Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Learn Python Programming, 3rd edition

You're reading from   Learn Python Programming, 3rd edition An in-depth introduction to the fundamentals of Python

Arrow left icon
Product type Paperback
Published in Oct 2021
Publisher Packt
ISBN-13 9781801815093
Length 554 pages
Edition 3rd Edition
Languages
Tools
Arrow right icon
Authors (2):
Arrow left icon
Heinrich Kruger Heinrich Kruger
Author Profile Icon Heinrich Kruger
Heinrich Kruger
Fabrizio Romano Fabrizio Romano
Author Profile Icon Fabrizio Romano
Fabrizio Romano
Arrow right icon
View More author details
Toc

Table of Contents (18) Chapters Close

Preface 1. A Gentle Introduction to Python 2. Built-In Data Types FREE CHAPTER 3. Conditionals and Iteration 4. Functions, the Building Blocks of Code 5. Comprehensions and Generators 6. OOP, Decorators, and Iterators 7. Exceptions and Context Managers 8. Files and Data Persistence 9. Cryptography and Tokens 10. Testing 11. Debugging and Profiling 12. GUIs and Scripting 13. Data Science in Brief 14. Introduction to API Development 15. Packaging Python Applications 16. Other Books You May Enjoy
17. Index

What are the drawbacks?

Probably, the only drawback that one could find in Python, which is not due to personal preferences, is its execution speed. Typically, Python is slower than its compiled siblings. The standard implementation of Python produces, when you run an application, a compiled version of the source code called byte code (with the extension .pyc), which is then run by the Python interpreter. The advantage of this approach is portability, which we pay for with increased runtimes due to the fact that Python is not compiled down to the machine level, as other languages are.

Despite this, Python speed is rarely a problem today, hence its wide use regardless of this aspect. What happens is that, in real life, hardware cost is no longer a problem, and usually it's easy enough to gain speed by parallelizing tasks. Moreover, many programs spend a great proportion of the time waiting for I/O operations to complete; therefore, the raw execution speed is often a secondary...

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 $19.99/month. Cancel anytime
Banner background image