I am using the following piece of code to extract a date from a string:
try:
my_date = datetime.strptime(input_date, "%Y-%m-%d").date()
except ValueError:
my_date = None
If I run this 750,000 times, it takes 19.144 seconds (determined with cProfile). Now I replace this with the following (ugly) code:
a= 1000 * int(input_date[0])
b= 100 * int(input_date[1])
c= 10 * int(input_date[2])
d= 1 * int(input_date[3])
year = a+b+c+d
c= 10 * int(input_date[5])
d= 1 * int(input_date[6])
month = c+d
c= 10 * int(input_date[8])
d= 1 * int(input_date[9])
day = c+d
try:
my_date = date(year, month, day)
except ValueError:
my_date = None
If I run this 750,000 times, it only takes 5.946 seconds. However, I find the code really ugly. Is there another fast way to extract a date from a string, without using strptime?
Yes, there are faster methods to parse a date than datetime.strptime()
, if you forgo a lot of flexibility and validation. strptime()
allows both numbers with and without zero-padding, and it only matches strings that use the right separators, whilst your 'ugly' version doesn't.
You should always use the timeit
module for time trials, it is far more accurate than cProfile
here.
Indeed, your 'ugly' approach is twice as fast as strptime()
:
>>> from datetime import date, datetime
>>> import timeit
>>> def ugly(input_date):
... a= 1000 * int(input_date[0])
... b= 100 * int(input_date[1])
... c= 10 * int(input_date[2])
... d= 1 * int(input_date[3])
... year = a+b+c+d
... c= 10 * int(input_date[5])
... d= 1 * int(input_date[6])
... month = c+d
... c= 10 * int(input_date[8])
... d= 1 * int(input_date[9])
... day = c+d
... try:
... my_date = date(year, month, day)
... except ValueError:
... my_date = None
...
>>> def strptime(input_date):
... try:
... my_date = datetime.strptime(input_date, "%Y-%m-%d").date()
... except ValueError:
... my_date = None
...
>>> timeit.timeit('f("2014-07-08")', 'from __main__ import ugly as f')
4.21576189994812
>>> timeit.timeit('f("2014-07-08")', 'from __main__ import strptime as f')
9.873773097991943
Your approach can be improved upon though; you could use slicing:
>>> def slicing(input_date):
... try:
... year = int(input_date[:4])
... month = int(input_date[5:7])
... day = int(input_date[8:])
... my_date = date(year, month, day)
... except ValueError:
... my_date = None
...
>>> timeit.timeit('f("2014-07-08")', 'from __main__ import slicing as f')
1.7224829196929932
Now it is almost 6 times faster. I also moved the int()
calls into the try
- except
to handle invalid input when converting strings to integers.
You could also use str.split()
to get the parts, but that makes it slightly slower again:
>>> def split(input_date):
... try:
... my_date = date(*map(int, input_date.split('-')))
... except ValueError:
... my_date = None
...
>>> timeit.timeit('f("2014-07-08")', 'from __main__ import split as f')
2.294667959213257