Memory Management in Python

Ever wonder how Python handles your data behind the scenes? How are your variables stored in memory? When do they get deleted?

In this article, we’re going to do a deep dive into the internals of Python to understand how it handles memory management.

By the end of this article, you’ll:

• Learn more about low-level computing, specifically as relates to memory
• Understand how Python abstracts lower-level operations
• Learn about Python’s internal memory management algorithms

Understanding Python’s internals will also give you better insight into some of Python’s behaviors. Hopefully, you’ll gain a new appreciation for Python as well. So much logic is happening behind the scenes to ensure your program works the way you expect.

Memory Is an Empty Book

You can begin by thinking of a computer’s memory as an empty book intended for short stories. There’s nothing written on the pages yet. Eventually, different authors will come along. Each author wants some space to write their story in.

Since they aren’t allowed to write over each other, they must be careful about which pages they write in. Before they begin writing, they consult the manager of the book. The manager then decides where in the book they’re allowed to write.

Since this book is around for a long time, many of the stories in it are no longer relevant. When no one reads or references the stories, they are removed to make room for new stories.

In essence, computer memory is like that empty book. In fact, it’s common to call fixed-length contiguous blocks of memory pages, so this analogy holds pretty well.

The authors are like different applications or processes that need to store data in memory. The manager, who decides where the authors can write in the book, plays the role of a memory manager of sorts. The person who removed the old stories to make room for new ones is a garbage collector.

Memory Management: From Hardware to Software

Memory management is the process by which applications read and write data. A memory manager determines where to put an application’s data. Since there’s a finite chunk of memory, like the pages in our book analogy, the manager has to find some free space and provide it to the application. This process of providing memory is generally called memory allocation.

On the flip side, when data is no longer needed, it can be deleted, or freed. But freed to where? Where did this “memory” come from?

Somewhere in your computer, there’s a physical device storing data when you’re running your Python programs. There are many layers of abstraction that the Python code goes through before the objects actually get to the hardware though.

One of the main layers above the hardware (such as RAM or a hard drive) is the operating system (OS). It carries out (or denies) requests to read and write memory.

Above the OS, there are applications, one of which is the default Python implementation (included in your OS or downloaded from python.org.) Memory management for your Python code is handled by the Python application. The algorithms and structures that the Python application uses for memory management is the focus of this article.

The Default Python Implementation

The default Python implementation, CPython, is actually written in the C programming language.

When I first heard this, it blew my mind. A language that’s written in another language?! Well, not really, but sort of.

The Python language is defined in a reference manual written in English. However, that manual isn’t all that useful by itself. You still need something to interpret written code based on the rules in the manual.

You also need something to actually execute interpreted code on a computer. The default Python implementation fulfills both of those requirements. It converts your Python code into instructions that it then runs on a virtual machine.