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Is time.process_time() a better measure for performance than time.time()?

I'm fairly new to python (and CS in general), and I've been reading some docs regarding the "time" library in python. There are quite a lot of time measuring methods, and I'm trying to find the most suitable one that will enable me to compare the performance of 2 versions of an algorithm.
I understand that time.time() is wall time, and time.process_time() is either user-cpu time or system-cpu time (I'm not quite sure), but which one of these two would be a better (more accurate) measure of performance?
Thank you!!!

I would suggest you use time.perf_counter() as it is the recommended function for this kind of tasks (it auto selects the method with highest precision available).
It returns a float, that means just nothing on its own (unlike the result of time.time()), but computing the difference between two time.perf_counter()'s measurements tells you how much time elapsed.
For more info, read the time.perf_counter()'s docs.

what is the difference between time.time and time.clock? [duplicate]

This question already has answers here:
Python's time.clock() vs. time.time() accuracy?
(16 answers)
Closed 6 years ago.
I thought both measure the amount of time? But they return very different numbers and I don't understand what the documentation is saying. Can anyone elaborate?

time.clock() gives you an elapsed amount of time. time.time() gives you the wall clock time.
You can use time.time() to communicate with others (including humans) about when something happened. time.clock() only lets you measure how long something takes.
Generally speaking, you'd use time.clock() when you want to measure timings, time.time() to schedule something. To that end time.time() has to be set correctly on your computer (to agree with the rest of your region as to what time it is now), but time.clock() doesn't, it just counts seconds from an arbitrary point in time (usually when your computer started or when your process first used the function).
The exact behaviour of time.clock() depends on your OS (it could just measure process time, excluding time sleeping, or it could measure time elapsed even when the process is inactive, it could go backwards if your system time is adjusted, etc).
For some use-cases this variability in exact behaviour isn't good enough, and as such it is deprecated in Python 3. There better options are available for either measuring performance or process time, see time.perf_counter() and time.process_time().

time.time(): get theprecision [duplicate]

Consider a very simple timer;
start = time.time()
end = time.time() - start
while(end<5):
end = time.time() - start
print end
how precise is this timer ? I mean compared to real-time clock, how synchronized and real-time is this one ?
Now for the real question ;
What is the smallest scale of time that can be measured precisely with Python ?

This is entirely platform dependent. Use the timeit.default_timer() function, it'll return the most precise timer for your platform.
From the documentation:
Define a default timer, in a platform-specific manner. On Windows, time.clock() has microsecond granularity, but time.time()‘s granularity is 1/60th of a second. On Unix, time.clock() has 1/100th of a second granularity, and time.time() is much more precise.
So, on Windows, you get microseconds, on Unix, you'll get whatever precision the platform can provide, which is usually (much) better than 1/100th of a second.

This entirely depends on the system you are running it on - there is no guarantee Python has any way of tracking time at all.
That said, it's pretty safe to assume you are going to get millisecond accuracy on modern systems, beyond that, it really is highly dependent on the system. To quote the docs:
Although this module is always available, not all functions are
available on all platforms. Most of the functions defined in this
module call platform C library functions with the same name. It may
sometimes be helpful to consult the platform documentation, because
the semantics of these functions varies among platforms.
And:
The precision of the various real-time functions may be less than
suggested by the units in which their value or argument is expressed.
E.g. on most Unix systems, the clock “ticks” only 50 or 100 times a
second.

Python Accurate Sampling

I am trying to sample cpu registers every millisecond and calculate the frequency. To have an accurate measurement, I require that the sampling time to be very accurate. I have been using the time.sleep() to achieve this but sleep is not very accurate past 1 second.
What I would like to do is set up a counter and sample when that counter reaches a certain value and where the counter is incremented at an accurate rate. I am running Python 2.6. Does anyone have any suggestions?

I suspect there are likely several Python packages out there that -help- with what you want. I also suspect Python is not the right tool for that surpose.
There is the timeit module
There is time module with clock() which is NOT a wall clock but a CPU usage clock (for the application initializing the time.clock() object. It is a floating point value which shows some 12+ digits below the ones place ie 1.12345678912345. Python floats are not know for there accuracy and the return value from time.clock() is not something I personally trust as accurate.
There are other Python introspection tools that you can google for, like inspect, itertools, and others, that time processes. however I suspect their accuracy is dependant on running averages of many iterations of measuring the same thing.

Is python time module reliable enough to use to measure response time?

My question was not specific enough last time, and so this is second question about this topic.
I'm running some experiments and I need to precisely measure participants' response time to questions in millisecond unit.
I know how to do this with the time module, but I was wondering if this is reliable enough or I should be careful using it. I was wondering if there are possibilities of some other random CPU load will interfere with the measuring of time.
So my question is, will the response time measure with time module be very accurate or there will be some noise associate with it?
Thank you,
Joon

CPU load will affect timing. If your application is startved of a slice of CPU time, then timing would get affected. You can not help that much. You can be as precise and no more. Ensure that your program gets a health slice of cpu time and the result will be accurate. In most cases, the results should be accurate to milliseconds.

If you benchmark on a *nix system (Linux most probably), time.clock() will return CPU time in seconds. On its own, it's not very informative, but as a difference of results (i.e. t0 = time.clock(); some_process(); t = time.clock() - t0), you'd have a much more load-independent timing than with time.time().