From 6709b7b01ba6b4c50a7f25e5c7c9bdc147da921f Mon Sep 17 00:00:00 2001 From: XiongNeng Date: Wed, 9 Dec 2015 14:39:43 +0800 Subject: [PATCH] =?UTF-8?q?13.13=E5=B0=8F=E8=8A=82=E5=AE=8C=E6=88=90?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- source/c13/p13_making_stopwatch_timer.rst | 138 +++++++++++----------- source/roadmap.rst | 8 +- 2 files changed, 74 insertions(+), 72 deletions(-) diff --git a/source/c13/p13_making_stopwatch_timer.rst b/source/c13/p13_making_stopwatch_timer.rst index 062f965..0d79055 100644 --- a/source/c13/p13_making_stopwatch_timer.rst +++ b/source/c13/p13_making_stopwatch_timer.rst @@ -5,100 +5,102 @@ ---------- 问题 ---------- -You want to be able to record the time it takes to perform various tasks. +你想记录程序执行多个任务所花费的时间 | ---------- 解决方案 ---------- -The time module contains various functions for performing timing-related functions. -However, it’s often useful to put a higher-level interface on them that mimics a stop -watch. For example: +``time`` 模块包含很多函数来执行跟时间有关的函数。 +尽管如此，通常我们会在此基础之上构造一个更高级的接口来模拟一个计时器。例如： -import time +.. code-block:: python -class Timer: - def __init__(self, func=time.perf_counter): - self.elapsed = 0.0 - self._func = func - self._start = None + import time - def start(self): - if self._start is not None: - raise RuntimeError('Already started') - self._start = self._func() + class Timer: + def __init__(self, func=time.perf_counter): + self.elapsed = 0.0 + self._func = func + self._start = None - def stop(self): - if self._start is None: - raise RuntimeError('Not started') - end = self._func() - self.elapsed += end - self._start - self._start = None + def start(self): + if self._start is not None: + raise RuntimeError('Already started') + self._start = self._func() - def reset(self): - self.elapsed = 0.0 + def stop(self): + if self._start is None: + raise RuntimeError('Not started') + end = self._func() + self.elapsed += end - self._start + self._start = None - @property - def running(self): - return self._start is not None + def reset(self): + self.elapsed = 0.0 - def __enter__(self): - self.start() - return self + @property + def running(self): + return self._start is not None - def __exit__(self, *args): - self.stop() + def __enter__(self): + self.start() + return self -This class defines a timer that can be started, stopped, and reset as needed by the user. -It keeps track of the total elapsed time in the elapsed attribute. Here is an example that -shows how it can be used: + def __exit__(self, *args): + self.stop() -def countdown(n): - while n > 0: - n -= 1 +这个类定义了一个可以被用户根据需要启动、停止和重置的计时器。 +它会在 ``elapsed`` 属性中记录整个消耗时间。 +下面是一个例子来演示怎样使用它： -# Use 1: Explicit start/stop -t = Timer() -t.start() -countdown(1000000) -t.stop() -print(t.elapsed) +.. code-block:: python -# Use 2: As a context manager -with t: + def countdown(n): + while n > 0: + n -= 1 + + # Use 1: Explicit start/stop + t = Timer() + t.start() countdown(1000000) + t.stop() + print(t.elapsed) -print(t.elapsed) + # Use 2: As a context manager + with t: + countdown(1000000) -with Timer() as t2: - countdown(1000000) -print(t2.elapsed) + print(t.elapsed) + + with Timer() as t2: + countdown(1000000) + print(t2.elapsed) | ---------- 讨论 ---------- -This recipe provides a simple yet very useful class for making timing measurements and -tracking elapsed time. It’s also a nice illustration of how to support the context- -management protocol and the with statement. -One issue in making timing measurements concerns the underlying time function used -to do it. As a general rule, the accuracy of timing measurements made with functions -such as time.time() or time.clock() varies according to the operating system. In -contrast, the time.perf_counter() function always uses the highest-resolution timer -available on the system. -As shown, the time recorded by the Timer class is made according to wall-clock time, -and includes all time spent sleeping. If you only want the amount of CPU time used by -the process, use time.process_time() instead. For example: +本节提供了一个简单而实用的类来实现时间记录以及耗时计算。 +同时也是对使用with语句以及上下文管理器协议的一个很好的演示。 -t = Timer(time.process_time) -with t: - countdown(1000000) -print(t.elapsed) +在计时中要考虑一个底层的时间函数问题。一般来说， +使用 ``time.time()`` 或 ``time.clock()`` 计算的时间精度因操作系统的不同会有所不同。 +而使用 ``time.perf_counter()`` 函数可以确保使用系统上面最精确的计时器。 -Both the time.perf_counter() and time.process_time() return a “time” in fractional -seconds. However, the actual value of the time doesn’t have any particular meaning. To -make sense of the results, you have to call the functions twice and compute a time -difference. -More examples of timing and profiling are given in Recipe 14.13. +上述代码中由 ``Timer`` 类记录的时间是钟表时间，并包含了所有休眠时间。 +如果你只想计算该进程所花费的CPU时间，应该使用 ``time.process_time()`` 来代替： + +.. code-block:: python + + t = Timer(time.process_time) + with t: + countdown(1000000) + print(t.elapsed) + +``time.perf_counter()`` 和 ``time.process_time()`` 都会返回小数形式的秒数时间。 +实际的时间值没有任何意义，为了得到有意义的结果，你得执行两次函数然后计算它们的差值。 + +更多关于计时和性能分析的例子请参考14.13小节。 diff --git a/source/roadmap.rst b/source/roadmap.rst index d20fda3..8b96382 100644 --- a/source/roadmap.rst +++ b/source/roadmap.rst @@ -56,28 +56,28 @@ Roadmap | 13章翻译完成 -2015/09/01 - 2015/09/30: +2015/09/01 - 2015/11/30: :: | 14章翻译完成 -2015/10/01 - 2015/10/31: +2015/12/01 - 2015/12/20: :: | 15章翻译完成 -2015/11/01 - 2015/11/15: +2015/12/21 - 2015/12/31: :: | 对全部翻译进行校对一次 -2015/11/16 - 2015/11/20: +2016/01/01 - 2016/01/10: ::