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Learning Functional Programming in Go

Learning Functional Programming in Go

By : Sheehan
4.1 (8)
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Learning Functional Programming in Go

Learning Functional Programming in Go

4.1 (8)
By: Sheehan

Overview of this book

Lex Sheehan begins slowly, using easy-to-understand illustrations and working Go code to teach core functional programming (FP) principles such as referential transparency, laziness, recursion, currying, and chaining continuations. This book is a tutorial for programmers looking to learn FP and apply it to write better code. Lex guides readers from basic techniques to advanced topics in a logical, concise, and clear progression. The book is divided into four modules. The first module explains the functional style of programming: pure functional programming, manipulating collections, and using higher-order functions. In the second module, you will learn design patterns that you can use to build FP-style applications. In the next module, you will learn FP techniques that you can use to improve your API signatures, increase performance, and build better cloud-native applications. The last module covers Category Theory, Functors, Monoids, Monads, Type classes and Generics. By the end of the book, you will be adept at building applications the FP way.
Table of Contents (13 chapters)
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FP and Micyoservices


Let's look hints of FP philosophies in microservices and related architecturesof  event driven architectures, CQRS, Lambda Architecture and  functional reactive programming.

The architectures we will consider leverage FP philosophies in different ways to achieve their goals of being:

  • Event driven
  • Scalable
  • Responsive
  • Resilient

Message passing

These architectures frequently employ fanout strategies to improve performance. For example, an application might have a series of requests that block while performing each request as follows:

If each request takes 1 second the total time required to send, receive and compose all responses will be 3 seconds.

When possible, we should opt to perform each request asynchronously by fanning out our requests as follows:

This would reduce the time required to process all requests from 3 seconds to 1 second.

 

Asynchronous processing takes less time which frees up our resources faster. This minimizes latency and reduces contention for our shared resources...

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