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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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Generics implementation options


Below is a decision matrix that can be used to evaluate which generics implementation is best.

There are many aspects to consider when we think about how to implement generics. For example, let's consider the difference between Haskell's parametric polymorphism and C++'s ad hoc polymorphism.

In Haskell, polymorphic functions are defined uniformly for all types. We could call this compile time polymorphism.

In C++, dynamic polymorphism, via substitution, virtual functions and interfaces enable polymorphic behavior, but whether our implementation works for any particular type is decided at runtime when the concrete type is substituted for its parameter.

C++ templates offer a similar functionality without the runtime overhead of dynamic polymorphism. The tradeoff is the fact that the flexibility is fixed at compile time.

Type classes in Haskell allow us to define different behaviors for the same function for different types. In C++, we do this using template specialization...

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