دانلود کتاب Mastering JavaScript Functional Programming: Write clean, robust, and maintainable web and server code using functional JavaScript and TypeScript

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Cover Title Page Copyright and Credits Contributors About the reviewers Table of Contents Preface Chapter 1: Becoming Functional – Several Questions What is functional programming? Theory versus practice A different way of thinking FP and other programming paradigms What FP is not Why use FP? What we need What we get Not all is gold Is JavaScript functional? JavaScript as a tool Going functional with JavaScript Key features of JavaScript How do we work with JavaScript? Using transpilers Working online A step further – TypeScript Testing Summary Questions Chapter 2: Thinking Functionally – A First Example Our problem – doing something only once Solution 1 – hoping for the best! Solution 2 – using a global flag Solution 3 – removing the handler Solution 4 – changing the handler Solution 5 – disabling the button Solution 6 – redefining the handler Solution 7 – using a local flag A functional solution to our problem A higher-order solution Testing the solution manually Testing the solution automatically Producing an even better solution Summary Questions Chapter 3: Starting Out with Functions – A Core Concept All about functions Of lambdas and functions Arrow functions – the modern way Functions as objects Using functions in FP ways Injection – sorting it out Callbacks and promises Continuation-passing style Polyfills Stubbing Immediate invocation (IIFE) Summary Questions Chapter 4: Behaving Properly – Pure Functions Pure functions Referential transparency Side effects Advantages of pure functions Impure functions Avoiding impure functions Is your function pure? Testing – pure versus impure Testing pure functions Testing purified functions Testing impure functions Summary Questions Chapter 5: Programming Declaratively – A Better Style Transformations Reducing an array to a value Applying an operation – map() Dealing with arrays of arrays More general looping Logical HOFs Filtering an array Searching an array Higher-level predicates – every() and some() Checking negatives – none() Working with async functions Some strange behaviors Async-ready looping Working with parallel functions Unresponsive pages A frontend worker A backend worker Workers, FP style Long-living pooled workers Summary Questions Chapter 6: Producing Functions – Higher-Order Functions Wrapping functions – keeping behavior Logging Timing functions Memoizing functions Altering a function’s behavior Doing things once, revisited Logically negating a function Inverting the results Arity changing Throttling and debouncing Changing functions in other ways Turning operations into functions Turning functions into promises Getting a property from an object Demethodizing – turning methods into functions Methodizing – turning functions into methods Finding the optimum Summary Questions Chapter 7: Transforming Functions – Currying and Partial Application A bit of theory Currying Dealing with many parameters Currying by hand Currying with bind() Partial application Partial application with arrow functions Partial application with closures Partial currying Partial currying with bind() Partial currying with closures Final thoughts Variable number of parameters Parameter order Being functional Summary Questions Chapter 8: Connecting Functions – Pipelining, Composition, and More Pipelining Piping in Unix/Linux Revisiting an example Creating pipelines Debugging pipelines Pointfree style Chaining and fluent interfaces An example of fluent APIs Chaining method calls Composing Some examples of composition Composing with higher-order functions Transducing Composing reducers Generalizing for all reducers Testing connected functions Testing pipelined functions Testing composed functions Testing chained functions Testing transduced functions Summary Questions Chapter 9: Designing Functions – Recursion Using recursion Thinking recursively Higher-order functions revisited Searching and backtracking Mutual recursion Odds and evens Doing arithmetic Recursion techniques Tail call optimization Continuation-passing style Trampolines and thunks Recursion elimination Summary Questions Chapter 10: Ensuring Purity – Immutability Going the straightforward JavaScript way Mutator functions Constants Freezing Cloning and mutating Getters and setters Lenses Prisms Creating persistent data structures Working with lists Updating objects A final caveat Summary Questions Chapter 11: Implementing Design Patterns – The Functional Way Understanding design patterns Design pattern categories Do we need design patterns? Object-oriented design patterns Facade and Adapter Decorator or Wrapper Strategy, Template, and Command Dependency Injection Observers and reactive programming Other patterns Functional design patterns Summary Questions Chapter 12: Building Better Containers – Functional Data Types Specifying data types Signatures for functions Other data type options Building containers Extending current data types Containers and functors Monads Functions as data structures Binary trees in Haskell Functions as binary trees Summary Questions Answers to Questions Chapter 1, Becoming Functional – Several Questions Chapter 2, Thinking Functionally – A First Example Chapter 3, Starting Out with Functions – A Core Concept Chapter 4, Behaving Properly – Pure Functions Chapter 5, Programming Declaratively – A Better Style Chapter 6, Producing Functions – Higher-Order Functions Chapter 7, Transforming Functions – Currying and Partial Application Chapter 8, Connecting Functions – Pipelining, Composition, and More Chapter 9, Designing Functions – Recursion Chapter 10, Ensuring Purity – Immutability Chapter 11, Implementing Design Patterns – The Functional Way Chapter 12, Building Better Containers – Functional Data Types Bibliography Index Other Books You May Enjoy