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Programming Scala

Cover of Programming Scala by Dean Wampler... Published by O'Reilly Media, Inc.
  1. Programming Scala
    1. SPECIAL OFFER: Upgrade this ebook with O’Reilly
    2. A Note Regarding Supplemental Files
    3. Foreword
    4. Preface
      1. Welcome to Programming Scala
      2. Conventions Used in This Book
      3. Using Code Examples
      4. Safari® Books Online
      5. How to Contact Us
      6. Acknowledgments
    5. 1. Zero to Sixty: Introducing Scala
      1. Why Scala?
      2. Installing Scala
      3. For More Information
      4. A Taste of Scala
      5. A Taste of Concurrency
      6. Recap and What’s Next
    6. 2. Type Less, Do More
      1. In This Chapter
      2. Semicolons
      3. Variable Declarations
      4. Method Declarations
      5. Inferring Type Information
      6. Literals
      7. Tuples
      8. Option, Some, and None: Avoiding nulls
      9. Organizing Code in Files and Namespaces
      10. Importing Types and Their Members
      11. Abstract Types And Parameterized Types
      12. Reserved Words
      13. Recap and What’s Next
    7. 3. Rounding Out the Essentials
      1. Operator? Operator?
      2. Methods Without Parentheses and Dots
      3. Domain-Specific Languages
      4. Scala if Statements
      5. Scala for Comprehensions
      6. Other Looping Constructs
      7. Conditional Operators
      8. Pattern Matching
      9. Enumerations
      10. Recap and What’s Next
    8. 4. Traits
      1. Introducing Traits
      2. Stackable Traits
      3. Constructing Traits
      4. Recap and What’s Next
    9. 5. Basic Object-Oriented Programming in Scala
      1. Class and Object Basics
      2. Parent Classes
      3. Constructors in Scala
      4. Nested Classes
      5. Visibility Rules
      6. Recap and What’s Next
    10. 6. Advanced Object-Oriented Programming In Scala
      1. Overriding Members of Classes and Traits
      2. Companion Objects
      3. Case Classes
      4. Equality of Objects
      5. Recap and What’s Next
    11. 7. The Scala Object System
      1. The Predef Object
      2. Classes and Objects: Where Are the Statics?
      3. Sealed Class Hierarchies
      4. The Scala Type Hierarchy
      5. Linearization of an Object’s Hierarchy
      6. Recap and What’s Next
    12. 8. Functional Programming in Scala
      1. What Is Functional Programming?
      2. Functional Programming in Scala
      3. Recursion
      4. Tail Calls and Tail-Call Optimization
      5. Functional Data Structures
      6. Traversing, Mapping, Filtering, Folding, and Reducing
      7. Pattern Matching
      8. Partial Functions
      9. Currying
      10. Implicits
      11. Implicit Function Parameters
      12. Call by Name, Call by Value
      13. Lazy Vals
      14. Recap: Functional Component Abstractions
    13. 9. Robust, Scalable Concurrency with Actors
      1. The Problems of Shared, Synchronized State
      2. Actors
      3. Actors in Scala
      4. Traditional Concurrency in Scala: Threading and Events
      5. Recap and What’s Next
    14. 10. Herding XML in Scala
      1. Reading XML
      2. Writing XML
      3. Recap and What’s Next
    15. 11. Domain-Specific Languages in Scala
      1. Internal DSLs
      2. External DSLs with Parser Combinators
      3. Recap and What’s Next
    16. 12. The Scala Type System
      1. Reflecting on Types
      2. Understanding Parameterized Types
      3. Variance Under Inheritance
      4. Type Bounds
      5. Nothing and Null
      6. Understanding Abstract Types
      7. Path-Dependent Types
      8. Value Types
      9. Self-Type Annotations
      10. Structural Types
      11. Existential Types
      12. Infinite Data Structures and Laziness
      13. Recap and What’s Next
    17. 13. Application Design
      1. Annotations
      2. Enumerations Versus Pattern Matching
      3. Thoughts On Annotations and Enumerations
      4. Using Nulls Versus Options
      5. Exceptions and the Alternatives
      6. Scalable Abstractions
      7. Effective Design of Traits
      8. Design Patterns
      9. Better Design with Design By Contract
      10. Recap and What’s Next
    18. 14. Scala Tools, Libraries, and IDE Support
      1. Command-Line Tools
      2. Build Tools
      3. Integration with IDEs
      4. Test-Driven Development in Scala
      5. Other Notable Scala Libraries and Tools
      6. Java Interoperability
      7. Java Library Interoperability
      8. Recap and What’s Next
    19. A. References
    20. Glossary
    21. Index
    22. About the Authors
    23. Colophon
    24. SPECIAL OFFER: Upgrade this ebook with O’Reilly
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Infinite Data Structures and Laziness

We described lazy values in Chapter 8. In functional languages that are lazy by default, like Haskell, laziness makes it easy to support infinite data structures.

For example, consider the following Scala method fib that calculates the Fibonacci number for n in the infinite Fibonacci sequence:

def fib(n: Int): Int = n match {
  case 0 | 1 => n
  case _ => fib(n-1) + fib(n-2)
}

If Scala were purely lazy, we could imagine a definition of the Fibonacci sequence like the following and it wouldn’t create an infinite loop:

fibonacci_sequence = for (i <- 0 to infinity) yield fib(i)

Scala isn’t lazy by default (and there is no infinity value or keyword…), but the library contains a Stream class that supports lazy evaluation and hence it can support infinite data structures. We’ll show an implementation of the Fibonacci sequence in a moment. First, here is a simpler example that uses streams to represent all positive integers, all positive odd integers, and all positive even integers:

// code-examples/TypeSystem/lazy/lazy-ints-script.scala

def from(n: Int): Stream[Int] = Stream.cons(n, from(n+1))

lazy val ints = from(0)
lazy val odds = ints.filter(_ % 2 == 1)
lazy val evens = ints.filter(_ % 2 == 0)

odds.take(10).print
evens.take(10).print

It produces this output:

1, 3, 5, 7, 9, 11, 13, 15, 17, 19, Stream.empty
0, 2, 4, 6, 8, 10, 12, 14, 16, 18, Stream.empty

The from method is recursive and never terminates! We use it to define the ints by calling from(0). Streams.cons ...

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