Python Context Managers

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Python Context Managers

Summary: in this tutorial, you’ll learn about Python context managers and how to use them effectively

Introduction to Python context managers

A context manager is an object that defines a runtime context executing within the with statement.

Let’s start with a simple example to understand the context manager concept.

Suppose that you have a file called data.txt that contains an integer 100.

The following program reads the data.txt file, converts its contents to a number, and shows the result to the standard output:

f = open('data.txt')
data = f.readlines()

# convert the number to integer and display it


Code language: Python (python)

The code is simple and straightforward.

However, the data.txt may contain data that cannot be converted to a number. In this case, the code will result in an exception.

For example, if the data.txt contains the string '100' instead of the number 100, you’ll get the following error:

ValueError: invalid literal for int() with base 10: "'100'"

Code language: Python (python)

Because of this exception, Python may not close the file properly.

To fix this, you may use the try...except...finally statement:

f = open('data.txt')
data = f.readlines()
# convert the number to integer and display it
except ValueError as error:

Code language: Python (python)

Since the code in the finally block always executes, the code will always close the file properly.

This solution works as expected. However, it’s quite verbose.

Therefore, Python provides you with a better way that allows you to automatically close the file after you complete processing it.

This is where context managers come into play.

The following shows how to use a context manager to process the data.txt file:

with open('data.txt') as f:
data = f.readlines()

Code language: Python (python)

In this example, we use the open() function with the with statement. After the with block, Python will close automatically.

Python with statement

Here is the typical syntax of the with statement:

with context as ctx:
# use the the object

# context is cleaned up

Code language: Python (python)

How it works.

  • When Python encounters the with statement, it creates a new context. The context can optionally return an object.
  • After the with block, Python cleans up the context automatically.
  • The scope of the ctx has the same scope as the with statement. It means that you can access the ctx both inside and after the with statement.

The following shows how to access the f variable after the with statement:

with open('data.txt') as f:
data = f.readlines()

print(f.closed) # True

Code language: Python (python)

Python context manager protocol

Python context managers work based on the context manager protocol.

The context manager protocol has the following methods:

  • __enter__() – setup the context and optionally return some object
  • __exit__() – cleanup the object.

If you want a class to support the context manager protocol, you need to implement these two methods.

Suppose that ContextManager is a class that supports the context manager protocol.

The following shows how to use the ContextManager class:

with ContextManager() as ctx:
# do something
# done with the context

Code language: Python (python)

When you use ContextManager class with the with statement, Python implicitly creates an instance of the ContextManager class (instance) and automatically call __enter__() method on that instance.

The __enter__() method may optionally return an object. If so, Python assigns the returned object the ctx.

Notice that ctx references the object returned by the __enter__() method. It doesn’t reference the instance of the ContextManager class.

If an exception occurs inside the with block or after the with block, Python calls the __exit__() method on the instance object.

Python Context Managers

Functionally, the with statement is equivalent to the following try...finally statement:

instance = ContextManager()
ctx = instance.__enter__()

# do something with the txt
# done with the context

Code language: Python (python)

The __enter__() method

In the __enter__() method, you can carry the necessary steps to setup the context.

Optionally, you can returns an object from the __enter__() method.

The __exit__() method

Python always executes the __exit__() method even if an exception occurs in the with block.

The __exit__() method accepts three arguments: exception type, exception value, and traceback object. All of these arguments will be None if no exception occurs.

def __exit__(self, ex_type, ex_value, ex_traceback):

Code language: Python (python)

The __exit__() method returns a boolean value, either True or False.

If the return value is True, Python will make any exception silent. Otherwise, it doesn’t silence the exception.

Python context manager applications

As you see from the previous example, the common usage of a context manager is to open and close files automatically.

However, you can use context managers in many other cases:

1) Open – Close

If you want to open and close a resource automatically, you can use a context manager.

For example, you can open a socket and close it using a context manager.

2) Lock – release

Context managers can help you manage locks for objects more effectively. They allow you to acquire a lock and release it automatically.

3) Start – stop

Context managers also help you to work with a scenario that requires the start and stop phases.

For example, you can use a context manager to start a timer and stop it automatically.

3) Change – reset

Context managers can work with change and reset scenario.

For example, your application needs to connect to multiple data sources. And it has a default connection.

To connect to another data source:

  • First, use a context manager to change the default connection to a new one.
  • Second, work with the new connection
  • Third, reset it back to the default connection once you complete working with the new connection.

Implementing Python context manager protocol

The following shows a simple implementation of the open() function using the context manager protocol:

class File:
def __init__(self, filename, mode):
self.filename = filename
self.mode = mode

def __enter__(self):
print(f'Opening the file {self.filename}.')
self.__file = open(self.filename, self.mode)
return self.__file

def __exit__(self, exc_type, exc_value, exc_traceback):
print(f'Closing the file {self.filename}.')
if not self.__file.closed:

return False

with File('data.txt', 'r') as f:

Code language: Python (python)

How it works.

  • First, initialize the filename and mode in the __init__() method.
  • Second, open the file in the __enter__() method and return the file object.
  • Third, close the file if it’s open in the __exit__() method.

Using Python context manager to implement the start and stop pattern

The following defines a Timer class that supports the context manager protocol:

from time import perf_counter

class Timer:
def __init__(self):
self.elapsed = 0

def __enter__(self):
self.start = perf_counter()
return self

def __exit__(self, exc_type, exc_value, exc_traceback):
self.stop = perf_counter()
self.elapsed = self.stop - self.start
return False

Code language: Python (python)

How it works.

  • First, import the perf_counter from the time module.
  • Second, start the timer in the __enter__() method
  • Third, stop the timer in the __exit__() method and return the elapsed time.

Now, you can use the Timer class to measure the time needed to calculate the Fibonacci of 1000, one million times:

def fibonacci(n):
f1 = 1
f2 = 1
for i in range(n-1):
f1, f2 = f2, f1 + f2

return f1

with Timer() as timer:
for _ in range(1, 1000000):


Code language: Python (python)


  • Use Python context managers to define runtime contexts when executing in the with statement.
  • implement the __enter__() and __exit__() methods to support the context manager protocol.

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