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Learn AI with Python · Lesson

Context Managers (with Statements)

Discover the power of context managers for managing resources.

Context Managers (with Statements) is a free Learn AI with Python lesson on CoddyKit — lesson 3 of 5. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Learn AI with Python learning path, one of 5 lessons in the course, and your progress syncs across the web and the CoddyKit app.

1

Introduction to Context Managers

Context managers in Python help you manage resources such as files, network connections, and database connections. They ensure resources are properly acquired and released, even if an error occurs.

In this lesson, you’ll learn how to use and create context managers using the with statement.

Context Managers (with Statements) — illustration 1

2

What Is a Context Manager?

A context manager is a construct that allows you to allocate and release resources efficiently. It uses the with statement to wrap resource management code.

# Using a context manager with a file
with open("example.txt", "r") as file:
    content = file.read()
    print(content)  # File is automatically closed after the block

3

Why Use Context Managers?

Context managers help you:

  • Ensure proper cleanup of resources.
  • Reduce the chances of resource leaks.
  • Write cleaner and more readable code.

4

Built-in Context Managers

Python includes several built-in context managers, such as:

  • open: Manages file operations.
  • decimal.localcontext: Manages precision settings for decimal operations.

5

Creating a Custom Context Manager

You can create a custom context manager using a class with __enter__ and __exit__ methods:

# Custom context manager class
class CustomManager:
    def __enter__(self):
        print("Entering the context")
        return self

    def __exit__(self, exc_type, exc_value, traceback):
        print("Exiting the context")

with CustomManager() as manager:
    print("Inside the context")

6

Handling Exceptions in Context Managers

Custom context managers can handle exceptions using the __exit__ method:

# Handling exceptions in a context manager
class ExceptionManager:
    def __enter__(self):
        print("Entering the context")
        return self

    def __exit__(self, exc_type, exc_value, traceback):
        if exc_type:
            print(f"An exception occurred: {exc_value}")
        print("Exiting the context")
        return True  # Suppresses the exception

with ExceptionManager():
    raise ValueError("Something went wrong")

7

Using Contextlib

The contextlib module provides utilities to simplify the creation of context managers:

# Using contextlib to create a context manager
from contextlib import contextmanager

@contextmanager
def custom_context():
    print("Entering the context")
    yield
    print("Exiting the context")

with custom_context():
    print("Inside the context")

8

Best Practices for Context Managers

Here are some best practices:

  • Use built-in context managers whenever possible.
  • Handle exceptions properly in custom context managers.
  • Use the contextlib module for simpler syntax.

9

10

Common Mistakes with Context Managers

Here are some mistakes to avoid:

  • Not using with for resource management.
  • Failing to implement __exit__ properly in custom context managers.
  • Ignoring exceptions in __exit__.

11

What Did We Learn?

In this lesson, you learned:

  • What context managers are and how they work with the with statement.
  • How to create custom context managers using __enter__ and __exit__.
  • How to use the contextlib module to simplify context manager creation.

Great job! Let’s move to the next topic.

Context Managers (with Statements) — illustration 11

Frequently asked questions

Is the “Context Managers (with Statements)” lesson free?

Yes — the full text of “Context Managers (with Statements)” is free to read here on the web, and the Learn AI with Python course includes 5 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Learn AI with Python course, upgrade to CoddyKit PRO.

What will I learn in “Context Managers (with Statements)”?

Discover the power of context managers for managing resources. You practise Learn AI with Python with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.

Do I need any experience to start Learn AI with Python?

No prior experience is required. Learn AI with Python on CoddyKit is structured for beginners through advanced learners; this is — lesson 3 of 5, so you can start here or from the beginning and move at your own pace.

How long does the “Context Managers (with Statements)” lesson take?

Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.

Can I write and run code in this Learn AI with Python lesson?

Yes. Every Learn AI with Python lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.

All lessons in this course

  1. Decorators
  2. Generators
  3. Context Managers (with Statements)
  4. Comprehensions (List, Set, and Dictionary)
  5. Iterators and Iterables
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