Python Context Managers

Introduction

One of the most "obscure" features of Python that almost all Python programmers use, even the beginner ones, but don't really understand, is context managers. You've probably seen them in the form of with statements, usually first encountered when you learn opening files in Python. Although context managers seem a little strange at first, when we really dive into them, understand the motivation and techniques behind it, we get access to a new weapon in our programming arsenal. So without further ado, let's dive into it!

Motivation: Resource Management

"Necessity is the mother of invention"

To really understand what a context manager is and how we can use it, we must first investigate the motivations behind it — the necessities that gave rise to this "invention".

The primary motivation behind context managers is resource management. When a program wants to get access to a resource on the computer, it asks the OS for it, and the OS, in turn, provides it with a handle for that resource. Some common examples of such resources are files and network ports. What's important to understand is that these resources have limited availability, for example, a network port can be used by a single process at a time, and there are a limited number of ports available. So whenever we open a resource, we have to remember to close it, so that the resource is freed. But unfortunately, it's easier said than done.

The most straightforward way to accomplish proper resource management would be calling the close function after we're done with the resource:

opened_file = open('readme.txt')
text = opened_file.read()
...
opened_file.close()

Here we are opening a file named readme.txt, reading the file and saving its contents in a string text, and then when we're done with it, closing the file by calling the close() method of the opened_file object. Now at first glance this might seem okay, but actually, it's not robust at all. If anything unexpected happens between opening the file and closing the file, causing the program to fail to execute the line containing the close statement, there would be a resource leak. These unexpected events are what we call exceptions, a common one would be when someone forcefully closes the program while it's executing.

Now, the proper way to handle this would be using Exception handling, using try...else blocks:

try:
    opened_file = open('readme.txt')
    text = opened_file.read()
    #...
else:
    opened_file.close()

Python always makes sure the code in the else block is executed, regardless of anything that might happen. This is the way programmers in other languages would handle resource management, but Python programmers get a special mechanism that lets them implement the same functionality without all the boilerplate. This is where context managers come into play!

Implementing Context Managers

Now that we are done with the most crucial part about understanding context managers, we can jump into implementing them. For this tutorial, we will implement a custom File class. It's totally redundant as Python already provides this, but nevertheless, it'll be a good learning exercise as we'll always be able to relate back to the File class that's already there in the standard library.

The standard and "lower-level" way of implementing a context manager is defining two "magic" methods in the class you want to implement resource management for, __enter__and __exit__. If you're getting lost-thinking, "what's this magic method thingy? I've never heard of this before" - well, if you've started doing object-oriented programming in Python, you surely have encountered a magic method already, the method __init__.

For lack of better words, they're special methods that you can define to make your classes smarter or add "magic" to them. You can find a nice reference list of all the magic methods available in Python here.

Anyway, getting back to the topic, before we start implementing these two magic methods, we'll have to understand their purpose. __enter__ is the method that gets called when we open the resource, or to put it in a slightly more technical way - when we "enter" the runtime context. The with statement will bind this method's return value to the target specified in the as clause of the statement:

class FileManager:
    def __init__(self, filename):
        self.filename = filename
        
    def __enter__(self):
        self.opened_file = open(self.filename)
        return self.opened_file

As you can see, the __enter__ method is opening the resource - the file, and returning it. When we use this FileManager in a with statement, this method will be called and its return value will be bind to the target variable you mentioned in the as clause:

with FileManager('readme.txt') as file:
    text = file.read()

Let's break it down part-by-part. Firstly, an instance of the FileManager class is created when we instantiate it, passing the filename "readme.txt" to the constructor. Then, the with statement starts working on it - it calls the __enter__ method of that FileManager object and assigns the returned value to the file variable mentioned in the as clause. Then, inside the with block, we can do whatever we want to do with the opened resource.

The other important part of the puzzle is the __exit__ method. The __exit__ method contains clean-up code which must be executed after we're done with the resource, no matter what. The instructions in this method will be similar to the ones in the else block we discussed before while discussing exception handling. To reiterate, the __exit__ method contains instructions to properly close the resource handler, so that the resource is freed for further use by other programs in the OS.

Now let's take a look at how we might write this method:

class FileManager:
    def __exit__(self. *exc):
        self.opened_file.close()

Whenever the instances of this class will be used in a with statement, this __exit__ method will be called before the program leaves the with block, or before the program halts due to some exception. Now let's look at the whole FileManager class so that we have a complete idea:

class FileManager:
    def __init__(self, filename):
        self.filename = filename
        
    def __enter__(self):
        self.opened_file = open(self.filename)
        return self.opened_file
    
    def __exit__(self, *exc):
        self.opened_file.close()
Free eBook: Git Essentials

Check out our hands-on, practical guide to learning Git, with best-practices, industry-accepted standards, and included cheat sheet. Stop Googling Git commands and actually learn it!

Simple enough, right? We just defined the opening and cleaning-up actions in the respective magic methods, and Python will take care of resource management wherever this class might be used. That brings us to the next topic, the different ways we can use context manager classes, such as this FileManager class.

Using Context Managers

There's not much to explain here, so instead of writing long paragraphs, let's take a look at a few code-snippets in this section:

file = FileManager('readme.txt')
with file as managed_file:
    text = managed_file.read()
    print(text)
with FileManager('readme.txt') as managed_file:
    text = managed_file.read()
    print(text)
def open_file(filename):
    file = FileManager(filename)
    return file

with open_file('readme.txt') as managed_file:
    text = managed_file.read()
    print(text)

You can see that the key thing to remember is,

  1. The object passed to the with statement must have __enter__ and __exit__ methods.
  2. The __enter__ method must return the resource that's to be used in the with block.

Important: There are some subtleties I left out, to make the discussion to-the-point. For the exact specifications of these magic methods, refer to the Python documentation here.

Using _contextlib_

The Zen of Python - Python's guiding principle as a list of aphorisms - states:

"Simple is better than complex"

To really drive this point home, Python developers have created a library named contextlib containing utilities regarding context managers, as if they didn't simplify the problem of resource management enough. We are going to demonstrate only one of them briefly here, but we recommend you to check out the official Python docs for more information.

from contextlib import contextmanager

@contextmanager
def open_file(filename):
    opened_file = open(filename)
    try:
        yield opened_file
    finally:
        opened_file.close()

Like the code above, we can simply define a function that yields the protected resource in a try statement, closing it in the subsequent finally statement. Another way to understand it:

  • All the contents you'd otherwise put in the __enter__ method, except the return statement, goes before the try block here — basically the instructions for opening the resource.
  • Instead of returning the resource, you yield it, inside a try block.
  • The contents of the __exit__ method goes inside the corresponding finally block.

Once we have such a function, we can decorate it using the contextlib.contextmanager decorator and we're good:

with open_file('readme.txt') as managed_file:
    text = managed_file.read()
    print(text)

As you can see, the decorated open_file function returns a context manager and we can use that directly. This lets us achieve the same effect as creating the FileManager class, without all the hassle.

Conclusion

If you're feeling enthusiastic and want to read more about context managers, I encourage you to check out the following links:

Last Updated: August 2nd, 2023
Was this article helpful?

Improve your dev skills!

Get tutorials, guides, and dev jobs in your inbox.

No spam ever. Unsubscribe at any time. Read our Privacy Policy.

Project

Building Your First Convolutional Neural Network With Keras

# python# artificial intelligence# machine learning# tensorflow

Most resources start with pristine datasets, start at importing and finish at validation. There's much more to know. Why was a class predicted? Where was...

David Landup
David Landup
Details
Course

Data Visualization in Python with Matplotlib and Pandas

# python# pandas# matplotlib

Data Visualization in Python with Matplotlib and Pandas is a course designed to take absolute beginners to Pandas and Matplotlib, with basic Python knowledge, and...

David Landup
David Landup
Details

© 2013-2024 Stack Abuse. All rights reserved.

AboutDisclosurePrivacyTerms