You are previewing Functional Programming in C#: Classic Programming Techniques for Modern Projects.

Functional Programming in C#: Classic Programming Techniques for Modern Projects

  1. Cover
  2. Title
  3. Copyright
  4. About the Author
  5. Credits
  6. Contents
  7. Introduction
  8. Part I : Introduction to Functional Programming
    1. Chapter 1 : A Look at Functional Programming History
      1. What Is Functional Programming?
      2. Functional Languages
      3. The Relationship to Object Oriented Programming
      4. Summary
    2. Chapter 2 : Putting Functional Programming into a Modern Context
      1. Managing Side Effects
      2. Agile Programming Methodologies
      3. Declarative Programming
      4. Functional Programming Is a Mindset
      5. Is Functional Programming in C# a Good Idea?
      6. Summary
  9. Part II : C# Foundations of Functional Programming
    1. Chapter 3 : Functions, Delegates, and Lambda Expressions
      1. Functions and Methods
      2. Reusing Functions
      3. Anonymous Functions and Lambda Expressions
      4. Extension Methods
      5. Referential Transparency
      6. Summary
    2. Chapter 4 : Flexible Typing with Generics
      1. Generic Functions
      2. Generic Classes
      3. Constraining Types
      4. Other Generic Types
      5. Covariance and Contravariance
      6. Summary
    3. Chapter 5 : Lazy Listing with Iterators
      1. The Meaning of Laziness
      2. Enumerating Things with .NET
      3. Implementing Iterator Functions
      4. Chaining Iterators
      5. Summary
    4. Chapter 6 : Encapsulating Data in Closures
      1. Constructing Functions Dynamically
      2. The Problem with Scope
      3. How Closures Work
      4. Summary
    5. Chapter 7 : Code Is Data
      1. Expression Trees in .NET
      2. Analyzing Expressions
      3. Generating Expressions
      4. .NET 4.0 Specifics
      5. Summary
  10. Part III : Implementing Well-known Functional Techniques in C#
    1. Chapter 8 : Currying and Partial Application
      1. Decoupling Parameters
      2. Calling Parts of Functions
      3. Why Parameter Order Matters
      4. Summary
    2. Chapter 9 : Lazy Evaluation
      1. What’s Good about Being Lazy?
      2. Passing Functions
      3. Explicit Lazy Evaluation
      4. Comparing the Lazy Evaluation Techniques
      5. How Lazy Can You Be?
      6. Summary
    3. Chapter 10 : Caching Techniques
      1. The Need to Remember
      2. Precomputation
      3. Memoization
      4. Summary
    4. Chapter 11 : Calling Yourself
      1. Recursion in C#
      2. Tail Recursion
      3. Accumulator Passing Style
      4. Continuation Passing Style
      5. Indirect Recursion
      6. Summary
    5. Chapter 12 : Standard Higher Order Functions
      1. Applying Operations: Map
      2. Map, Filter, and Fold in LINQ
      3. Standard Higher Order Functions
      4. Summary
    6. Chapter 13 : Sequences
      1. Understanding List Comprehensions
      2. A Functional Approach to Iterators
      3. Ranges
      4. Restrictions
      5. Summary
    7. Chapter 14 : Constructing Functions from Functions
      1. Composing Functions
      2. Advanced Partial Application
      3. Combining Approaches
      4. Summary
    8. Chapter 15 : Optional Values
      1. The Meaning of Nothing
      2. Implementing Option(al) Values
      3. Summary
    9. Chapter 16 : Keeping Data from Changing
      1. Change Is Good — not!
      2. False Assumptions
      3. Implementing Immutable Container Data Structures
      4. Alternatives to Persistent Data Types
      5. Summary
    10. Chapter 17 : Monads
      1. What’s in a Typeclass?
      2. What’s in a Monad?
      3. Why Do a Whole Abstraction?
      4. A Second Monad: Logging
      5. Syntactic Sugar
      6. Binding with SelectMany?
      7. Summary
  11. Part IV : Putting Functional Programming into Action
    1. Chapter 18 : Integrating Functional Programming Approaches
      1. Refactoring
      2. Writing New Code
      3. Finding Likely Candidates for Functional Programming
      4. Summary
    2. Chapter 19 : The MapReduce Pattern
      1. Implementing MapReduce
      2. Abstracting the Problem
      3. Summary
    3. Chapter 20 : Applied Functional Modularization
      1. Executing SQL Code from an Application
      2. Rewriting the Function with Partial Application and Precomputation in Mind
      3. Summary
    4. Chapter 21 : Existing Projects Using Functional Techniques
      1. The .NET Framework
      2. LINQ
      3. Google MapReduce and Its Implementations
      4. NUnit
      5. Summary
  12. Index
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WHAT’S IN A TYPECLASS?

Monads are an advanced abstraction mechanism, and the abstraction in Haskell is based on the idea of typeclasses (typeclasses, not type classes). Typeclasses are an abstraction that C# and many other object oriented languages don’t have. Look at the following examples to understand what they do.

Say you have your own data type — a discriminated union in Haskell, very similar to an enum in .NET:

data Food = Pasta | Pizza | Chips

You also have a function that can check whether two given values of type Food are considered equal:

isEqualFood :: Food -> Food -> Bool

isEqualFood Pasta Pasta = True

isEqualFood Pizza Pizza = True

isEqualFood Chips Chips = True

isEqualFood _ _ = False

The variations of the function declare the three special cases explicitly in which the two given parameters are the same — in these cases the result is True. In all other cases, denoted by the use of the wildcard operator _, the result is False.

Using the function on a Haskell console at this stage would render these results:

Main> isEqualFood Pizza Chips

False

Main> isEqualFood Pizza Pizza

True

Main>

Of course, a check for equality of two values is something you want to be able to do with most data types. In other words, there is a group, a class of types, for which comparing for equality makes sense. In Haskell, a typeclass can be used to describe that class of types. Here’s how a typeclass for the purpose of equality comparison could be written:

class MyEq a where

  isEqual ...

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