Reference Tracking

[Greg Ewing (using news.cis.dfn.de)]

  -- any number of system-maintained
 > data structures may have attributes and items that happen to
 > be worth 1 (or 0, or other small, popular numbers).
 >
 > import gc
 > gc.get_referrers(1)
 >
 > will at any time give you a list of all containers which have
 > a reference to the value 1, if you're curious.  Of course, having
 > such a container in hand will not necessarily make it easy to
 > understand WHAT the container in fact IS -- but many will be
 > dicts with string keys, which lets you do some detective work;-).
 >
 >
 > Note that any Python function call always passes VALUES -- i.e.
 > there is no difference between your call to sys.getrefcount in
 > the above snippet and one that directly does sys.getrefcount(1).
 > In either case, it's the VALUE (1) that you're asking info about;
 > it makes no difference HOW you obtain the value to pass (I guess
 > this is probably already clear to you, but, just in case...).
 >
 >
 > In your case, you were talking about tracking objects of a specific
 > different type -- not ones that Python will implicitly cache and
 > reuse, such as small integers.  Thus, you do not necessarily need
 > to work with _changes_ in refcounts rather than with refcounts
 > directly -- I think using the refcounts directly may be simpler.
 >
 >
 > Alex
 >


Alex Martelli wrote:
> In practice, Python does such caching for small integers, and 1
> is clearly a popular value

Just for fun, I did a quick poll of the popularities
of integers from 0-99:

 >>> for i in range(100): print i, sys.getrefcount(i)
...
0 98
1 45
2 21
3 9
4 14
5 10
6 11
7 10
8 10
9 9
10 14
11 8
12 8
13 10
14 7
15 7
16 6
17 9
18 7
19 7
20 7
21 7
22 7
23 8
24 7
25 7
26 7
27 7
28 7
29 9
30 8
31 7
32 9
33 5
34 5
35 5
....
99 5

It seems that the most popular number is 0, and the most
popular popularity is 5.

0-for-prime-minister-ly,

-- 
Greg Ewing, Computer Science Dept,
University of Canterbury,	
Christchurch, New Zealand
http://www.cosc.canterbury.ac.nz/~greg