Hi guys, here we are for the second issue of our new monthly newsletter! This month I have chosen for you four links that I have found very interesting. The first two links are for Pythonistas who want to improve their Python knowledge and are about concurrency in Python and how to implement the Factory method design pattern. The third link will teach you a weird aspect of Python that I'm sure you didn't know about and the fourth link is about memory management and why you should be aware of if even when you're working with a language like Python.
Enjoy this month's selection and ... happy Pythoning guys!
Guide to Concurrency in Python with Asyncio Author: Mark McDonnell Audience Level: Intermediate
Let's face it: the only code that is really scalable is the one who works asynchronously, and this article is a quick introduction to asynchronous code in Python. So if you have asked yourself what are coroutines, event loops, tasks, and futures here you will find all the information you need!
The Factory Method Pattern and Its Implementation in Python Author: Isaac Rodriguez Audience Level: Beginner / Intermediate
Right from my friends at Real Python here we have a great article about the Pythonic implementation of one of the most important patterns for every OOP developer: the Factory Method Pattern.
If you like the article and you want to find out more about design patterns in OOP programming, my suggestion is to have a look at the "Design Patterns: Elements of Reusable Object-Oriented Software" book from the so-called Gang of four. The book can be found on Amazon and even if it is quite old (1995), the patterns contained are still invaluable content for OOP developers. Please, before buying the book, consider that the examples contained are in C++, even if the patterns described can be used in any OOP programming language.
Python WAT!? Integer Cache Author: Will Vincent Audience Level: Beginner / Intermediate
Did you know that Python caches integers in the range [-5, 256]? Well neither did I, so this article is for you! :)
Clinging to memory: how Python function calls can increase your memory usage Author: Itamar Turner-Trauring Audience Level: Intermediate / Advanced
Do the way you write your code affect the memory footprint of your application? Of course, it does! And in this article, you will have a closer look at it.