计时python函数timeit vs time.clock悬殊

Question

import time
import logging
from functools import reduce

logging.basicConfig(filename='debug.log', level=logging.DEBUG)



def read_large_file(file_object):
    """Uses a generator to read a large file lazily"""

    while True:
        data = file_object.readline()
        if not data:
            break
        yield data


def process_file_1(file_path):
    """Opens a large file and reads it in"""

    try:
        with open(file_path) as fp:
            for line in read_large_file(fp):
                logging.debug(line)
                pass

    except(IOError, OSError):
        print('Error Opening or Processing file')


def process_file_2(file_path):
    """Opens a large file and reads it in"""

    try:
        with open(path) as file_handler:
            while True:
                logging.debug(next(file_handler))
    except (IOError, OSError):
        print("Error opening / processing file")
    except StopIteration:
        pass


if __name__ == "__main__":
    path = "TB_data_dictionary_2016-04-15.csv"

    l1 = []
    for i in range(1,10):
        start = time.clock()
        process_file_1(path)
        end = time.clock()
        diff = (end - start)
        l1.append(diff)

    avg = reduce(lambda x, y: x + y, l1) / len(l1)
    print('processing time (with generators) {}'.format(avg))


    l2 = []
    for i in range(1,10):
        start = time.clock()
        process_file_2(path)
        end = time.clock()
        diff = (end - start)
        l2.append(diff)

    avg = reduce(lambda x, y: x + y, l2) / len(l2)
    print('processing time (with iterators) {}'.format(avg))

计划的输出：

C:\Python34\python.exe C:/pypen/data_structures/generators/generators1.py
processing time (with generators) 0.028033358176432314
processing time (with iterators) 0.02699498330810426

我使用的另一种方法如下。

def wrapper(func, *args, **kwargs):
    def wrapped():
        return func(*args, **kwargs)
    return wrapped


if __name__ == "__main__":
    path = "TB_data_dictionary_2016-04-15.csv"

    wrapped = wrapper(process_file_1, path)
    t = timeit.timeit(wrapped, number=100)
    print('processing time (with generators) {}'.format(t))

    wrapped = wrapper(process_file_2, path)
    t = timeit.timeit(wrapped, number=100)
    print('processing time (with iterators) {}'.format(t))

这给了我不同的结果。

 C:\Python34\python.exe C:/pypen/data_structures/generators/generators1.py
    processing time (with generators) 3.0999817624283916
    processing time (with iterators) 3.2149597826018304

我希望使用generators的实现比使用iterators的实现更快（这是我在使用timeit时得到的）。

为什么我没有使用其他方法获得相同的结果。