Two candies

bearophileHUGS at bearophileHUGS at
Wed Jan 2 22:28:47 CET 2008

First of all, thank you Raymond for your answer, and a happy new year
to you and to all the Python group :-)

>#3 is a fine choice.  It is memory efficient -- the repeat() itertool takes-up only a few bytes.  It doesn't need psyco, you already have to fast C routines talking to each other without having to go through the interpreter loop.<

In my code I have found otherwise, so to be more sure I have just done
few benchmarks on a Pentium3 CPU, 256 MB RAM, ActivePython, on

It may sound unfair, but I think it's useful to have some basic
reference timing, so I taken timings from a program written in D
language too (it's like a better C++ mixed with some Python and other
things), this is the D code:

import std.stdio, std.conv, std.string, std.c.stdlib, std.c.time;
void main(string[] args) {
    int n = toInt(args[1].replace("_", ""));
    auto t0 = clock();
    if (args[2].strip() == "1")
        auto a = new int[n];
        auto a = cast(int*)calloc(n, int.sizeof);
    auto t1 = clock();
    writefln("%.2f s", (t1-t0)/cast(double)CLOCKS_PER_SEC);

As input it takes n and 1 or 2,
"Warm" timings:

     n      time-1  time-2
 1_000_000    0.04    0.04
10_000_000    0.44    0.42
30_000_000    1.32    1.26

In both cases the a array is initialized to all 0.
D "int" is 4 always bytes. The memory used by this little program is
essentially what you ask for, so it is 4 MB for n = 1 million, 40 MB
for n = 10 millions, and 120 MB for n = 30 millions (plus few other
small things, like the stack, etc. All the other extra memory is
probably less than 800 KB.).

This is the Python code, as input it takes n and 1, 2 or 3:

from array import array
from itertools import repeat
from time import clock
from sys import argv

def main():
    n = int(argv[1].replace("_", ""))
    choice = int(argv[2])
    assert choice in [1, 2, 3]

    if choice == 1:
        t0 = clock()
        a = array("l", xrange(n))
        t1 = clock()
    if choice == 2:
        t0 = clock()
        a = array("l", [0] * n)
        t1 = clock()
    if choice == 3:
        t0 = clock()
        a = array("l", repeat(0, n))
        t1 = clock()

    print round(t1 - t0, 2), "s"
    assert len(a) == n


"Warm" timings:

Time (seconds):
     n         #1      #2      #3
 1_000_000   1.98    0.79    1.91
10_000_000  21.73    7.97   21.13
30_000_000  70.     28.55   65.3

Approximate peak MB RAM used:
     n        #1     #2      #3
 1_000_000     9   10.3     6.6
10_000_000    60   81      64
30_000_000   184  210+    200+

At runtime the Python interpreter plus other little things take some
memory, about 1.7 MB.
In the cases with the "+" sign the RAM was not enough, and I've had
swaps, so timings are probably different if you have more RAM (but I
think this benchmark is significant anyway, because IMHO an array of
integers of 120 MB isn't supposed to make your OS swap your 256 MB of
memory if you allocate it properly).
To me it seems that array("l",repeat(0,n)) eats lot of memory, and
it's quite slower than array("l",[0]*n) too. (I presume
array("l",repeat(0,n)) converts the python int 0 to the signed 4-byte
int over and over again...). So I belive still an allocate-like method
may be useful to the array object. It may allocate the data structure
with n=30 millions in probably less than 2 seconds. In the meantime
such arrays I presume I'll use an external numerical lib :-)


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