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Swift Functional Programming

Swift Functional Programming

By : Nayebi
4.3 (3)
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Swift Functional Programming

Swift Functional Programming

4.3 (3)
By: Nayebi

Overview of this book

Swift is a multi-paradigm programming language enabling you to tackle different problems in various ways. Understanding each paradigm and knowing when and how to utilize and combine them can lead to a better code base. Functional programming (FP) is an important paradigm that empowers us with declarative development and makes applications more suitable for testing, as well as performant and elegant. This book aims to simplify the FP paradigms, making them easily understandable and usable, by showing you how to solve many of your day-to-day development problems using Swift FP. It starts with the basics of FP, and you will go through all the core concepts of Swift and the building blocks of FP. You will also go through important aspects, such as function composition and currying, custom operator definition, monads, functors, applicative functors,memoization, lenses, algebraic data types, type erasure, functional data structures, functional reactive programming (FRP), and protocol-oriented programming(POP). You will then learn to combine those techniques to develop a fully functional iOS application from scratch
Table of Contents (12 chapters)
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Trees


In computer science, a Tree is a very popular abstract data type (ADT) or a data structure implementing this ADT that simulates a hierarchical Tree structure with a root value and subtrees of the children with a parent node, represented as a set of linked nodes.

A Tree data structure can be defined recursively (locally) as a collection of nodes (starting at a root node), where each node is a data structure consisting of a value, together with a list of references to nodes (the children) with the constraints that no reference is duplicated and none point to the root.

Alternatively, a Tree can be defined abstractly as a whole (globally) as an ordered Tree, with a value assigned to each node. Both these perspectives are useful: while a Tree can be analyzed mathematically as a whole, when actually represented as a data structure, it is usually represented and worked separately by a node (rather than as a list of nodes and an adjacency list of edges between nodes, as one may represent a digraph...

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