In this course you will learn how to apply the functional programming style in the design of larger applications. You'll get to know important new functional programming concepts, from lazy evaluation to structuring your libraries using monads. We'll work on larger and more involved examples, from state space exploration to random testing to discrete circuit simulators. You’ll also learn some best practices on how to write good Scala code in the real world. Several parts of this course deal with the question how functional programming interacts with mutable state. We will explore the consequences of combining functions and state. We will also look at purely functional alternatives to mutable state, using infinite data structures or functional reactive programming. Learning Outcomes. By the end of this course you will be able to: - recognize and apply design principles of functional programs, - design functional libraries and their APIs, - competently combine functions and state in one program, - understand reasoning techniques for programs that combine functions and state, - write simple functional reactive applications. Recommended background: You should have at least one year programming experience. Proficiency with Java or C# is ideal, but experience with other languages such as C/C++, Python, Javascript or Ruby is also sufficient. You should have some familiarity using the command line. This course is intended to be taken after Functional Programming Principles in Scala: https://www.coursera.org/learn/progfun1.
本課程是 Functional Programming in Scala 專項課程 專項課程的一部分
Functional Program Design in Scala
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- Data Engineers
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- Chief Technology Officers (CTOs)
教學大綱 - 您將從這門課程中學到什麼
For Expressions and Monads
We'll start by revisiting some concepts that we have learned from Principles of Functional Programming in Scala; collections, pattern matching, and functions. We'll then touch on for-comprehensions, a powerful way in Scala to traverse a list, process it, and return a new list. We'll see how to do queries with for-comprehensions as well as how the for-comprehension is "desugared" into calls to higher-order functions by the Scala compiler. Finally, we'll discuss what monads are, and how to verify that the monad laws are satisfied for a number of examples.
Lazy Evaluation
This week we'll revisit performance issues caused by combinatorial search, and we'll discover an important concept in functional programming that can these issues: laziness. We'll also learn a little bit about proofs on trees; in particular, we'll see how to extend structural induction to trees.
Functions and State
This week, we'll learn about state and side-effects. Through a rich example, we'll learn programming patterns for managing state in larger programs. We'll also learn about for-loops and while-loops in Scala.
Timely Effects
This week we'll learn a number of important programming patterns via examples, starting with the observer pattern, and then going on to functional reactive programming. We'll learn how latency can be modeled as an effect, and how latency can be handled with Scala's monadic futures. We'll learn the important combinators on futures as well as how they can be composed to build up rich and responsive services.
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來自Functional Program Design in Scala的熱門評論
This is a university degree course which takes enormous effort to complete. But still its beond the programming course range giving you whats not possible to google or learn practical way. Thanks!
Thank you for this exciting course! I did the FP in Scala course a few years ago and decided to do the full certification now. I am looking forward to the next courses in the specialisation.
講師
Martin Odersky
Professor關於 洛桑联邦理工学院
關於 Functional Programming in Scala 專項課程
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