第461页 | Learning Python | 阅读 ‧ 电子书库

Timing Script

To time iteration tool speed, run the following script—it uses the timer module we wrote to time the relative speeds of the list construction techniques we’ve studied:

# File timeseqs.py

import sys, mytimer                              # Import timer function
reps = 10000
repslist = range(reps)                           # Hoist range out in 2.6

def forLoop():
    res = []
    for x in repslist:
        res.append(abs(x))
    return res

def listComp():
    return [abs(x) for x in repslist]

def mapCall():
    return list(map(abs, repslist))              # Use list in 3.0 only

def genExpr():
    return list(abs(x) for x in repslist)        # list forces results

def genFunc():
    def gen():
        for x in repslist:
            yield abs(x)
    return list(gen())

print(sys.version)
for test in (forLoop, listComp, mapCall, genExpr, genFunc):
    elapsed, result = mytimer.timer(test)
    print ('-' * 33)
    print ('%-9s: %.5f => [%s...%s]' %
           (test.__name__, elapsed, result[0], result[-1]))

This script tests five alternative ways to build lists of results and, as shown, executes on the order of 10 million steps for each—that is, each of the five tests builds a list of 10,000 items 1,000 times.

Notice how we have to run the generator expression and function results through the built-in list call to force them to yield all of their values; if we did not, we would just produce generators that never do any real work. In Python 3.0 (only) we must do the same for the map result, since it is now an iterable object as well. Also notice how the code at the bottom steps through a tuple of four function objects and prints the __name__ of each: as we’ve seen, this is a built-in attribute that gives a function’s name.[45]