Range of time.clock() in Python

Question

I use Python 2.7.6 to measure the running time of an algorithm:

starting_time = time.clock()      
# run algorithm
finishing_time = time.clock()
running_time = (finishing_time - starting_time)

I run the algorithm with different input sizes. The algorithm is O(n-squared) and I get the following results:

Input Size Running Time

  1K        0.079382

  10K       8.310275

  100K      838.066953

  1000K    -2040.323576

When the input size is 1000K, running_time should be about 83800. Instead, I get a negative result. Is it because of the range of time.clock() function?

Python docs page says: time.clock() - On Unix, return the current processor time as a floating point number expressed in seconds. The precision, and in fact the very definition of the meaning of “processor time”, depends on that of the C function of the same name, but in any case, this is the function to use for benchmarking Python or timing algorithms. — yildizabdullah, Oct 27 '15 at 11:59

score 1 · Accepted Answer · edited May 23 '17 at 12:14

Yes, this is because of the limitations of the underlying system call. The results you'll get really depend on your platform.

On Windows, the system call always returns a signed 64-bit integer (which is the divided by the counter frequency). So it should not wrap on any reasonable time scale.

On Linux the underlying integer is either signed 32-bit or signed 64-bit depending on whether your platform is 32-bit or 64-bit system. It is also further divided by the frequency of the counter so a 32-bit integer could definitely wrap after several hours.

On Linux you should really be using the newer clock_gettime() system call rather than clock(), which shouldn't have this wrap around problem. If you have Python 3.3 or newer it's as simple as:

time.clock_gettime(time.CLOCK_PROCESS_CPUTIME_ID)

If you have an older version of Python, you can either install a C API package like posix_timers to give you clock_gettime(). Check out: https://pypi.python.org/pypi/posix_timers/

Alternatively, you can use ctypes to access it your self. There is a stack overflow question that shows how to do this with a monotonic clock here: How do I get monotonic time durations in python?

The only difference you would have to make is to define CLOCK_PROCESS_CPUTIME_ID = 2 and use that instead of CLOCK_MONOTONIC_RAW.

However, the best answer is probably the one given by jonrsharpe, which is to use timeit or one of the other profiling tools that comes with Python.

Range of time.clock() in Python

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