# scalable bottleneck

Schachner, Joseph Joseph.Schachner at Teledyne.com
Thu Apr 4 12:34:23 EDT 2019

```If you are using Python 3, range does not create at list, it is a generator.   If you're using Python 2.x, use xrange instead of range.  xrange is a generator.   In Python 3 there is no xrange, they just made range the generator.

--- Joseph S.

-----Original Message-----
From: Sayth Renshaw <flebber.crue at gmail.com>
Sent: Wednesday, April 3, 2019 5:42 PM
To: python-list at python.org
Subject: scalable bottleneck

In an email, I received this question as part of a newsletter.

def fetch_squares ( max_root ):
squares = []
for x in range ( max_root ):
squares . append (x **2)
return squares

MAX = 5

for square in fetch_squares (MAX ):
do_something_with ( square )

1) Do you see a memory bottleneck here? If so, what is it?
2) Can you think of a way to fix the memory bottleneck?

Want to know if I am trying to solve the correct bottleneck.
I am thinking that the bottleneck is to create a list only to iterate the same list you created sort of doubling the time through.

Is that the correct problem to solve?

If it is then I thought the best way is just to supply the numbers on the fly, a generator.

def supply_squares(max_root):
for x in max_root:
yield x

MAX = 5

So then I set up a loop and do whatever is needed. At this time I am creating generator objects. But is this the correct way to go? More of a am I thinking correctly questino.

item = 0
while item < MAX:
print(supply_squares(item))
item += 1

<generator object supply_squares at 0x0000000004DEAC00> <generator object supply_squares at 0x0000000004DEAC00> <generator object supply_squares at 0x0000000004DEAC00> <generator object supply_squares at 0x0000000004DEAC00> <generator object supply_squares at 0x0000000004DEAC00>

Thanks

Sayth

```