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Functional Python Programming

You're reading from   Functional Python Programming Discover the power of functional programming, generator functions, lazy evaluation, the built-in itertools library, and monads

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788627061
Length 408 pages
Edition 2nd Edition
Languages
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Toc

Table of Contents (18) Chapters Close

Preface 1. Understanding Functional Programming 2. Introducing Essential Functional Concepts FREE CHAPTER 3. Functions, Iterators, and Generators 4. Working with Collections 5. Higher-Order Functions 6. Recursions and Reductions 7. Additional Tuple Techniques 8. The Itertools Module 9. More Itertools Techniques 10. The Functools Module 11. Decorator Design Techniques 12. The Multiprocessing and Threading Modules 13. Conditional Expressions and the Operator Module 14. The PyMonad Library 15. A Functional Approach to Web Services 16. Optimizations and Improvements 17. Other Books You May Enjoy

Implementing simulation with monads


Monads are expected to pass through a kind of pipeline: a monad will be passed as an argument to a function and a similar monad will be returned as the value of the function. The functions must be designed to accept and return similar structures.

We'll look at a simple pipeline that can be used for simulation of a process. This kind of simulation may be a formal part of a Monte Carlo simulation. We'll take the phrase Monte Carlo simulation literally and simulate a casino dice game, Craps. This involves some stateful rules for a fairly complex simulation.

There is some strange gambling terminology involved, for which we apologize. Craps involves someone rolling the dice (a shooter) and additional bettors. The game has two phases of play:

  • The first roll of the dice is called a come out roll. There are three conditions:
    • If the dice total is 7 or 11, the shooter wins. Anyone betting on the pass line will be paid off as a winner, and all other bets lose. The game...
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