Python’s with statement allows you to manage external resources safely by using objects that support the context manager protocol. These objects automatically handle the setup and cleanup phases of common operations.By using the with statement alongside appropriate context managers, you can focus on your core logic while the context managers prevent resource leaks like unclosed files, unreleased memory, or dangling network connections.By the end of this tutorial, you’ll understand that:Python’s with statement automates the process of setting up and tearing down computational resources using context managers.Using with reduces code complexity and prevents resource leaks by ensuring proper resource release, even if exceptions occur.A context manager in Python is an object that implements .__enter__() and .__exit__() methods to manage resources safely.Get ready to learn how Python’s with statement and context managers streamline the setup and teardown phases of resource management so you can write safer, more reliable code.Get Your Code: Click here to download the free sample code that shows you how to use Python’s with statement to manage external resources safely. Take the Quiz: Test your knowledge with our interactive “Context Managers and Python's with Statement” quiz. You’ll receive a score upon completion to help you track your learning progress: Interactive Quiz Context Managers and Python's with Statement Test your knowledge of Python's with statement and context managers to write cleaner code and manage resources safely and efficiently. Managing External Resources in PythonProperly managing external resources, such as files, locks, and network connections, is a common requirement in programming. Sometimes, a program uses a given resource and doesn’t release the associated memory when it no longer needs the resource. This kind of issue is called a memory leak because the available memory shrinks every time you create a new instance of a resource without releasing the unneeded ones.Managing resources properly is often a tricky task. It requires setup and teardown phases. The latter phase requires you to perform cleanup actions, like 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 occupied. This behavior might compromise valuable system resources, such as memory and network bandwidth.For example, say that a program that uses databases keeps creating new connections without releasing the old ones or reusing them. In that case, the database back end can stop accepting new connections. This might require an administrator to log in and manually terminate those stale connections to make the database usable again.Another common issue occurs when developers work 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, developers forget to call .close() and part of the data can be lost.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 where you use the built-in open() function to write some text to a file: Python file = open("hello.txt", "w")file.write("Hello, World!")file.close() Copied! This code doesn’t guarantee the file will be closed if an exception occurs during the call to .write(). In this situation, the code might never call .close(), and your program will leak a file descriptor. Failing to release a file descriptor on some operating systems can prevent other programs from accessing the underlying file.Note: To learn more about closing files, check out the Why Is It Important to Close Files in Python? tutorial.In Python, you can use a couple of general approaches to deal with resource management. You can wrap your code in:A try … finally constructA with constructThe first approach is quite generic and allows you to provide setup and teardown code to manage any kind of resource. However, it’s a little bit verbose, and you might forget some cleanup actions if you use this construct in several places.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 ConstructWorking with files is probably the most common example of resource management in programming. In Python, you can use a try … finally construct to handle opening and closing files properly: Python file = open("hello.txt", "w")try: file.write("Hello, World!")finally: file.close() Copied! In this example, you open the hello.txt file using open(). To write some text into the file, you wrap the call to .write() in a try statement with a finally clause. This clause guarantees that the file is properly closed by calling .close(), even if an exception occurs during the call to .write() in the try clause. Remember that the finally clause always runs.When managing external resources in Python, you can use the construct in the previous example to handle setup and teardown logic. The setup logic might include opening the file and writing content to it, while the teardown logic might consist of closing the file to release the acquired resources.Read the full article at https://realpython.com/python-with-statement/ » [ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn more and see examples ]