Decorators and Metadata Preservation in Python 2026

Decorators and Metadata Preservation in Python 2026 – Best Practices

When you apply a decorator to a function, Python replaces the original function with the wrapper returned by the decorator. This causes the loss of important metadata such as `__name__`, `__doc__`, `__module__`, and function signature. In 2026, preserving metadata is considered mandatory for professional code.

TL;DR — Key Rule in 2026

• Always use @wraps(func) from functools in every decorator
• This preserves the original function’s name, docstring, signature, and other metadata
• Without wraps, tools like IDEs, debuggers, and documentation generators break

1. The Problem Without Metadata Preservation

def bad_timer(func):
    def wrapper(*args, **kwargs):
        start = time.perf_counter()
        result = func(*args, **kwargs)
        print(f"{func.__name__} took {time.perf_counter() - start:.4f}s")
        return result
    return wrapper

@bad_timer
def calculate():
    """This is an important calculation function."""
    return 42

print(calculate.__name__)   # "wrapper" ← Broken!
print(calculate.__doc__)    # None ← Docstring lost!

2. Correct Way – Using @wraps (2026 Standard)

from functools import wraps
import time

def timer(func):
    """Decorator that measures execution time and preserves metadata."""
    
    @wraps(func)                    # ← This is the key line
    def wrapper(*args, **kwargs):
        start = time.perf_counter()
        result = func(*args, **kwargs)
        elapsed = time.perf_counter() - start
        print(f"⏱️  {func.__name__}() took {elapsed:.6f} seconds")
        return result
    
    return wrapper

@timer
def calculate():
    """This is an important calculation function."""
    return 42

print(calculate.__name__)   # "calculate" ✓
print(calculate.__doc__)    # "This is an important calculation function." ✓
help(calculate)             # Shows original signature and docstring

3. Best Practices for Metadata in 2026

• Always use @wraps(func) in every decorator you write
• Place @wraps on the inner wrapper function
• Use it even for simple decorators
• For advanced cases, consider the wrapt library
• This ensures compatibility with IDEs, type checkers, and documentation tools

Conclusion

Preserving metadata with functools.wraps is no longer optional — it is a required best practice in 2026. Forgetting to use @wraps breaks introspection, debugging, and documentation. Always include it in every decorator you create.

Next steps:

• Go through all your custom decorators and add @wraps(func) where missing
• Related articles: Decorators in Python 2026 • Writing Functions in Python 2026