Context managers are a powerful feature in Python that allow for resource management and clean-up tasks. They ensure that resources are properly managed by automatically handling setup and teardown operations. The most common use of context managers is with the `with` statement, which helps manage file operations, database connections, and locks, ensuring proper closure and cleanup.
Here's a simple example of using a context manager to work with files:
with open('example.txt', 'r') as file:
data = file.read()
print(data)
# File is automatically closed after this block
In this example, the file 'example.txt' is opened in read mode. The `with` statement ensures that the file is closed automatically after the block of code is executed, even if an exception occurs.
How do I avoid rehashing overhead with std::set in multithreaded code?
How do I find elements with custom comparators with std::set for embedded targets?
How do I erase elements while iterating with std::set for embedded targets?
How do I provide stable iteration order with std::unordered_map for large datasets?
How do I reserve capacity ahead of time with std::unordered_map for large datasets?
How do I erase elements while iterating with std::unordered_map in multithreaded code?
How do I provide stable iteration order with std::map for embedded targets?
How do I provide stable iteration order with std::map in multithreaded code?
How do I avoid rehashing overhead with std::map in performance-sensitive code?
How do I merge two containers efficiently with std::map for embedded targets?