Haskell Tutorial and Cookbook
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Haskell Tutorial and Cookbook

About the Book

Note: the second edition was released August 6, 2019. There is a free upgrade for readers who purchased the first edition. This book (and all of my Leanpub books) are also available for free on my web site https://markwatson.com/books/ if you would like them for free.

Functional programming is the paradigm that is replacing object oriented methodologies. The Haskell language has several advantages for functional programming: the language is mature, is supported by many libraries and development tools, and compiles to compact and efficient executable programs that can be "single file" deployed.

Haskell does have a steep learning curve in general but in this book I show you a small but effective subset of Haskell that will get you started quickly.

This book also provides something for more experienced Haskell developers: new ideas for Haskell applications and example code that is likely to be useful for your own projects.

The first section of this book contains two chapters:

  • A tutorial on pure Haskell development: no side effects.
  • A tutorial on impure Haskell development: dealing with the world (I/O, network access, database access, etc.)

After working through these tutorial chapters you will understand enough of Haskell development to understand and be able to modify for your own use the cookbook examples in the second section. Some of the general topics will be covered again in the second book section that contains longer sample applications. For example, you will learn the basics for interacting with Sqlite and Postgres databases in the tutorial on impure Haskell code but you will see a much longer example later in the book when I provide code for a Blackjack playing program.

The second section of this book contains the following recipes implemented as complete programs:

  • Textprocessing CSV Files
  • Textprocessing JSON Files
  • Natural Language Processing (NLP) tools
  • Client and Server network programming examples
  • Access data on the Web using scraping and by querying Semantic Web RDF Data Sources
  • Annotating English text with Wikipedia/DBPedia URIs for entities in the original text. Entities can be people, places, organizations, etc.
  • Using sqlite and Postgres databases.
  • Play a simple form of the Blackjack card game.

The third section (added for the second edition) contains:

  • Automatic generation of Knowledge Graphs
  • Hybrid Haskell + Python NLP examples

All of my Leanpub books, including this book, can be read for FREE on my web site: https://markwatson.com/

About the Author

Mark Watson
Mark Watson

Mark Watson is a consultant specializing in deep learning, machine learning, knowledge graphs, and general artificial intelligence software development. He uses Common Lisp, Clojure, Python, Java, Haskell, and Ruby for development.

He is the author of 20+ published books on Artificial Intelligence, Deep Learning, Java, Ruby, Machine Learning, Common LISP, Clojure, JavaScript, Semantic Web, NLP, C++, Linux, and Scheme. He has 55 US Patents.

Mark's consulting customer list includes: Google, Capital One, Olive AI, CompassLabs, Disney, Sitescout.com, Embed.ly, and Webmind Corporation.

All of my Leanpub books are available to read for free on my web site:  https://markwatson.com/

Table of Contents

  • Cover Material, Copyright, and License
  • Preface
    • Additional Material in the Second Edition
    • A Request from the Author
    • Structure of the Book
    • Code Examples
    • Functional Programming Requires a Different Mind Set
    • eBooks Are Living Documents
    • Setting Up Your Development Environment
    • Why Haskell?
    • Enjoy Yourself
    • Acknowledgements
  • Section 1 - Tutorial
  • Tutorial on Pure Haskell Programming
    • Interactive GHCi Shell
    • Introduction to Haskell Types
    • Functions Are Pure
    • Using Parenthesis or the Special $ Character and Operator Precedence
    • Lazy Evaluation
    • Understanding List Comprehensions
    • Haskell Rules for Indenting Code
    • Understanding let and where
    • Conditional do Expressions and Anonymous Functions
    • Maps
    • Sets
    • More on Functions
    • Comments on Dealing With Immutable Data and How to Structure Programs
    • Error Handling
    • Testing Haskell Code
    • Pure Haskell Wrap Up
  • Tutorial on Impure Haskell Programming
    • Hello IO () Monad
    • A Note About >> and >>= Operators
    • Console IO Example with Stack Configuration
    • File IO
    • Error Handling in Impure Code
    • Network IO
    • A Haskell Game Loop that Maintains State Functionally
    • A More Detailed Look at Monads
    • Using Applicative Operators <$> and <*>: Finding Common Words in Files
    • List Comprehensions Using the do Notation
    • Dealing With Time
    • Using Debug.Trace
    • Wrap Up
  • Section 2 - Cookbook
  • Text Processing
    • CSV Spreadsheet Files
    • JSON Data
    • Cleaning Natural Language Text
  • Natural Language Processing Tools
    • Resolve Entities in Text to DBPedia URIs
    • Bag of Words Classification Model
    • Text Summarization
    • Part of Speech Tagging
    • Natural Language Processing Wrap Up
  • Linked Data and the Semantic Web
    • The SPARQL Query Language
    • A Haskell HTTP Based SPARQL Client
    • Querying Remote SPARQL Endpoints
    • Linked Data and Semantic Web Wrap Up
  • Web Scraping
    • Using the Wreq Library
    • Using the HandsomeSoup Library for Parsing HTML
    • Web Scraping Wrap Up
  • Using Relational Databases
    • Database Access for Sqlite
    • Database Access for Postgres
  • Haskell Program to Play the Blackjack Card Game
  • Section 3 - Larger Projects
  • Knowledge Graph Creator
    • Code Layout For the KGCreator Project and strategies for sharing Haskell code between projects
    • The Main Event: Detecting Entities in Text
    • Utility Code for Generating RDF
    • Utility Code for Generating Cypher Input Data for Neo4J
    • Top Level API Code for Handling Knowledge Graph Data Generation
    • Wrapup for Automating the Creation of Knowledge Graphs
  • Hybrid Haskell and Python Natural Language Processing
    • Example Use of the Haskell NLP Client
    • Setting up the Python NLP Server
    • Understanding the Haskell NLP Client Code
    • Wrapup for Using the Python SpaCy NLP Service
  • Hybrid Haskell and Python For Coreference Resolution
    • Installing the Python Coreference Server
    • Understanding the Haskell Coreference Client Code
    • Wrapup for Using the Python Coreference NLP Service
  • Book Wrap Up
  • Appendix A - Haskell Tools Setup
    • stack
    • Emacs Setup
    • Do you want more of an IDE-like Development Environment?
    • hlint

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