Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
Arrow up icon
GO TO TOP
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

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

Table of Contents (22) Chapters Close

Title Page
Packt Upsell
Contributors
Preface
1. Understanding Functional Programming FREE CHAPTER 2. Introducing Essential Functional Concepts 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 1. Other Books You May Enjoy Index

What concurrency really means


In a small computer, with a single processor and a single core, all evaluations are serialized through the one and only core of the processor. The use OS throughout will interleave multiple processes and multiple threads through clever time-slicing arrangements.

On a computer with multiple CPUs or multiple cores in a single CPU, there can be some actual concurrent processing of CPU instructions. All other concurrency is simulated through time slicing at the OS level. A macOS X laptop can have 200 concurrent processes that share the CPU; this is many more processes than the number of available cores. From this, we can see that OS time slicing is responsible for most of the apparently concurrent behavior of the system as a whole.

The boundary conditions

Let's consider a hypothetical algorithm that has a complexity described by 

. Assume that there is an inner loop that involves 1,000 bytes of Python code. When processing 10,000 objects, we're executing 100 billion...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $15.99/month. Cancel anytime
Visually different images