Another optimization technique, one that is contrary to memoization, is not particularly generic. Instead, it is directly tied to how the Python interpreter works.
Default arguments can be used to determine values once at function creation time, instead of at run time.
Tip
This can only be done for functions or objects that will not be changed during program execution.
Let's look at an example of how this optimization can be applied. The following code shows two versions of the same function, which does some random trigonometric calculation:
import math
#original function
def degree_sin(deg):
return math.sin(deg * math.pi / 180.0)
#optimized function, the factor variable is calculated during function creation time,
#and so is the lookup of the math.sin method.
def degree_sin(deg, factor=math.pi/180.0, sin=math.sin):
return sin(deg * factor)