Why Does Function Encapsulation Enhance Python Code Execution Speed?

Code Execution Speed Enhancement through Function Encapsulation

When executing Python code, it is noticed that code contained within a function runs significantly faster than the same code executed outside of a function. To investigate this phenomenon, let us analyze a simple code snippet:

def main():
    for i in xrange(10**8):
        pass
main()

This code runs in approximately 1.8 seconds when executed within the main() function. However, if the for loop is placed outside of the function, the execution time increases to around 4.5 seconds:

for i in xrange(10**8):
    pass

The reason for this performance disparity lies in the way Python compiles code. When the code is executed within a function, it is compiled into a form known as bytecode. Bytecode is a sequence of instructions that the Python Virtual Machine (PVM) executes more efficiently than the original Python code.

Examining the bytecode for the code snippet using the dis module reveals the difference:

Within a function:

  2           0 SETUP_LOOP              20 (to 23)
              3 LOAD_GLOBAL              0 (xrange)
              6 LOAD_CONST               3 (100000000)
              9 CALL_FUNCTION            1
             12 GET_ITER            
        >>   13 FOR_ITER                 6 (to 22)
             16 STORE_FAST               0 (i)

  3          19 JUMP_ABSOLUTE           13
        >>   22 POP_BLOCK           
        >>   23 LOAD_CONST               0 (None)
             26 RETURN_VALUE        

Outside a function:

  1           0 SETUP_LOOP              20 (to 23)
              3 LOAD_NAME                0 (xrange)
              6 LOAD_CONST               3 (100000000)
              9 CALL_FUNCTION            1
             12 GET_ITER            
        >>   13 FOR_ITER                 6 (to 22)
             16 STORE_NAME               1 (i)

  2          19 JUMP_ABSOLUTE           13
        >>   22 POP_BLOCK           
        >>   23 LOAD_CONST               2 (None)
             26 RETURN_VALUE        

The crucial difference is in the instructions at lines 16 and 19. Within the function, the variable i is stored using STORE_FAST, which is optimized for local variables. However, outside the function, i is stored using STORE_NAME, which is more computationally intensive since it pertains to global variables.

Therefore, by encapsulating the code within a function, we optimize the storage and retrieval of variables, resulting in faster execution times.

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