While trying to tackle a more complex problem, I came to compare access speed to local variable vs member variables.
Here a test program:
#!/usr/bin/env python
MAX=40000000
class StressTestMember(object):
def __init__(self):
self.m = 0
def do_work(self):
self.m += 1
self.m *= 2
class StressTestLocal(object):
def __init__(self):
pass
def do_work(self):
m = 0
m += 1
m *= 2
# LOCAL access test
for i in range(MAX):
StressTestLocal().do_work()
# MEMBER access test
for i in range(MAX):
StressTestMember().do_work()
I know it might look like a bad idea to instantiate StressTestMember
and StressTestLocal
on each iterations but it makes sense in the modeled program where these are basically Active Records.
After a simple benchmark,
- LOCAL access test: 0m22.836
- MEMBER access test: 0m32.648s
The local version is ~33% faster while still part of a class. Why?
self.m += 1
means you have to look up a local variable called self
and then find the attribute called m
Of course if you just have to look up a local variable, it will be faster without the extra step.
It can be useful to look at what is happening under the hood:
>>> import dis
>>> dis.dis(StressTestLocal.do_work)
18 0 LOAD_CONST 1 (0)
3 STORE_FAST 1 (m)
19 6 LOAD_FAST 1 (m)
9 LOAD_CONST 2 (1)
12 INPLACE_ADD
13 STORE_FAST 1 (m)
20 16 LOAD_FAST 1 (m)
19 LOAD_CONST 3 (2)
22 INPLACE_MULTIPLY
23 STORE_FAST 1 (m)
26 LOAD_CONST 0 (None)
29 RETURN_VALUE
>>> dis.dis(StressTestMember.do_work)
10 0 LOAD_FAST 0 (self)
3 DUP_TOP
4 LOAD_ATTR 0 (m)
7 LOAD_CONST 1 (1)
10 INPLACE_ADD
11 ROT_TWO
12 STORE_ATTR 0 (m)
11 15 LOAD_FAST 0 (self)
18 DUP_TOP
19 LOAD_ATTR 0 (m)
22 LOAD_CONST 2 (2)
25 INPLACE_MULTIPLY
26 ROT_TWO
27 STORE_ATTR 0 (m)
30 LOAD_CONST 0 (None)
33 RETURN_VALUE
Local names is faster because Python does some optimization that local names don't need dict access, on the other hand, instance attributes need to access the __dict__
of the object.
This is also the reason why local names are faster than global names.