English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 3h 22m | 584 MB
Functional reactive data flows for GUIs and distributed network applications
This video will be your guide to getting started with Reactive programming in Python. You will begin with the general concepts of Reactive programming and then gradually move on to work with asynchronous data streams.
You will then be introduced to functional reactive programming and will learn to apply FRP in practical use cases in Python. You will understand how ReactiveX works and how it efficiently supports sequences of data. You will then understand the role of asynchronous programming and event-based programming in detail to build reactive extensions.
You will learn to create dataflow-based systems, the building blocks of reactive programming. This course will take you through creating, merging, filtering, transforming, and error-handling observables to extend your asynchronous code.
You will then learn to scale applications using multi-node clusters and will learn to unit-test your clusters. This video also introduces you to Reactive microservices with Python.
In this video, you’ll learn how to build reactive applications in a step-by-step manner. You’ll build applications that use reactive programming principles, the Qt GUI framework, and the Tornado web framework. you’ll test these parts and then put them together to build a real-time stock exchange.
What You Will Learn
- Use reactive programming to build distributed systems running on multiple nodes
- What is Reactive programming and when should you use it?
- Handle UI interactions/events very easily
- Handle errors with Reactive programming
- Create a distributed application using Tornado that uses Reactive programming
- Test a cluster of reactive, distributed web servers and clients to make sure your app can scale
- Unit-test reactive programs whether they’re GUIs or web servers
- Build a reactive real-time stock exchange with Python, Qt, Tornado, and RxPy
Table of Contents
Installation and Setup
1 The Course Overview
2 Installing RxPy Reactive Extensions
3 Installing Qt5 and PyQt5
4 Installing the Tornado Web Framework
Reactive Extensions for Python
5 What Is Reactive Programming
6 Reactive Operators and Observables – From, Interval, and Buffer
7 More Reactive Operators and Observables – Group By, Sample, and Max
8 Loading CSV Data Reactively with RxPy
9 Even More Reactive Operators – Map, FlatMap, Window, CombineLatest, and Zip
Reactive GUIs and Data Flows with Qt and RxPy
10 Hello World GUI with a Simple Reactive Button
11 DisplayingFiltering Table Data from a Real-Time Source
12 Real-Time Form Validation
Reactive Web ServersClients with the Tornado Web Framework
13 Async Real-Time Web Server
14 Real-Time Async Client – Part 1
15 Queues in Tornado
16 Real-Time Async Client – Part 2
Testing Reactive GUIs and a Cluster of Web ServersClients
17 Unit Testing a Basic Reactive Data Flow
18 Unit Testing a GUI Reactive Data Flow
19 Unit Testing a Reactive Tornado Server
20 Building and Testing a Web Server Cluster
Build a Reactive Real-Time Stock Exchange
21 Stock Exchange Web Server with WebSockets
22 Stock Exchange GUI to Display Orders
23 Connecting the Stock Exchange Reactive Client to the Server
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