Measuring elapsed time with the Time module

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执念已碎
执念已碎 2020-12-02 03:13

With the Time module in python is it possible to measure elapsed time? If so, how do I do that?

I need to do this so that if the cursor has been in a widget for a c

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  • 2020-12-02 03:52

    Another nice way to time things is to use the with python structure.

    with structure is automatically calling __enter__ and __exit__ methods which is exactly what we need to time things.

    Let's create a Timer class.

    from time import time
    
    class Timer():
        def __init__(self, message):
            self.message = message
        def __enter__(self):
            self.start = time()
            return None  # could return anything, to be used like this: with Timer("Message") as value:
        def __exit__(self, type, value, traceback):
            elapsed_time = (time() - self.start) * 1000
            print(self.message.format(elapsed_time))
    

    Then, one can use the Timer class like this:

    with Timer("Elapsed time to compute some prime numbers: {}ms"):
        primes = []
        for x in range(2, 500):
            if not any(x % p == 0 for p in primes):
                primes.append(x)
        print("Primes: {}".format(primes))
    

    The result is the following:

    Primes: [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97, 101, 103, 107, 109, 113, 127, 131, 137, 139, 149, 151, 157, 163, 167, 173, 179, 181, 191, 193, 197, 199, 211, 223, 227, 229, 233, 239, 241, 251, 257, 263, 269, 271, 277, 281, 283, 293, 307, 311, 313, 317, 331, 337, 347, 349, 353, 359, 367, 373, 379, 383, 389, 397, 401, 409, 419, 421, 431, 433, 439, 443, 449, 457, 461, 463, 467, 479, 487, 491, 499]

    Elapsed time to compute some prime numbers: 5.01704216003418ms

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  • 2020-12-02 03:55

    In programming, there are 2 main ways to measure time, with different results:

    >>> print(time.process_time()); time.sleep(10); print(time.process_time())
    0.11751394000000001
    0.11764988400000001  # took  0 seconds and a bit
    >>> print(time.perf_counter()); time.sleep(10); print(time.perf_counter())
    3972.465770326
    3982.468109075       # took 10 seconds and a bit
    
    • Processor Time: This is how long this specific process spends actively being executed on the CPU. Sleep, waiting for a web request, or time when only other processes are executed will not contribute to this.

      • Use time.process_time()
    • Wall-Clock Time: This refers to how much time has passed "on a clock hanging on the wall", i.e. outside real time.

      • Use time.perf_counter()

        • time.time() also measures wall-clock time but can be reset, so you could go back in time
        • time.monotonic() cannot be reset (monotonic = only goes forward) but has lower precision than time.perf_counter()
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  • 2020-12-02 04:00

    Here is an update to Vadim Shender's clever code with tabular output:

    import collections
    import time
    from functools import wraps
    
    PROF_DATA = collections.defaultdict(list)
    
    def profile(fn):
        @wraps(fn)
        def with_profiling(*args, **kwargs):
            start_time = time.time()
            ret = fn(*args, **kwargs)
            elapsed_time = time.time() - start_time
            PROF_DATA[fn.__name__].append(elapsed_time)
            return ret
        return with_profiling
    
    Metrics = collections.namedtuple("Metrics", "sum_time num_calls min_time max_time avg_time fname")
    
    def print_profile_data():
        results = []
        for fname, elapsed_times in PROF_DATA.items():
            num_calls = len(elapsed_times)
            min_time = min(elapsed_times)
            max_time = max(elapsed_times)
            sum_time = sum(elapsed_times)
            avg_time = sum_time / num_calls
            metrics = Metrics(sum_time, num_calls, min_time, max_time, avg_time, fname)
            results.append(metrics)
        total_time = sum([m.sum_time for m in results])
        print("\t".join(["Percent", "Sum", "Calls", "Min", "Max", "Mean", "Function"]))
        for m in sorted(results, reverse=True):
            print("%.1f\t%.3f\t%d\t%.3f\t%.3f\t%.3f\t%s" % (100 * m.sum_time / total_time, m.sum_time, m.num_calls, m.min_time, m.max_time, m.avg_time, m.fname))
        print("%.3f Total Time" % total_time)
    
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  • 2020-12-02 04:01

    time.time() will do the job.

    import time
    
    start = time.time()
    # run your code
    end = time.time()
    
    elapsed = end - start
    

    You may want to look at this question, but I don't think it will be necessary.

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  • 2020-12-02 04:07

    Vadim Shender response is great. You can also use a simpler decorator like below:

    import datetime
    def calc_timing(original_function):                            
        def new_function(*args,**kwargs):                        
            start = datetime.datetime.now()                     
            x = original_function(*args,**kwargs)                
            elapsed = datetime.datetime.now()                      
            print("Elapsed Time = {0}".format(elapsed-start))     
            return x                                             
        return new_function()  
    
    @calc_timing
    def a_func(*variables):
        print("do something big!")
    
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  • 2020-12-02 04:08

    For a longer period.

    import time
    start_time = time.time()
    ...
    e = int(time.time() - start_time)
    print('{:02d}:{:02d}:{:02d}'.format(e // 3600, (e % 3600 // 60), e % 60))
    

    would print

    00:03:15
    

    if more than 24 hours

    25:33:57
    

    That is inspired by Rutger Hofste's answer. Thank you Rutger!

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