Using functools.wraps with a logging decorator

To use functools.wraps with a logging decorator in Python, you can wrap your decorator function with functools.wraps to ensure that the decorated function retains its original metadata, such as its name, docstring, and function signature. This helps maintain consistency when using introspection tools and debugging.

Here's an example of creating a logging decorator using functools.wraps:

import functools import logging # Configure logging logging.basicConfig(level=logging.INFO) def log_args_and_result(func): @functools.wraps(func) def wrapper(*args, **kwargs): args_str = ', '.join([repr(arg) for arg in args]) kwargs_str = ', '.join([f"{key}={repr(value)}" for key, value in kwargs.items()]) all_args = ', '.join(filter(None, [args_str, kwargs_str])) logging.info(f"Calling {func.__name__}({all_args})") result = func(*args, **kwargs) logging.info(f"{func.__name__} returned {repr(result)}") return result return wrapper # Usage example @log_args_and_result def add(a, b): """Adds two numbers.""" return a + b result = add(3, 5) 

In this example:

1. We import functools and logging.

2. We configure the logging module using logging.basicConfig() to set the logging level.

3. We define a decorator log_args_and_result that logs function arguments and results. Inside the decorator, we use functools.wraps to wrap the inner wrapper function.

4. The wrapper function logs the function call, executes the decorated function func, logs the result, and returns it.

5. We apply the @log_args_and_result decorator to the add function, which logs its arguments and result.

6. When we call add(3, 5), it logs the function call, computes the result, logs the result, and returns it.

By using functools.wraps, the add function retains its original docstring and name, which is essential for maintaining documentation and debugging information.

Examples

1. "How to use functools.wraps with a logging decorator in Python?" Description: Learn how to preserve function metadata while creating a logging decorator in Python using the functools.wraps decorator.

   import functools import logging def log_function(func): @functools.wraps(func) def wrapper(*args, **kwargs): logging.info(f"Calling {func.__name__} with args: {args}, kwargs: {kwargs}") return func(*args, **kwargs) return wrapper @log_function def example_function(x, y): return x + y print(example_function(3, 4)) 

2. "Example of using functools.wraps for logging decorators" Description: Explore a practical example demonstrating the usage of functools.wraps to create a logging decorator for Python functions.

   import functools import logging def log_function(func): @functools.wraps(func) def wrapper(*args, **kwargs): logging.info(f"Calling {func.__name__} with args: {args}, kwargs: {kwargs}") return func(*args, **kwargs) return wrapper @log_function def example_function(x, y): return x + y print(example_function(3, 4)) 

3. "Preserving function attributes with functools.wraps in logging decorators" Description: Understand how functools.wraps ensures that function attributes like __name__ and __doc__ are preserved when creating logging decorators in Python.

   import functools import logging def log_function(func): @functools.wraps(func) def wrapper(*args, **kwargs): logging.info(f"Calling {func.__name__} with args: {args}, kwargs: {kwargs}") return func(*args, **kwargs) return wrapper @log_function def example_function(x, y): """ This function adds two numbers together. """ return x + y print(example_function.__name__) # Output: example_function print(example_function.__doc__) # Output: This function adds two numbers together. 

4. "Using functools.wraps to maintain function signature in logging decorators" Description: Discover how functools.wraps helps in preserving the original function signature when creating logging decorators in Python.

   import functools import logging def log_function(func): @functools.wraps(func) def wrapper(*args, **kwargs): logging.info(f"Calling {func.__name__} with args: {args}, kwargs: {kwargs}") return func(*args, **kwargs) return wrapper @log_function def example_function(x: int, y: int) -> int: return x + y import inspect print(inspect.signature(example_function)) # Output: (x: int, y: int) -> int 

5. "Explanation of functools.wraps usage in Python logging decorators" Description: Gain insight into the role of functools.wraps in maintaining function metadata integrity when building logging decorators in Python.

   import functools import logging def log_function(func): @functools.wraps(func) def wrapper(*args, **kwargs): logging.info(f"Calling {func.__name__} with args: {args}, kwargs: {kwargs}") return func(*args, **kwargs) return wrapper @log_function def example_function(x, y): return x + y print(example_function.__name__) # Output: example_function print(example_function.__doc__) # Output: None (if no docstring is provided) 

6. "Tutorial on using functools.wraps for logging decorators" Description: Follow a step-by-step tutorial illustrating the utilization of functools.wraps to implement logging decorators efficiently in Python.

   import functools import logging def log_function(func): @functools.wraps(func) def wrapper(*args, **kwargs): logging.info(f"Calling {func.__name__} with args: {args}, kwargs: {kwargs}") return func(*args, **kwargs) return wrapper @log_function def example_function(x, y): return x + y print(example_function(3, 4)) 

7. "How to maintain function documentation using functools.wraps in logging decorators" Description: Learn how to retain function documentation while creating logging decorators in Python with the help of functools.wraps.

   import functools import logging def log_function(func): @functools.wraps(func) def wrapper(*args, **kwargs): logging.info(f"Calling {func.__name__} with args: {args}, kwargs: {kwargs}") return func(*args, **kwargs) return wrapper @log_function def example_function(x, y): """ This function adds two numbers together. """ return x + y print(example_function.__doc__) # Output: This function adds two numbers together. 

8. "Using functools.wraps to avoid losing function name in logging decorators" Description: Prevent the loss of function names when creating logging decorators by employing functools.wraps effectively in Python.

   import functools import logging def log_function(func): @functools.wraps(func) def wrapper(*args, **kwargs): logging.info(f"Calling {func.__name__} with args: {args}, kwargs: {kwargs}") return func(*args, **kwargs) return wrapper @log_function def example_function(x, y): return x + y print(example_function.__name__) # Output: example_function 

9. "Importance of functools.wraps in Python logging decorators" Description: Understand the significance of functools.wraps in maintaining function metadata consistency when designing logging decorators in Python.

   import functools import logging def log_function(func): @functools.wraps(func) def wrapper(*args, **kwargs): logging.info(f"Calling {func.__name__} with args: {args}, kwargs: {kwargs}") return func(*args, **kwargs) return wrapper @log_function def example_function(x, y): return x + y # The original function name is preserved print(example_function.__name__) # Output: example_function 

10. "Explanation of functools.wraps usage for function wrapping in Python logging decorators" Description: Delve into the explanation of how functools.wraps facilitates function wrapping within logging decorators while ensuring metadata coherence in Python.

    import functools import logging def log_function(func): @functools.wraps(func) def wrapper(*args, **kwargs): logging.info(f"Calling {func.__name__} with args: {args}, kwargs: {kwargs}") return func(*args, **kwargs) return wrapper @log_function def example_function(x, y): return x + y print(example_function.__name__) # Output: example_function 

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