python-tactics-2

############################################## RE-MAP FUNCTIONS AT RUNTIME ##############################################

Say you have a function

 class Test:
   def check(self,a,b,c):
     if a == 0:
       self.str = b*100
     else:
       self.str = c*100

 a = Test()
 def example():
   for i in xrange(0,100000):
     a.check(i,"b","c")

 import profile
 profile.run("example()")

And suppose this function gets called from somewhere else many times.

Well, your check will have an if statement slowing you down all the time except the first time, so you can do this:

 class Test2:
   def check(self,a,b,c):
     self.str = b*100
     self.check = self.check_post
   def check_post(self,a,b,c):
     self.str = c*100

 a = Test2()
 def example2():
   for i in xrange(0,100000):
     a.check(i,"b","c")

 import profile
 profile.run("example2()")
 
 
 
################################################### PYTHON IS NOT C ###################################################

  % timeit.py -s 'x = 47' 'x * 2'
  loops, best of 3: 0.574 usec per loop
  % timeit.py -s 'x = 47' 'x << 1'
  loops, best of 3: 0.524 usec per loop
  % timeit.py -s 'x = 47' 'x + x'
  loops, best of 3: 0.382 usec per loop
  
There is a significant advantage in Python to adding a number to itself instead of multiplying it by two or shifting it left by one bit.



################################################### DATA AGGREGATION ##################################################

Avoid :

  x = 0
  def doit1(i):
      global x
      x = x + i

  list = range(100000)
  t = time.time()
  for i in list:
      doit1(i)

Use :

  x = 0
  def doit2(list):
      global x
      for i in list:
          x = x + i

  list = range(100000)
  t = time.time()
  doit2(list)
  
Even written in Python, the second example runs about four times faster than the first. Had doit been written in C the difference would likely have been even greater (exchanging a Python for loop for a C for loop as well as removing most of the function calls).