2
29. Drag & Drop 1/2
var mousedown = Rx.Observable.fromEvent(dragTarget, 'mousedown');
var mousemove = Rx.Observable.fromEvent(document, 'mousemove');
var mouseup = Rx.Observable.fromEvent(dragTarget, 'mouseup');
30. mousedown.flatMap(function (md) {
// get starting coordinates
var startX = md.offsetX, startY = md.offsetY;
return mousemove.map(function (mm) {
// return the mouse distance from start
return {left: mm.clientX - startX, top: mm.clientY - startY };
}).takeUntil(mouseup);
}).subscribe(function (pos) {
// do UI stuff
});
31. Some Cool Stuff on Observables
.bufferWithTime(500)
.pausable(pauser), .pausableBuffered(..)
.repeat(3)
.skip(1), skipUntilWithTime(..)
.do() // for side-effects like logging
.onErrorResumeNext(second) // resume with other obs
.window() // project into windows
.timestamp() // add time for each value
.delay()
36. Conclusion
■ There is a learning curve
■ Great abstraction for async & events
■ Improves
● Readability
● Reusability
● Scalability
■ Both on the front- and backend