The following code is a lot slower with pypy as compared to CPython. The
code mainly measures the time taken to execute a simple SQLite user
defined function (UDF) and a more complex one, 1000000 times each.
Execution time for both queries is:
CPython 2.7: 7 sec 489 msec
Pypy nightly build: 28 sec 753 msec
Execution time for simple query only is:
CPython 2.7: 1 sec 39 msec
Pypy nightly build: 13 sec 645 msec
Pypy seems to not jit at all when a (pypy) Python function is called from C.
Also based on the simple query times, pypy seems to have massive
overhead (nearly 13 times slower) when executing callbacks from C code.
lefteris.
--- code --
import sqlite3
import datetime
# Simple function
def testfun(*args):
return 1
# Complex function
def sectohuman(*args):
secs=int(args[0])
h=''
days=secs/86400
if days > 0:
h+=str(days)+' day'
if days > 1:
h+='s'
h+=' '
secs=secs % 86400
hours=secs/3600
if hours > 0:
h+=str(hours)+' hour'
if hours > 1:
h+='s'
h+=' '
secs=secs % 3600
mins=secs/60
if mins > 0:
h+=str(mins)+' min '
secs=secs % 60
if secs > 0:
h+=str(secs)+' sec'
return h
con=sqlite3.Connection('')
con.create_function('testfun', -1, testfun)
con.create_function('sectohuman', -1, sectohuman)
cur=con.cursor()
cur.execute('create table l(a);')
cur.execute('begin;')
for i in xrange(1000000):
cur.execute('insert into l values(?)',(i,))
before=datetime.datetime.now()
# Simple query
a=list(cur.execute('select sum(testfun(a)) as s from l'))
# Complex query
a=list(cur.execute('select sum(length(sectohuman(a))) as s from l'))
after=datetime.datetime.now()
tmdiff=after-before
print "Execution time is %s min. %s sec %s msec"
%((int(tmdiff.days)*24*60+(int(tmdiff.seconds)/60),(int(tmdiff.seconds)%60),(int(tmdiff.microseconds)/1000)))
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