为什么 python 字典中的字符串键的写入/读取速度比元组慢？

Question

在尝试优化模仿树结构的程序的速度时（“树”存储在以笛卡尔坐标 x,y 坐标对作为键的 DICT 中），我发现将它们的唯一地址作为元组存储在字典中，而不是与字符串相比，运行时间要快得多。

我的问题是，如果 Python 针对字典和哈希中的字符串键进行了优化，为什么在这个示例中使用元组会快得多？在执行完全相同的任务时，字符串键似乎要花费 60% 的时间。我在我的例子中忽略了一些简单的事情吗？

我引用这个线程作为我的问题的基础（以及其他同样断言字符串更快的线程）：使用字符串作为字典中的键总是更快吗？

下面是我用来测试这些方法并计时的代码：

import time

def writeTuples():
    k = {}
    for x in range(0,500):
        for y in range(0,x):
            k[(x,y)] = "%s,%s"%(x,y)
    return k

def readTuples(k):
    failures = 0
    for x in range(0,500):
        for y in range(0,x):
            if k.get((x,y)) is not None: pass
            else: failures += 1
    return failures

def writeStrings():
    k = {}
    for x in range(0,500):
        for y in range(0,x):
            k["%s,%s"%(x,y)] = "%s,%s"%(x,y)
    return k

def readStrings(k):
    failures = 0
    for x in range(0,500):
        for y in range(0,x):
            if k.get("%s,%s"%(x,y)) is not None: pass
            else: failures += 1
    return failures

def calcTuples():
    clockTimesWrite = []
    clockTimesRead = []
    failCounter = 0
    trials = 100

    st = time.clock()
    for x in range(0,trials):
        startLoop = time.clock()
        k = writeTuples()
        writeTime = time.clock()
        failCounter += readTuples(k)
        readTime = time.clock()
        clockTimesWrite.append(writeTime-startLoop)
        clockTimesRead.append(readTime-writeTime)

    et = time.clock()

    print("The average time to loop with tuple keys is %f, and had %i total failed records"%((et-st)/trials,failCounter))
    print("The average write time is %f, and average read time is %f"%(sum(clockTimesWrite)/trials,sum(clockTimesRead)/trials))
    return None

def calcStrings():
    clockTimesWrite = []
    clockTimesRead = []
    failCounter = 0
    trials = 100

    st = time.clock()
    for x in range(0,trials):
        startLoop = time.clock()
        k = writeStrings()
        writeTime = time.clock()
        failCounter += readStrings(k)
        readTime = time.clock()
        clockTimesWrite.append(writeTime-startLoop)
        clockTimesRead.append(readTime-writeTime)

    et = time.clock()
    print("The average time to loop with string keys is %f, and had %i total failed records"%((et-st)/trials,failCounter))
    print("The average write time is %f, and average read time is %f"%(sum(clockTimesWrite)/trials,sum(clockTimesRead)/trials))
    return None

calcTuples()
calcStrings()

谢谢！

Answer 1

测试的权重不公平（因此存在时间差异）。format您在循环中对writeStrings循环的调用次数是循环中的两倍writeTuples，并且在 中对它的调用次数是无限多的readStrings。为了进行更公平的测试，您需要确保：

• %两个写循环仅对每个内部循环进行一次调用
• 这readStrings两者readTuples都对每个内部循环进行一次或零次调用%。