pythonperformancedatetimestrptime

A faster strptime?


I have code which reads vast numbers of dates in 'YYYY-MM-DD' format. Parsing all these dates, so that it can add one, two, or three days then write back in the same format is slowing things down quite considerably.

 3214657   14.330    0.000  103.698    0.000 trade.py:56(effective)
 3218418   34.757    0.000   66.155    0.000 _strptime.py:295(_strptime)

 day = datetime.datetime.strptime(endofdaydate, "%Y-%m-%d").date()

Any suggestions how to speed it up a bit (or a lot)?


Solution

  • Python 3.7+: fromisoformat()

    Since Python 3.7, the datetime class has a method fromisoformat. It should be noted that this can also be applied to this question:

    Performance vs. strptime()

    Explicit string slicing may give you about a 9x increase in performance compared to normal strptime, but you can get about a 90x increase with the built-in fromisoformat method!

    %timeit isofmt(datelist)
    569 µs ± 8.45 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
    
    %timeit slice2int(datelist)
    5.51 ms ± 48.9 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
    
    %timeit normalstrptime(datelist)
    52.1 ms ± 1.27 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)
    
    from datetime import datetime, timedelta
    base, n = datetime(2000, 1, 1, 1, 2, 3, 420001), 10000
    datelist = [(base + timedelta(days=i)).strftime('%Y-%m-%d') for i in range(n)]
    
    def isofmt(l):
        return list(map(datetime.fromisoformat, l))
        
    def slice2int(l):   
        def slicer(t):
            return datetime(int(t[:4]), int(t[5:7]), int(t[8:10]))
        return list(map(slicer, l))
    
    def normalstrptime(l):
        return [datetime.strptime(t, '%Y-%m-%d') for t in l]
        
    print(isofmt(datelist[0:1]))
    print(slice2int(datelist[0:1]))
    print(normalstrptime(datelist[0:1]))
    
    # [datetime.datetime(2000, 1, 1, 0, 0)]
    # [datetime.datetime(2000, 1, 1, 0, 0)]
    # [datetime.datetime(2000, 1, 1, 0, 0)]
    

    Python 3.8.3rc1 x64 / Win10