python - Comparison: import statement vs __import__ function -

as followup question using builtin __import__() in normal cases, lead few tests, , came across surprising results.

i here comparing execution time of classical import statement, , call __import__ built-in function. purpose, use following script in interactive mode:

import timeit     def test(module):         t1 = timeit.timeit("import {}".format(module))     t2 = timeit.timeit("{0} = __import__('{0}')".format(module))     print("import statement:   ", t1)     print("__import__ function:", t2)     print("t(statement) {} t(function)".format("<" if t1 < t2 else ">")) 

as in linked question, here comparison when importing sys, along other standard modules:

>>> test('sys') import statement:    0.319865173171288 __import__ function: 0.38428380458522987 t(statement) < t(function)  >>> test('math') import statement:    0.10262547545597034 __import__ function: 0.16307580163101054 t(statement) < t(function)  >>> test('os') import statement:    0.10251490255312312 __import__ function: 0.16240755669640627 t(statement) < t(function)  >>> test('threading') import statement:    0.11349136644972191 __import__ function: 0.1673617034957573 t(statement) < t(function) 

so far good, import faster __import__(). makes sense me, because wrote in linked post, find logical import_name instruction optimized in comparison call_function, when latter results in call __import__.

but when comes less standard modules, results reverse:

>>> test('numpy') import statement:    0.18907936340054476 __import__ function: 0.15840019037769792 t(statement) > t(function)  >>> test('tkinter') import statement:    0.3798560809537861 __import__ function: 0.15899962771786136 t(statement) > t(function)  >>> test("pygame") import statement:    0.6624641952621317 __import__ function: 0.16268579177259568 t(statement) > t(function) 

what reason behind difference in execution times? actual reason why import statement faster on standard modules? on other hand, why __import__ function faster other modules?

tests lead python 3.6

timeit measures total execution time, first import of module, whether through import or __import__, slower subsequent ones - because it's 1 performs module initialization. has search filesystem module's file(s), load module's source code (slowest) or created bytecode (slow bit faster parsing .py files) or shared library (for c extensions), execute initialization code, , store module object in sys.modules. subsequent imports skip , retrieve module object sys.modules.

if reverse order results different:

import timeit     def test(module):         t2 = timeit.timeit("{0} = __import__('{0}')".format(module))     t1 = timeit.timeit("import {}".format(module))     print("import statement:   ", t1)     print("__import__ function:", t2)     print("t(statement) {} t(function)".format("<" if t1 < t2 else ">"))  test('numpy') import statement:    0.4611093703134608 __import__ function: 1.275512785926014 t(statement) < t(function) 

the best way non-biased results import once , timings:

import timeit     def test(module):         exec("import {}".format(module))     t2 = timeit.timeit("{0} = __import__('{0}')".format(module))     t1 = timeit.timeit("import {}".format(module))     print("import statement:   ", t1)     print("__import__ function:", t2)     print("t(statement) {} t(function)".format("<" if t1 < t2 else ">"))  test('numpy') import statement:    0.4826306561727307 __import__ function: 0.9192819125911029 t(statement) < t(function) 

so, yes, import faster __import__.