Faust: Faust 1.10 intermediate

  • 4 Courses | 6h 24m 8s
 
Explore Faust, a programming language for sound synthesis and audio processing.

GETTING STARTED

Faust: Getting Started with Stream Processing

  • 2m 25s
  • 8m 27s

COURSES INCLUDED

Faust: Getting Started with Stream Processing
Faust is a stream processing library that allows you to write code to process data available as streams. In this course, you'll explore the basics of stream processing and how it fundamentally differs from batch processing. You'll start by examining the components of a stream processing system architecture, specifically the role of stream transport. You'll then investigate the Faust stream processing library, which uses native Python code for transformations on streaming data. Moving on, you'll explore what's meant by producers, consumers, and topics in Apache Kafka. You'll install Faust on your local machine as well as the Apache Kafka messaging service. You'll then use these to write a stream processing application. When you're finished with this course, you'll be able to clearly articulate the characteristics of stream processing and work with Apache Kafka and Faust to perform simple operations on input streams.
13 videos | 1h 46m has Assessment available Badge
Faust: Stream Processing Using Models, Agents, & Channels
Stream processing in Faust uses native Python code, meaning you don't have to learn a new domain-specific language to perform data transformations. All you need to know is how existing concepts, such as models, work within a Faust context. Faust models allow you to specify fields and their data types and use this well-defined data structure to access streaming data. In this course, you'll learn how to represent the individual elements of a stream using Faust models. You'll work with agents, which are at the heart of every Faust stream processing application. You'll perform operations using agents and invoke agents synchronously and asynchronously from within your application. You'll then work with channels in Faust. At the end of this course, you'll have the confidence to use models, agents, and channels in the right way to build a successful application.
12 videos | 1h 31m has Assessment available Badge
Faust: Performing Operations & Maintaining State Using Tables
Faust streams support a wide range of operations. In this course, you'll learn how to perform several of these. You'll also work with Faust tables - which store state in the form of key-value pairs and allow for the recovery of failed processing, making Faust fault-tolerant. You'll start off by using the group by operation to designate a key used to repartition an input stream and create a new topic in Kafka. You'll then use the items() operation to access the key and message value and take() operation to buffer multiple elements in a stream. Next, you'll work with tables to conduct stateful stream processing, illustrating how table data is stored in an embedded RocksDB database. When you've finished this course, you'll be able to apply a wide range of operations on input streams and perform stateful stream processing using tables.
15 videos | 1h 37m has Assessment available Badge
Faust: Stream Processing Using Windowing Operations
When working with data, windows are a handy tool to accumulate data subsets from input streams and perform aggregation operations on this specific data. In this course, you'll learn how to perform stream processing through windowing operations in Faust. You'll start by examining the different windowing operations possible on input streams, including tumbling, sliding, count, session, and global windows. Next, you'll distinguish the three notions of time associated with streaming events: event, ingestion, and processing time. You'll then use Faust window features to perform windowing operations on input streams and emit aggregation results for every window. Finally, you'll use the REST API server, which all Faust applications have, to make streaming code metrics and table data accessible to the user. Once you're done with this course, you'll be able to use windowing operations via Faust and expose metrics using web views.
13 videos | 1h 28m has Assessment available Badge
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SKILL BENCHMARKS INCLUDED

Python Resource Optimization Literacy (Beginner Level)
The Python Resource Optimization Literacy (Beginner Level) benchmark assesses your ability to use OpenCV to read and write images, explore color scale and grayscale images, and perform basic image transformations. You will be evaluated on your ability to differentiate batch and stream processing, recall the components in a stream processing architecture, and install stream processing using a Faust application that reads streaming messages from a Kafka topic. A learner who scores high on this benchmark demonstrates that they have the skills to perform basic operations in OpenCV and Faust for image transformation and stream processing.
14m    |   14 questions
Python Resource Optimization Competency (Intermediate Level)
The Python Resource Optimization Competency (Intermediate Level) benchmark measures your ability to implement a variety of image manipulations using OpenCV to prepare images for end users or machine learning pipelines. You will be evaluated on your knowledge of representing streaming elements using Faust models, processing them using agents, and sending and receiving messages using channels. A learner who scores high on this benchmark demonstrates that they have the skills to manipulate images in OpenCV and perform stream processing using models, agents, and channels in Faust.
12m    |   12 questions
Python Resource Optimization Proficiency (Advanced Level)
The Python Resource Optimization Proficiency (Advanced Level benchmark measures your ability to perform image transformation in OpenCV using advanced image operations to generate augmented or pre-processed images. You will be evaluated on your ability to implement operations for processing Faust stream data and use tables for fault-tolerance and stateful stream processing transformations. You will also be assessed on your knowledge of different windowing operation types, performing windowing operations, exposing app metrics using web views, and the differences between event time, ingestion time, and processing time. A learner who scores high on this benchmark demonstrates that they have the skills to perform advanced image operations using OpenCV, and can maintain state in tables and implement stream processing using windows operations in Faust.
22m    |   22 questions
Python Resource Optimization Awareness (Entry Level)
The Python Resource Optimization Awareness benchmark will measure your ability to read images from file system into Python source and analyze and process using OpenCV and Faust. You will be evaluated on your ability to recognize fundamental concepts related to computer vision and the basic operations performed on images using OpenCV. A learner who scores high on this benchmark demonstrates that they have the skills to perform basic operations such as add and subtract using two images and to perform stream processing through windowing operations in Faust.
22m 30s    |   15 questions
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