A common issue with decorators is that they obscure the metadata of the original function. If you inspect a decorated function (e.g., its name, docstring), you’ll see the metadata of the wrapper function, not the original one.
Python’s functools module provides wraps to solve this.
import time
import functools
def time_it_with_metadata(*, use_nanos: bool = False):
def actual_decorator(func):
@functools.wraps(func) # Apply functools.wraps to the wrapper
def wrapper(*args, **kwargs):
start = time.perf_counter_ns() if use_nanos else time.perf_counter()
result = func(*args, **kwargs)
end = time.perf_counter_ns() if use_nanos else time.perf_counter()
duration = end - start
unit = 'nanoseconds' if use_nanos else 'seconds'
print(f"Function '{func.__name__}' took: {duration:.4f} {unit}")
return result
return wrapper
return actual_decorator
@time_it_with_metadata(use_nanos=True)
def documented_database_operation():
"""
This is a very important database operation
that is well documented.
"""
time.sleep(1)
return "Documented DB Op Complete"
print(f"Function Name: {documented_database_operation.__name__}")
print(f"Docstring: {documented_database_operation.__doc__}")
# Try help(documented_database_operation) as well
# print(help(documented_database_operation))By adding @functools.wraps(func) to our wrapper function, the metadata from the original func (like __name__ and __doc__) is copied over to the wrapper function.