ciso8601 converts ISO8601 date time strings into Python datetime objects. Since it's written as a C module, it is much faster than other Python libraries. Tested with Python 2.7 + 3.4 + 3.5.
(Interested in working on projects like this? Close.io is looking for great engineers to join our team)
Contents
% pip install ciso8601In [1]: import ciso8601
In [2]: ciso8601.parse_datetime('2014-12-05T12:30:45.123456-05:30')
Out[2]: datetime.datetime(2014, 12, 5, 12, 30, 45, 123456, tzinfo=pytz.FixedOffset(330))
In [3]: ciso8601.parse_datetime('20141205T123045')
Out[3]: datetime.datetime(2014, 12, 5, 12, 30, 45)
In [4]: ciso8601.parse_datetime_unaware('2014-12-05T12:30:45.123456-05:30')
Out[4]: datetime.datetime(2014, 12, 5, 12, 30, 45, 123456)Date time string with no time zone information:
In [1]: import datetime, aniso8601, iso8601, isodate, dateutil.parser, arrow, ciso8601
In [2]: ds = u'2014-01-09T21:48:00.921000'
In [3]: %timeit ciso8601.parse_datetime(ds)
1000000 loops, best of 3: 320 ns per loop
In [4]: %timeit datetime.datetime.strptime(ds, "%Y-%m-%dT%H:%M:%S.%f")
100000 loops, best of 3: 19.7 us per loop
In [5]: %timeit dateutil.parser.parse(ds)
10000 loops, best of 3: 111 us per loop
In [6]: %timeit aniso8601.parse_datetime(ds)
10000 loops, best of 3: 31.1 us per loop
In [7]: %timeit iso8601.parse_date(ds)
10000 loops, best of 3: 70.9 us per loop
In [8]: %timeit isodate.parse_datetime(ds)
10000 loops, best of 3: 81.8 us per loop
In [9]: %timeit arrow.get(ds).datetime
10000 loops, best of 3: 41.4 us per loopciso8601 takes 0.32us, which is 62x faster than datetime's strptime, which is not a full ISO8601 parser. It is 97x faster than aniso8601, the next fastest ISO8601 parser in this comparison.
Date time string with time zone information:
In [1]: import datetime, aniso8601, iso8601, isodate, dateutil.parser, arrow, ciso8601
In [2]: ds = u'2014-01-09T21:48:00.921000+05:30'
In [3]: %timeit ciso8601.parse_datetime(ds)
100000 loops, best of 3: 3.62 us per loop
In [4]: %timeit dateutil.parser.parse(ds)
10000 loops, best of 3: 126 us per loop
In [5]: %timeit aniso8601.parse_datetime(ds)
10000 loops, best of 3: 34.9 us per loop
In [6]: %timeit iso8601.parse_date(ds)
10000 loops, best of 3: 94 us per loop
In [7]: %timeit isodate.parse_datetime(ds)
10000 loops, best of 3: 91.3 us per loop
In [8]: %timeit arrow.get(ds).datetime
10000 loops, best of 3: 56.2 us per loopEven with time zone information, ciso8601 is almost 10x faster than aniso8601.
Tested on Python 2.7 on OS X 10.9.2 using the following modules:
aniso8601==0.82
arrow==0.4.2
ciso8601==1.0
iso8601==0.1.10
isodate==0.5.0
python-dateutil==2.2Dates may have one of the following formats:
YYYYMMDDYYYY-MM-DDYYYY-MM
Week dates or ordinal dates are not currently supported.
Times are optional and are separated by the letter T or also by space (unlike ISO8601). The following time formats are supported:
hhhhmmorhh:mmhhmmssorhh:mm:ss
Fractions of a second may be provided, separated by . or ,. Up to 6 digits are supported, excessive digits will be ignored.
Time zone information may be provided in one of the following formats:
Z±hh±hh:mm±hhmm
If time zone information is provided, an aware datetime object will be returned. Otherwise, the datetime is unaware. Please note that it takes more time to parse aware datetimes, especially if they're not in UTC. If you don't care about time zone information, use the parse_datetime_unaware method, which will discard any time zone information and is faster. Parsing aware date times requires the pytz module, otherwise time zone information is ignored and unaware datetimes are returned.
If parsing fails, None will be returned. The parser will attempt to parse as much of the date time as possible.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent