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[Tips] Several Python execution time calculation methods

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Posted on 4/23/2018 3:54:36 PM | | | |
First of all, let's talk about the pitfalls I encountered, the problems encountered in production, I schedule the execution of the python script and monitor the process, the python script running time is far greater than the program execution time I count in the python script.
The time to monitor the execution of python scripts is 36 hours, while the time of self-execution in python scripts is about 4 hours.
The first thing that comes to mind after the problem is that there is a problem with Linux, and I found no abnormalities in various logs.
Then I think of the py2neo used in python to write data asynchronously, blocking the execution of the process.
Finally, the problem was found: the way the python script uses time.clock() to count the execution time of the CPU, not the execution time of the program.
Next, let's compare several Python time statistics:

Method 1:

datetime.datetime.now() gets the current date, and after the program execution ends, the time value obtained by this method is the time of program execution.

Method 2:

time.time() to get the current time since the epoch (In seconds）。 If the system clock provides them, there may be a fraction of seconds. So this place returns a floating-point type. What is obtained here is also the execution time of the program.

Method 3:

time.clock() returns the CPU time since the program started or was first called. This has as much precision as system recording. The return is also a floating-point type. What you get here is the execution time of the CPU.
Note: Program execution time = CPU time + io time + hibernation or waiting time

Here is how I test the execution time of the function using method 2:







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