Real Python: Context Managers and Python's with Statement

The with statement in Python is a quite useful tool for properly managing external resources in your programs. It allows you to take advantage of existing context managers to automatically handle the setup and teardown phases whenever you’re dealing with external resources or with operations that require those phases.

Besides, the context management protocol allows you to create your own context managers so you can customize the way you deal with system resources. So, what’s the with statement good for?

In this tutorial, you’ll learn:

• What the Python with statement is for and how to use it
• What the context management protocol is
• How to implement your own context managers

With this knowledge, you’ll write more expressive code and avoid resource leaks in your programs. The with statement helps you implement some common resource management patterns by abstracting their functionality and allowing them to be factored out and reused.

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Managing Resources in Python

One common problem you’ll face in programming is how to properly manage external resources, such as files, locks, and network connections. Sometimes, a program will retain those resources forever, even if you no longer need them. This kind of issue is called a memory leak because the available memory gets reduced every time you create and open a new instance of a given resource without closing an existing one.

Managing resources properly is often a tricky problem. It requires both a setup phase and a teardown phase. The latter phase requires you to perform some cleanup actions, such as closing a file, releasing a lock, or closing a network connection. If you forget to perform these cleanup actions, then your application keeps the resource alive. This might compromise valuable system resources, such as memory and network bandwidth.

For example, a common problem that can arise when developers are working with databases is when a program keeps creating new connections without releasing or reusing them. In that case, the database back end can stop accepting new connections. This might require an admin to log in and manually kill those stale connections to make the database usable again.

Another frequent issue shows up when developers are working with files. Writing text to files is usually a buffered operation. This means that calling .write() on a file won’t immediately result in writing text to the physical file but to a temporary buffer. Sometimes, when the buffer isn’t full and developers forget to call .close(), part of the data can be lost forever.

Another possibility is that your application runs into errors or exceptions that cause the control flow to bypass the code responsible for releasing the resource at hand. Here’s an example in which you use open() to write some text to a file:

file = open("hello.txt", "w")
file.write("Hello, World!")
file.close()

This implementation doesn’t guarantee the file will be closed if an exception occurs during the .write() call. In this case, the code will never call .close(), and therefore your program might leak a file descriptor.

In Python, you can use two general approaches to deal with resource management. You can wrap your code in:

1. A try … finally construct
2. A with construct

The first approach is quite general and allows you to provide setup and teardown code to manage any kind of resource. However, it’s a little bit verbose. Also, what if you forget any cleanup actions?

The second approach provides a straightforward way to provide and reuse setup and teardown code. In this case, you’ll have the limitation that the with statement only works with context managers. In the next two sections, you’ll learn how to use both approaches in your code.

The try … finally Approach

Working with files is probably the most common example of resource management in programming. In Python, you can use a try … finally statement to handle opening and closing files properly:

# Safely open the file
file = open("hello.txt", "w")

try:
    file.write("Hello, World!")
finally:
    # Make sure to close the file after using it
    file.close()

In this example, you need to safely open the file hello.txt, which you can do by wrapping the call to open() in a try … except statement. Later, when you try to write to file, the finally clause will guarantee that file is properly closed, even if an exception occurs during the call to .write() in the try clause. You can use this pattern to handle setup and teardown logic when you’re managing external resources in Python.

The try block in the above example can potentially raise exceptions, such as AttributeError or NameError. You can handle those exceptions in an except clause like this:

# Safely open the file
file = open("hello.txt", "w")

try:
    file.write("Hello, World!")
except Exception as e:
    print(f"An error occurred while writing to the file: {e}")
finally:
    # Make sure to close the file after using it
    file.close()

In this example, you catch any potential exceptions that can occur while writing to the file. In real-life situations, you should use a specific exception type instead of the general Exception to prevent unknown errors from passing silently.

Read the full article at https://realpython.com/python-with-statement/ »

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