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Real World Haskell

Cover of Real World Haskell by John Goerzen... Published by O'Reilly Media, Inc.
  1. Real World Haskell
    1. SPECIAL OFFER: Upgrade this ebook with O’Reilly
    2. A Note Regarding Supplemental Files
    3. Preface
      1. Have We Got a Deal for You!
      2. What to Expect from This Book
      3. What to Expect from Haskell
      4. A Brief Sketch of Haskell’s History
      5. Helpful Resources
      6. Conventions Used in This Book
      7. Using Code Examples
      8. Safari® Books Online
      9. How to Contact Us
      10. Acknowledgments
    4. 1. Getting Started
      1. Your Haskell Environment
      2. Getting Started with ghci, the Interpreter
      3. Basic Interaction: Using ghci as a Calculator
      4. Command-Line Editing in ghci
      5. Lists
      6. Strings and Characters
      7. First Steps with Types
      8. A Simple Program
    5. 2. Types and Functions
      1. Why Care About Types?
      2. Haskell’s Type System
      3. What to Expect from the Type System
      4. Some Common Basic Types
      5. Function Application
      6. Useful Composite Data Types: Lists and Tuples
      7. Functions over Lists and Tuples
      8. Function Types and Purity
      9. Haskell Source Files, and Writing Simple Functions
      10. Understanding Evaluation by Example
      11. Polymorphism in Haskell
      12. The Type of a Function of More Than One Argument
      13. Why the Fuss over Purity?
      14. Conclusion
    6. 3. Defining Types, Streamlining Functions
      1. Defining a New Data Type
      2. Type Synonyms
      3. Algebraic Data Types
      4. Pattern Matching
      5. Record Syntax
      6. Parameterized Types
      7. Recursive Types
      8. Reporting Errors
      9. Introducing Local Variables
      10. The Offside Rule and Whitespace in an Expression
      11. The case Expression
      12. Common Beginner Mistakes with Patterns
      13. Conditional Evaluation with Guards
    7. 4. Functional Programming
      1. Thinking in Haskell
      2. A Simple Command-Line Framework
      3. Warming Up: Portably Splitting Lines of Text
      4. Infix Functions
      5. Working with Lists
      6. How to Think About Loops
      7. Anonymous (lambda) Functions
      8. Partial Function Application and Currying
      9. As-patterns
      10. Code Reuse Through Composition
      11. Tips for Writing Readable Code
      12. Space Leaks and Strict Evaluation
    8. 5. Writing a Library: Working with JSON Data
      1. A Whirlwind Tour of JSON
      2. Representing JSON Data in Haskell
      3. The Anatomy of a Haskell Module
      4. Compiling Haskell Source
      5. Generating a Haskell Program and Importing Modules
      6. Printing JSON Data
      7. Type Inference Is a Double-Edged Sword
      8. A More General Look at Rendering
      9. Developing Haskell Code Without Going Nuts
      10. Pretty Printing a String
      11. Arrays and Objects, and the Module Header
      12. Writing a Module Header
      13. Fleshing Out the Pretty-Printing Library
      14. Creating a Package
      15. Practical Pointers and Further Reading
    9. 6. Using Typeclasses
      1. The Need for Typeclasses
      2. What Are Typeclasses?
      3. Declaring Typeclass Instances
      4. Important Built-in Typeclasses
      5. Automatic Derivation
      6. Typeclasses at Work: Making JSON Easier to Use
      7. Living in an Open World
      8. How to Give a Type a New Identity
      9. JSON Typeclasses Without Overlapping Instances
      10. The Dreaded Monomorphism Restriction
      11. Conclusion
    10. 7. I/O
      1. Classic I/O in Haskell
      2. Working with Files and Handles
      3. Extended Example: Functional I/O and Temporary Files
      4. Lazy I/O
      5. The IO Monad
      6. Is Haskell Really Imperative?
      7. Side Effects with Lazy I/O
      8. Buffering
      9. Reading Command-Line Arguments
      10. Environment Variables
    11. 8. Efficient File Processing, Regular Expressions, and Filename Matching
      1. Efficient File Processing
      2. Filename Matching
      3. Regular Expressions in Haskell
      4. More About Regular Expressions
      5. Translating a glob Pattern into a Regular Expression
      6. An important Aside: Writing Lazy Functions
      7. Making Use of Our Pattern Matcher
      8. Handling Errors Through API Design
      9. Putting Our Code to Work
    12. 9. I/O Case Study: A Library for Searching the Filesystem
      1. The find Command
      2. Starting Simple: Recursively Listing a Directory
      3. A Naive Finding Function
      4. Predicates: From Poverty to Riches, While Remaining Pure
      5. Sizing a File Safely
      6. A Domain-Specific Language for Predicates
      7. Controlling Traversal
      8. Density, Readability, and the Learning Process
      9. Another Way of Looking at Traversal
      10. Useful Coding Guidelines
    13. 10. Code Case Study: Parsing a Binary Data Format
      1. Grayscale Files
      2. Parsing a Raw PGM File
      3. Getting Rid of Boilerplate Code
      4. Implicit State
      5. Introducing Functors
      6. Writing a Functor Instance for Parse
      7. Using Functors for Parsing
      8. Rewriting Our PGM Parser
      9. Future Directions
    14. 11. Testing and Quality Assurance
      1. QuickCheck: Type-Based Testing
      2. Testing Case Study: Specifying a Pretty Printer
      3. Measuring Test Coverage with HPC
    15. 12. Barcode Recognition
      1. A Little Bit About Barcodes
      2. Introducing Arrays
      3. Encoding an EAN-13 Barcode
      4. Constraints on Our Decoder
      5. Divide and Conquer
      6. Turning a Color Image into Something Tractable
      7. What Have We Done to Our Image?
      8. Finding Matching Digits
      9. Life Without Arrays or Hash Tables
      10. Turning Digit Soup into an Answer
      11. Working with Row Data
      12. Pulling It All Together
      13. A Few Comments on Development Style
    16. 13. Data Structures
      1. Association Lists
      2. Maps
      3. Functions Are Data, Too
      4. Extended Example: /etc/passwd
      5. Extended Example: Numeric Types
      6. Taking Advantage of Functions as Data
      7. General-Purpose Sequences
    17. 14. Monads
      1. Revisiting Earlier Code Examples
      2. Looking for Shared Patterns
      3. The Monad Typeclass
      4. And Now, a Jargon Moment
      5. Using a New Monad: Show Your Work!
      6. Mixing Pure and Monadic Code
      7. Putting a Few Misconceptions to Rest
      8. Building the Logger Monad
      9. The Maybe Monad
      10. The List Monad
      11. Desugaring of do Blocks
      12. The State Monad
      13. Monads and Functors
      14. The Monad Laws and Good Coding Style
    18. 15. Programming with Monads
      1. Golfing Practice: Association Lists
      2. Generalized Lifting
      3. Looking for Alternatives
      4. Adventures in Hiding the Plumbing
      5. Separating Interface from Implementation
      6. The Reader Monad
      7. A Return to Automated Deriving
      8. Hiding the IO Monad
    19. 16. Using Parsec
      1. First Steps with Parsec: Simple CSV Parsing
      2. The sepBy and endBy Combinators
      3. Choices and Errors
      4. Extended Example: Full CSV Parser
      5. Parsec and MonadPlus
      6. Parsing a URL-Encoded Query String
      7. Supplanting Regular Expressions for Casual Parsing
      8. Parsing Without Variables
      9. Applicative Functors for Parsing
      10. Applicative Parsing by Example
      11. Parsing JSON Data
      12. Parsing a HTTP Request
    20. 17. Interfacing with C: The FFI
      1. Foreign Language Bindings: The Basics
      2. Regular Expressions for Haskell: A Binding for PCRE
      3. Passing String Data Between Haskell and C
      4. Matching on Strings
    21. 18. Monad Transformers
      1. Motivation: Boilerplate Avoidance
      2. A Simple Monad Transformer Example
      3. Common Patterns in Monads and Monad Transformers
      4. Stacking Multiple Monad Transformers
      5. Moving Down the Stack
      6. Understanding Monad Transformers by Building One
      7. Transformer Stacking Order Is Important
      8. Putting Monads and Monad Transformers into Perspective
    22. 19. Error Handling
      1. Error Handling with Data Types
      2. Exceptions
      3. Error Handling in Monads
    23. 20. Systems Programming in Haskell
      1. Running External Programs
      2. Directory and File Information
      3. Program Termination
      4. Dates and Times
      5. Extended Example: Piping
    24. 21. Using Databases
      1. Overview of HDBC
      2. Installing HDBC and Drivers
      3. Connecting to Databases
      4. Transactions
      5. Simple Queries
      6. SqlValue
      7. Query Parameters
      8. Prepared Statements
      9. Reading Results
      10. Database Metadata
      11. Error Handling
    25. 22. Extended Example: Web Client Programming
      1. Basic Types
      2. The Database
      3. The Parser
      4. Downloading
      5. Main Program
    26. 23. GUI Programming with gtk2hs
      1. Installing gtk2hs
      2. Overview of the GTK+ Stack
      3. User Interface Design with Glade
      4. Event-Driven Programming
      5. Initializing the GUI
      6. The Add Podcast Window
      7. Long-Running Tasks
      8. Using Cabal
    27. 24. Concurrent and Multicore Programming
      1. Defining Concurrency and Parallelism
      2. Concurrent Programming with Threads
      3. Simple Communication Between Threads
      4. The Main Thread and Waiting for Other Threads
      5. Communicating over Channels
      6. Useful Things to Know About
      7. Shared-State Concurrency Is Still Hard
      8. Using Multiple Cores with GHC
      9. Parallel Programming in Haskell
      10. Parallel Strategies and MapReduce
    28. 25. Profiling and Optimization
      1. Profiling Haskell Programs
      2. Controlling Evaluation
      3. Understanding Core
      4. Advanced Techniques: Fusion
    29. 26. Advanced Library Design: Building a Bloom Filter
      1. Introducing the Bloom Filter
      2. Use Cases and Package Layout
      3. Basic Design
      4. The ST Monad
      5. Designing an API for Qualified Import
      6. Creating a Mutable Bloom Filter
      7. The Immutable API
      8. Creating a Friendly Interface
      9. Creating a Cabal Package
      10. Testing with QuickCheck
      11. Performance Analysis and Tuning
    30. 27. Sockets and Syslog
      1. Basic Networking
      2. Communicating with UDP
      3. Communicating with TCP
    31. 28. Software Transactional Memory
      1. The Basics
      2. Some Simple Examples
      3. STM and Safety
      4. Retrying a Transaction
      5. Choosing Between Alternatives
      6. I/O and STM
      7. Communication Between Threads
      8. A Concurrent Web Link Checker
      9. Practical Aspects of STM
    32. A. Installing GHC and Haskell Libraries
      1. Installing GHC
      2. Installing Haskell Software
    33. B. Characters, Strings, and Escaping Rules
      1. Writing Character and String Literals
      2. International Language Support
      3. Escaping Text
    34. Index
    35. About the Authors
    36. Colophon
    37. SPECIAL OFFER: Upgrade this ebook with O’Reilly

What to Expect from Haskell

Haskell is a general-purpose programming language. It was designed without any application niche in mind. Although it takes a strong stand on how programs should be written, it does not favor one problem domain over others.

While at its core, the language encourages a pure, lazy style of functional programming, this is the default, not the only option. Haskell also supports the more traditional models of procedural code and strict evaluation. Additionally, although the focus of the language is squarely on writing statically typed programs, it is possible (though rarely seen) to write Haskell code in a dynamically typed manner.

Compared to Traditional Static Languages

Languages that use simple static type systems have been the mainstay of the programming world for decades. Haskell is statically typed, but its notion of what types are for and what we can do with them is much more flexible and powerful than traditional languages. Types make a major contribution to the brevity, clarity, and efficiency of Haskell programs.

Although powerful, Haskell’s type system is often also unobtrusive. If we omit explicit type information, a Haskell compiler will automatically infer the type of an expression or function. Compared to traditional static languages, to which we must spoon-feed large amounts of type information, the combination of power and inference in Haskell’s type system significantly reduces the clutter and redundancy of our code.

Several of Haskell’s other features combine to further increase the amount of work we can fit into a screenful of text. This brings improvements in development time and agility; we can create reliable code quickly and easily refactor it in response to changing requirements.

Sometimes, Haskell programs may run more slowly than similar programs written in C or C++. For most of the code we write, Haskell’s large advantages in productivity and reliability outweigh any small performance disadvantage.

Multicore processors are now ubiquitous, but they remain notoriously difficult to program using traditional techniques. Haskell provides unique technologies to make multicore programming more tractable. It supports parallel programming, software transactional memory for reliable concurrency, and it scales to hundreds of thousands of concurrent threads.

Compared to Modern Dynamic Languages

Over the past decade, dynamically typed, interpreted languages have become increasingly popular. They offer substantial benefits in developer productivity. Although this often comes at the cost of a huge performance hit, for many programming tasks productivity trumps performance, or performance isn’t a significant factor in any case.

Brevity is one area in which Haskell and dynamically typed languages perform similarly: in each case, we write much less code to solve a problem than in a traditional language. Programs are often around the same size in dynamically typed languages and Haskell.

When we consider runtime performance, Haskell almost always has a huge advantage. Code compiled by the Glasgow Haskell Compiler (GHC) is typically between 20 to 60 times faster than code run through a dynamic language’s interpreter. GHC also provides an interpreter, so you can run scripts without compiling them.

Another big difference between dynamically typed languages and Haskell lies in their philosophies around types. A major reason for the popularity of dynamically typed languages is that only rarely do we need to explicitly mention types. Through automatic type inference, Haskell offers the same advantage.

Beyond this surface similarity, the differences run deep. In a dynamically typed language, we can create constructs that are difficult to express in a statically typed language. However, the same is true in reverse: with a type system as powerful as Haskell’s, we can structure a program in a way that would be unmanageable or infeasible in a dynamically typed language.

It’s important to recognize that each of these approaches involves trade-offs. Very briefly put, the Haskell perspective emphasizes safety, while the dynamically typed outlook favors flexibility. If someone had already discovered one way of thinking about types that was always best, we imagine that everyone would know about it by now.

Of course, we, the authors, have our own opinions about which trade-offs are more beneficial. Two of us have years of experience programming in dynamically typed languages. We love working with them; we still use them every day; but usually, we prefer Haskell.

Haskell in Industry and Open Source

Here are just a few examples of large software systems that have been created in Haskell. Some of these are open source, while others are proprietary products:

  • ASIC and FPGA design software (Lava, products from Bluespec, Inc.)

  • Music composition software (Haskore)

  • Compilers and compiler-related tools (most notably GHC)

  • Distributed revision control (Darcs)

  • Web middleware (HAppS, products from Galois, Inc.)

The following is a sample of some of the companies using Haskell in late 2008, taken from the Haskell wiki:


An international bank. It uses Haskell in investment banking, in order to measure the counterparty risk on portfolios of financial derivatives.


A startup company. It develops multimedia content creation tools using Haskell.


A biotech company. It creates mathematical models and other complex applications in Haskell.


An ASIC and FPGA design software vendor. Its products are developed in Haskell, and the chip design languages that its products provide are influenced by Haskell.


Uses Haskell for the design and verification of hydraulic hybrid vehicle systems.

Compilation, Debugging, and Performance Analysis

For practical work, almost as important as a language itself is the ecosystem of libraries and tools around it. Haskell has a strong showing in this area.

The most widely used compiler, GHC, has been actively developed for over 15 years and provides a mature and stable set of features:

  • Compiles to efficient native code on all major modern operating systems and CPU architectures

  • Easy deployment of compiled binaries, unencumbered by licensing restrictions

  • Code coverage analysis

  • Detailed profiling of performance and memory usage

  • Thorough documentation

  • Massively scalable support for concurrent and multicore programming

  • Interactive interpreter and debugger

Bundled and Third-Party Libraries

The GHC compiler ships with a collection of useful libraries. Here are a few of the common programming needs that these libraries address:

  • File I/O and filesystem traversal and manipulation

  • Network client and server programming

  • Regular expressions and parsing

  • Concurrent programming

  • Automated testing

  • Sound and graphics

The Hackage package database is the Haskell community’s collection of open source libraries and applications. Most libraries published on Hackage are licensed under liberal terms that permit both commercial and open source use. Some of the areas covered by these open source libraries include the following:

  • Interfaces to all major open source and commercial databases

  • XML, HTML, and XQuery processing

  • Network and web client and server development

  • Desktop GUIs, including cross-platform toolkits

  • Support for Unicode and other text encodings

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