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Decorator Benchmarks |
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==================== |
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The **wrapt** module ensures that your decorators will work in all |
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situations. The implementation therefore does not take the shortcuts that |
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people usually take with decorators of using function closures. Instead it |
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implements the wrappers as a class, which also acts as a descriptor. |
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Ensuring correctness though does come at an additional cost in runtime |
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overhead. The following attempts to quantify what that overhead is and |
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compare it to other solutions typically used. |
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Results were collected under MacOS X Mountain Lion on a 2012 model MacBook |
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Pro, running with Python 2.7. |
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Undecorated Calls |
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These tests provide a baseline for comparing decorated functions against a |
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normal undecorated function call. |
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**Test Code**:: |
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def function1(): |
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pass |
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class Class(object): |
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def function1(self): |
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pass |
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@classmethod |
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def function1cm(cls): |
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pass |
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@staticmethod |
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def function1sm(): |
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pass |
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**Test Results**:: |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.function1()' |
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10000000 loops, best of 3: 0.132 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function1()' |
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10000000 loops, best of 3: 0.143 usec per loop |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.Class.function1cm()' |
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1000000 loops, best of 3: 0.217 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function1cm()' |
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10000000 loops, best of 3: 0.159 usec per loop |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.Class.function1sm()' |
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1000000 loops, best of 3: 0.199 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function1sm()' |
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10000000 loops, best of 3: 0.13 usec per loop |
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Note that differences between calling the class and static methods via the |
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class vs the instance are possibly more to do with needing to traverse |
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the dotted path. |
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Function Closures |
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These tests provide results for decorated functions where the decorators are |
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implemented using function closures. |
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**Test Code**:: |
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def wrapper2(func): |
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def _wrapper2(*args, **kwargs): |
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return func(*args, **kwargs) |
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return _wrapper2 |
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@wrapper2 |
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def function2(): |
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pass |
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class Class(object): |
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@wrapper2 |
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def function2(self): |
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pass |
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@classmethod |
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@wrapper2 |
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def function2cmi(cls): |
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pass |
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@staticmethod |
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@wrapper2 |
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def function2smi(): |
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pass |
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**Test Results**:: |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.function2()' |
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1000000 loops, best of 3: 0.326 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function2()' |
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1000000 loops, best of 3: 0.382 usec per loop |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.Class.function2cmi()' |
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1000000 loops, best of 3: 0.46 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function2cmi()' |
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1000000 loops, best of 3: 0.384 usec per loop |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.Class.function2smi()' |
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1000000 loops, best of 3: 0.389 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function2smi()' |
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1000000 loops, best of 3: 0.319 usec per loop |
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Note that decorators implemented as function closures cannot be added around |
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staticmethod and classmethod decorators and must be added inside of those |
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decorators. |
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wrapt.decorator |
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These tests provides results for decorated functions where the decorators |
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are implemented using the **wrapt** module. Separate results are provided |
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for when using the C extension and when using the pure Python |
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implementation. |
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**Test Code**:: |
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@wrapt.decorator |
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def wrapper3(wrapped, instance, args, kwargs): |
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return wrapped(*args, **kwargs) |
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@wrapper3 |
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def function3(): |
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pass |
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class Class(object): |
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@wrapper3 |
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def function3(self): |
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pass |
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@wrapper3 |
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@classmethod |
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def function3cmo(cls): |
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pass |
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@classmethod |
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@wrapper3 |
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def function3cmi(cls): |
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pass |
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@wrapper3 |
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@staticmethod |
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def function3smo(): |
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pass |
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@staticmethod |
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@wrapper3 |
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def function3smi(): |
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pass |
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**Test Results (C Extension)**:: |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.function3()' |
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1000000 loops, best of 3: 0.382 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function3()' |
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1000000 loops, best of 3: 0.836 usec per loop |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.Class.function3cmo()' |
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1000000 loops, best of 3: 1.11 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function3cmo()' |
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1000000 loops, best of 3: 1.06 usec per loop |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.Class.function3cmi()' |
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1000000 loops, best of 3: 0.535 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function3cmi()' |
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1000000 loops, best of 3: 0.455 usec per loop |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.Class.function3smo()' |
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1000000 loops, best of 3: 1.37 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function3smo()' |
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1000000 loops, best of 3: 1.31 usec per loop |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.Class.function3smi()' |
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1000000 loops, best of 3: 0.453 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function3smi()' |
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1000000 loops, best of 3: 0.378 usec per loop |
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Note that results for where the decorator is inside that of the classmethod |
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decorator is quite a bit less than that where it is outside. This due to a |
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potential bug in Python whereby it doesn't apply the descriptor protocol to |
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what the classmethod decorator wraps. Instead it is executing a straight |
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function call, which has less overhead. |
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**Test Results (Pure Python)**:: |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.function3()' |
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1000000 loops, best of 3: 0.771 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function3()' |
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100000 loops, best of 3: 6.67 usec per loop |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.Class.function3cmo()' |
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100000 loops, best of 3: 6.89 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function3cmo()' |
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100000 loops, best of 3: 6.77 usec per loop |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.Class.function3cmi()' |
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1000000 loops, best of 3: 0.911 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function3cmi()' |
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1000000 loops, best of 3: 0.863 usec per loop |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.Class.function3smo()' |
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100000 loops, best of 3: 7.26 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function3smo()' |
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100000 loops, best of 3: 7.17 usec per loop |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.Class.function3smi()' |
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1000000 loops, best of 3: 0.835 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function3smi()' |
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1000000 loops, best of 3: 0.774 usec per loop |
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Note that results for where the decorator is inside that of the classmethod |
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decorator is quite a bit less than that where it is outside. This due to a |
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potential bug in Python whereby it doesn't apply the descriptor protocol to |
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what the classmethod decorator wraps. Instead it is executing a straight |
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function call, which has less overhead. |
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decorator.decorator |
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These tests provides results for decorated functions where the decorators |
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are implemented using the **decorator** module available from PyPi. |
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**Test Code**:: |
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@decorator.decorator |
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def wrapper4(wrapped, *args, **kwargs): |
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return wrapped(*args, **kwargs) |
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@wrapper4 |
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def function4(): |
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pass |
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class Class(object): |
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@wrapper4 |
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def function4(self): |
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pass |
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@classmethod |
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@wrapper4 |
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def function4cmi(cls): |
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pass |
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@staticmethod |
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@wrapper4 |
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def function4smi(): |
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pass |
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**Test Results**:: |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.function4()' |
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1000000 loops, best of 3: 0.465 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function4()' |
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1000000 loops, best of 3: 0.537 usec per loop |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.Class.function4cmi()' |
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1000000 loops, best of 3: 0.606 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function4cmi()' |
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1000000 loops, best of 3: 0.533 usec per loop |
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$ python -m timeit -s 'import benchmarks' 'benchmarks.Class.function4smi()' |
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1000000 loops, best of 3: 0.532 usec per loop |
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$ python -m timeit -s 'import benchmarks; c=benchmarks.Class()' 'c.function4smi()' |
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1000000 loops, best of 3: 0.456 usec per loop |
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Note that decorators implemented using the decorator module cannot be added |
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around staticmethod and classmethod decorators and must be added inside of |
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those decorators. |
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