wrapt 2.0.0

Module for decorators, wrappers and monkey patching.

wrapt

A Python module for decorators, wrappers and monkey patching.

Overview

The wrapt module provides a transparent object proxy for Python, which can be used as the basis for the construction of function wrappers and decorator functions.

The wrapt module focuses very much on correctness. It goes way beyond existing mechanisms such as functools.wraps() to ensure that decorators preserve introspectability, signatures, type checking abilities etc. The decorators that can be constructed using this module will work in far more scenarios than typical decorators and provide more predictable and consistent behaviour.

To ensure that the overhead is as minimal as possible, a C extension module is used for performance critical components. An automatic fallback to a pure Python implementation is also provided where a target system does not have a compiler to allow the C extension to be compiled.

Features

• Universal decorators that work with functions, methods, classmethods, staticmethods, and classes
• Transparent object proxies for advanced wrapping scenarios
• Monkey patching utilities for safe runtime modifications
• C extension for optimal performance with Python fallback
• Comprehensive introspection preservation (signatures, annotations, etc.)
• Thread-safe decorator implementations

Installation

pip install wrapt

Quick Start

Basic Decorator

import wrapt

@wrapt.decorator
def pass_through(wrapped, instance, args, kwargs):
    return wrapped(*args, **kwargs)

@pass_through
def function():
    pass

Decorator with Arguments

import wrapt

def with_arguments(myarg1, myarg2):
    @wrapt.decorator
    def wrapper(wrapped, instance, args, kwargs):
        print(f"Arguments: {myarg1}, {myarg2}")
        return wrapped(*args, **kwargs)
    return wrapper

@with_arguments(1, 2)
def function():
    pass

Universal Decorator

import inspect
import wrapt

@wrapt.decorator
def universal(wrapped, instance, args, kwargs):
    if instance is None:
        if inspect.isclass(wrapped):
            # Decorator was applied to a class
            print("Decorating a class")
        else:
            # Decorator was applied to a function or staticmethod
            print("Decorating a function")
    else:
        if inspect.isclass(instance):
            # Decorator was applied to a classmethod
            print("Decorating a classmethod")
        else:
            # Decorator was applied to an instancemethod
            print("Decorating an instance method")
    
    return wrapped(*args, **kwargs)

Documentation

For comprehensive documentation, examples, and advanced usage patterns, visit:

wrapt.readthedocs.io

Supported Python Versions

• Python 3.8+
• CPython
• PyPy

Contributing

We welcome contributions! This is a pretty casual process - if you're interested in suggesting changes, improvements, or have found a bug, please reach out via the GitHub issue tracker. Whether it's a small fix, new feature idea, or just a question about how something works, feel free to start a discussion.

Please note that wrapt is now considered a mature project. We're not expecting any significant new developments or major feature additions. The primary focus is on ensuring that the package continues to work correctly with newer Python versions and maintaining compatibility as the Python ecosystem evolves.

Testing

For information about running tests, including Python version-specific test conventions and available test commands, see TESTING.md.

License

This project is licensed under the BSD License - see the LICENSE file for details.

Links

• Documentation: https://wrapt.readthedocs.io/
• PyPI: https://pypi.python.org/pypi/wrapt
• Issues: https://github.com/GrahamDumpleton/wrapt/issues/
• Changelog: https://wrapt.readthedocs.io/en/latest/changes.html

Related Blog Posts

This repository also contains a series of blog posts explaining the design and implementation of wrapt:

• How you implemented your Python decorator is wrong
• The interaction between decorators and descriptors
• Implementing a factory for creating decorators
• Implementing a universal decorator
• Decorators which accept arguments
• Maintaining decorator state using a class
• The missing synchronized decorator
• The synchronized decorator as context manager
• Performance overhead of using decorators
• Performance overhead when applying decorators to methods
• Safely applying monkey patches in Python
• Using wrapt to support testing of software
• Ordering issues when monkey patching in Python
• Automatic patching of Python applications