First, let’s look at a small program. This is a program that measures the time spent. The following are examples of previous solutions
from functools import wraps, partial from time import time def timing(func=None, frequencies=1): if func is None: # print("+None") return partial(timing, frequencies=frequencies) # else: # print("-None") @wraps(func) def _wrapper(*args, **kwargs): start_time = time() for t in range(frequencies): result = func(*args, **kwargs) end_time = time() print('运行花费时间：{:.6f}s。'.format(end_time-start_time)) return result return _wrapper @timing def run(): l = [] for i in range(5000000): l.extend([i]) return len(l)
Run as follows:
In [4]: run() 运行花费时间：2.383398s。 Out[4]: 5000000
(If you like to get to the bottom of it, you can remove the comments and think about what kind of output is expected).
Today I accidentally saw Python’s context manager (Context Manager), and found it to be very good. In fact, it is closely related to thewithstatement, and I had never noticed it before.
from time import time def run2(): l = [] for i in range(5000000): l.extend([i]) return len(l) class ElapsedTime(): def __enter__(self): self.start_time = time() return self def __exit__(self, exception_type, exception_value, traceback): self.end_time = time() print('运行花费时间：{:.6f}s。'.format(self.end_time - self.start_time)) with ElapsedTime(): run2()
Summary
After briefly reading some official documents, context management is still a bit complicated. Python has developed to this day, and it is actually not simple anymore. To put it simply, you are just not keeping up with the times, and all you have mastered are the old-fashioned three-axe. Therefore, knowledge needs to be constantly updated to make up for your blind spots. The above is the entire content of this article. I hope it can bring some help to everyone's study or work.
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