Python’s support for static typing gradually improves with each new release of Python. The core features were in place in Python 3.5. Since then, there’ve been many tweaks and improvements to the type hinting system. This evolution continues in Python 3.12, which, in particular, simplifies the typing of generics. In this tutorial, you’ll: Use type variables in Python to annotate generic classes and functions Explore the new syntax for type hinting type variables Model inheritance with the new @override decorator […]

Now that you know what a Python subinterpreter is, you’ll take a look at what’s changing in the upcoming releases of CPython. Most of the subinterpreter changes are described in two proposals, PEP 684 and PEP 554. Only PEP 684 will make it into the 3.12 release. PEP 554 is scheduled for the 3.13 release but hasn’t been officially approved yet. Changes to the Global State and the GIL The main focus of PEP 684 is refactoring the internals of […]

The common advice when Python is too slow is to switch to a low-level compiled language like Cython or Rust. But what do you do if that code is too slow? At that point you might start thinking about parallelism: using multi-threading or multi-processing so you can take advantage of multiple CPU cores. But parallelism comes with its own set of complexities; at the very least, some algorithms can only really work in a single-threaded way. So what can you […]

In this tutorial, you’ll learn various techniques to catch multiple exceptions with Python. To begin with, you’ll review Python’s exception handling mechanism before diving deeper and learning how to identify what you’ve caught, sometimes ignore what you’ve caught, and even catch lots of exceptions. Python raises an exception when your code encounters an occasional but not unexpected error. For example, this will occur if you try to read a missing file. Because you’re aware that such exceptions may occur, you […]

In Python, operators are special symbols, combinations of symbols, or keywords that designate some type of computation. You can combine objects and operators to build expressions that perform the actual computation. So, operators are the building blocks of expressions, which you can use to manipulate your data. Therefore, understanding how operators work in Python is essential for you as a programmer. In this tutorial, you’ll learn about the operators that Python currently supports. You’ll also learn the basics of how […]

Unlocking Python’s true potential in terms of speed through shared-memory parallelism has traditionally been limited and challenging to achieve. That’s because the global interpreter lock (GIL) doesn’t allow for thread-based parallel processing in Python. Fortunately, there are several work-arounds for this notorious limitation, which you’re about to explore now! To get the most out of this advanced tutorial, you should understand the difference between concurrency and parallelism. You’ll benefit from having previous experience with multithreading in programming languages other than […]

Object-oriented programming (OOP) is a method of structuring a program by bundling related properties and behaviors into individual objects. In this tutorial, you’ll learn the basics of object-oriented programming in Python. Conceptually, objects are like the components of a system. Think of a program as a factory assembly line of sorts. At each step of the assembly line, a system component processes some material, ultimately transforming raw material into a finished product. An object contains data, like the raw or […]