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Functional Python Programming

You're reading from   Functional Python Programming Create succinct and expressive implementations with functional programming in Python

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781784396992
Length 360 pages
Edition 1st Edition
Languages
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Author (1):
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Steven F. Lott Steven F. Lott
Author Profile Icon Steven F. Lott
Steven F. Lott
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Table of Contents (18) Chapters Close

Preface 1. Introducing Functional Programming FREE CHAPTER 2. Introducing Some Functional Features 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 Index

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 some Monte Carlo simulation. We'll take the Monte Carlo simulation literally and simulate a casino dice game, Craps. This involves what might be thought of as stateful rules for a fairly complex simulation.

There's a lot of very strange gambling terminology involved. We can't provide much background about the various buzzwords involved. In some cases, the origins are lost in history.

Craps involves someone rolling the dice (a shooter) and additional bettors. The game works like this:

The first roll is called a come out roll. There are three conditions:

  1. If the...
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