python-3.x - time.perf_counter() 是否应该在 Windows 上的 Python 中跨进程保持一致？

Question

更新:此错误的修复已提交并将在 Python 3.10 中首次亮相，预计将于 2021 年 10 月发布。参见 bug report了解详情。

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time.perf_counter() 的文档表明它是系统范围的

time.perf_counter() → float

Return the value (in fractional seconds) of a performance counter, i.e. a clock with the highest available resolution to measure a short duration. It does include time elapsed during sleep and is system-wide. The reference point of the returned value is undefined, so that only the difference between the results of consecutive calls is valid.

我将系统范围解释为包括跨进程的一致性是否不正确？

如下所示，它在 Linux 上似乎是一致的，但在 Windows 上却不一致。此外，Python 3.6 的 Windows 行为与 3.7 有很大不同。

如果有人能指出涉及此行为的文档或错误报告，我将不胜感激。

测试用例

import concurrent.futures
import time

def worker():
    return time.perf_counter()

if __name__ == '__main__':
    pool = concurrent.futures.ProcessPoolExecutor()
    futures = []
    for i in range(3):
        print('Submitting worker {:d} at time.perf_counter() == {:.3f}'.format(i, time.perf_counter()))
        futures.append(pool.submit(worker))
        time.sleep(1)

    for i, f in enumerate(futures):
        print('Worker {:d} started at time.perf_counter() == {:.3f}'.format(i, f.result()))

Windows 7 上的结果

C:\...>Python36\python.exe -VV
Python 3.6.8 (tags/v3.6.8:3c6b436a57, Dec 24 2018, 00:16:47) [MSC v.1916 64 bit (AMD64)]

C:\...>Python36\python.exe perf_counter_across_processes.py
Submitting worker 0 at time.perf_counter() == 0.000
Submitting worker 1 at time.perf_counter() == 1.169
Submitting worker 2 at time.perf_counter() == 2.170
Worker 0 started at time.perf_counter() == 0.000
Worker 1 started at time.perf_counter() == 0.533
Worker 2 started at time.perf_counter() == 0.000

C:\...>Python37\python.exe -VV
Python 3.7.3 (v3.7.3:ef4ec6ed12, Mar 25 2019, 22:22:05) [MSC v.1916 64 bit (AMD64)]

C:\...>Python37\python.exe perf_counter_across_processes.py
Submitting worker 0 at time.perf_counter() == 0.376
Submitting worker 1 at time.perf_counter() == 1.527
Submitting worker 2 at time.perf_counter() == 2.529
Worker 0 started at time.perf_counter() == 0.380
Worker 1 started at time.perf_counter() == 0.956
Worker 2 started at time.perf_counter() == 1.963

为简洁起见，我省略了 Windows 上的更多结果，但在 Windows 8.1 上观察到了相同的行为。此外，Python 3.6.7 的行为与 3.6.8 相同，而 Python 3.7.1 的行为与 3.7.3 相同。

Ubuntu 18.04.1 LTS 上的结果

$ python3 -VV
Python 3.6.7 (default, Oct 22 2018, 11:32:17) 
[GCC 8.2.0]

$ python3 perf_counter_across_processes.py 
Submitting worker 0 at time.perf_counter() == 2075.896
Submitting worker 1 at time.perf_counter() == 2076.900
Submitting worker 2 at time.perf_counter() == 2077.903
Worker 0 started at time.perf_counter() == 2075.900
Worker 1 started at time.perf_counter() == 2076.902
Worker 2 started at time.perf_counter() == 2077.905

$ python3.7 -VV
Python 3.7.1 (default, Oct 22 2018, 11:21:55) 
[GCC 8.2.0]

$ python3.7 perf_counter_across_processes.py 
Submitting worker 0 at time.perf_counter() == 1692.514
Submitting worker 1 at time.perf_counter() == 1693.518
Submitting worker 2 at time.perf_counter() == 1694.520
Worker 0 started at time.perf_counter() == 1692.517
Worker 1 started at time.perf_counter() == 1693.519
Worker 2 started at time.perf_counter() == 1694.522

Answer 1

在 Windows 中，time.perf_counter 基于 WINAPI QueryPerformanceCounter。这个计数器是系统范围的。有关详细信息，请参阅 acquiring high-resolution time stamps .

也就是说，Windows 中的 perf_counter 返回一个相对于进程启动值的值。因此它不是系统范围的值。这样做是为了在将整数值转换为精度只有 15 位小数的 float 时减少精度损失。在大多数情况下不需要使用相对值，它只需要微秒精度。应该有一个可选参数来查询真正的 QPC 计数器值，尤其是对于 3.7+ 中的 perf_counter_ns。

关于 perf_counter 在 3.6 和 3.7 中返回的不同初始值，实现随着时间的推移发生了一些变化。在 3.6.8 中，perf_counter 在 Modules/timemodule.c 中实现，因此当 time 模块首次导入和初始化时会存储初始值，这就是您看到第一个结果为 0.000 秒的原因。在最近的版本中，它在 Python 的 C API 中单独实现。例如，参见 "Python/pytime.c"在最新的 3.8 测试版中。在这种情况下，当 Python 代码调用 time.perf_counter() 时，计数器的增量已远远超过启动值。

这是一个基于 ctypes 的替代实现，它使用系统范围的 QPC 值而不是相对值。

import sys

if sys.platform != 'win32':
    from time import perf_counter
    try:
        from time import perf_counter_ns
    except ImportError:
        def perf_counter_ns():
            """perf_counter_ns() -> int

            Performance counter for benchmarking as nanoseconds.
            """
            return int(perf_counter() * 10**9)
else:
    import ctypes
    from ctypes import wintypes

    kernel32 = ctypes.WinDLL('kernel32', use_last_error=True)

    kernel32.QueryPerformanceFrequency.argtypes = (
        wintypes.PLARGE_INTEGER,) # lpFrequency

    kernel32.QueryPerformanceCounter.argtypes = (
        wintypes.PLARGE_INTEGER,) # lpPerformanceCount

    _qpc_frequency = wintypes.LARGE_INTEGER()
    if not kernel32.QueryPerformanceFrequency(ctypes.byref(_qpc_frequency)):
        raise ctypes.WinError(ctypes.get_last_error())
    _qpc_frequency = _qpc_frequency.value

    def perf_counter_ns():
        """perf_counter_ns() -> int

        Performance counter for benchmarking as nanoseconds.
        """
        count = wintypes.LARGE_INTEGER()
        if not kernel32.QueryPerformanceCounter(ctypes.byref(count)):
            raise ctypes.WinError(ctypes.get_last_error())
        return (count.value * 10**9) // _qpc_frequency

    def perf_counter():
        """perf_counter() -> float

        Performance counter for benchmarking.
        """
        count = wintypes.LARGE_INTEGER()
        if not kernel32.QueryPerformanceCounter(ctypes.byref(count)):
            raise ctypes.WinError(ctypes.get_last_error())
        return count.value / _qpc_frequency

QPC 通常具有 0.1 微秒的分辨率。 CPython 中的 float 具有 15 位十进制数字的精度。因此，此 perf_counter 的实现在 QPC 决议范围内，正常运行时间约为 3 年。