ciso8601
converts ISO 8601 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, 3.6, 3.7b.
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Contents
% pip install ciso8601
In [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)
Version 2.0.0 of ciso8601
changed the core implementation. This was not entirely backwards compatible, and care should be taken when migrating
See CHANGELOG for the Migration Guide.
Starting in v2.0.0, ciso8601
offers strong guarantees when it comes to parsing strings.
parse_datetime(dt: String): datetime
is a function that takes a string and either:
- Returns a properly parsed Python datetime, if and only if the entire string conforms to the supported subset of ISO 8601
- Raises a
ValueError
with a description of the reason why the string doesn't conform to the supported subset of ISO 8601
If time zone information is provided, an aware datetime object will be returned. Otherwise, a naive datetime is returned.
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: 204 ns per loop
In [4]: %timeit datetime.datetime.strptime(ds, "%Y-%m-%dT%H:%M:%S.%f")
100000 loops, best of 3: 15 µs per loop
In [5]: %timeit dateutil.parser.parse(ds)
10000 loops, best of 3: 122 µs per loop
In [6]: %timeit aniso8601.parse_datetime(ds)
10000 loops, best of 3: 28.9 µs per loop
In [7]: %timeit iso8601.parse_date(ds)
10000 loops, best of 3: 42 µs per loop
In [8]: %timeit isodate.parse_datetime(ds)
10000 loops, best of 3: 69.4 µs per loop
In [9]: %timeit arrow.get(ds).datetime
10000 loops, best of 3: 87 µs per loop
ciso8601 takes 0.204us, which is 73x faster than datetime's strptime, which is not a full ISO8601 parser. It is 141x 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)
1000000 loops, best of 3: 525 ns per loop
In [4]: %timeit dateutil.parser.parse(ds)
10000 loops, best of 3: 162 µs per loop
In [5]: %timeit aniso8601.parse_datetime(ds)
10000 loops, best of 3: 36.8 µs per loop
In [6]: %timeit iso8601.parse_date(ds)
10000 loops, best of 3: 53.5 µs per loop
In [7]: %timeit isodate.parse_datetime(ds)
10000 loops, best of 3: 82.6 µs per loop
In [8]: %timeit arrow.get(ds).datetime
10000 loops, best of 3: 104 µs per loop
Even with time zone information, ciso8601
is 70x as fast as aniso8601
.
Tested on Python 2.7.10 on macOS 10.12.6 using the following modules:
aniso8601==1.2.1
arrow==0.10.0
ciso8601==1.0.4
iso8601==0.1.12
isodate==0.5.4
python-dateutil==2.6.1
In Python 2, ciso8601
uses the pytz library while parsing timestamps with time zone information. This means that if you wish to parse such timestamps, you must first install pytz
:
pip install pytz
Otherwise, ciso8601
will raise an exception when you try to parse a timestamp with time zone information:
In [2]: ciso8601.parse_datetime('2014-12-05T12:30:45.123456-05:30')
Out[2]: ImportError: Cannot parse a timestamp with time zone information without the pytz dependency. Install it with `pip install pytz`.
pytz
is intentionally not an explicit dependency of ciso8601
. This is because many users use ciso8601
to parse only naive timestamps, and therefore don't need this extra dependency.
In Python 3, ciso8601
makes use of the built-in datetime.timezone class instead, so pytz is not necessary.
ciso8601
only supports the most common subset of ISO 8601.
The following date formats are supported:
Format | Example | Supported |
---|---|---|
YYYY-MM-DD |
2018-04-29 |
✅ |
YYYY-MM |
2018-04 |
✅ |
YYYYMMDD |
2018-04 |
✅ |
--MM-DD (omitted year) |
--04-29 |
❌ |
--MMDD (omitted year) |
--0429 |
❌ |
±YYYYY-MM (>4 digit year) |
+10000-04 |
❌ |
+YYYY-MM (leading +) |
+2018-04 |
❌ |
-YYYY-MM (negative -) |
-2018-04 |
❌ |
Week dates or ordinal dates are not currently supported.
Format | Example | Supported |
---|---|---|
YYYY-Www (week date) |
2009-W01 |
❌ |
YYYYWww (week date) |
2009W01 |
❌ |
YYYY-Www-D (week date) |
2009-W01-1 |
❌ |
YYYYWwwD (week date) |
2009-W01-1 |
❌ |
YYYY-DDD (ordinal date) |
1981-095 |
❌ |
YYYYDDD (ordinal date) |
1981095 |
❌ |
Times are optional and are separated from the date by the letter T
.
Consistent with RFC 3339, ciso860
also allows either a space character, or a lower-case t
, to be used instead of a T
.
The following time formats are supported:
Format | Example | Supported |
---|---|---|
hh |
11 |
✅ |
hhmm |
1130 |
✅ |
hh:mm |
11:30 |
✅ |
hhmmss |
113059 |
✅ |
hh:mm:ss |
11:30:59 |
✅ |
hhmmss.ssssss |
113059.123456 |
✅ |
hh:mm:ss.ssssss |
11:30:59.123456 |
✅ |
hhmmss,ssssss |
113059,123456 |
✅ |
hh:mm:ss,ssssss |
11:30:59,123456 |
✅ |
Midnight (special case) | 24:00:00 |
✅ |
hh.hhh (fractional hours) |
11.5 |
❌ |
hh:mm.mmm (fractional minutes) |
11:30.5 |
❌ |
Note: Python datetime objects only have microsecond precision (6 digits). Any additional precision will be truncated.
Time zone information may be provided in one of the following formats:
Format | Example | Supported |
---|---|---|
Z |
Z |
✅ |
z |
z |
✅ |
±hh |
+11 |
✅ |
±hhmm |
+1130 |
✅ |
±hh:mm |
+11:30 |
✅ |
While the ISO 8601 specification allows the use of MINUS SIGN (U+2212) in the time zone separator, ciso8601
only supports the use of the HYPHEN-MINUS (U+002D) character.
Consistent with RFC 3339, ciso860
also allows a lower-case z
to be used instead of a Z
.
It takes more time to parse timestamps with time zone information, especially if they're not in UTC. However, there are times when you don't care about time zone information, and wish to produce naive datetimes instead. For example, if you are certain that your program will only parse timestamps from a single time zone, you might want to strip the time zone information and only output naive datetimes.
In these limited cases, there is a second function provided.
parse_datetime_as_naive
will ignore any time zone information it finds and, as a result, is faster for timestamps containing time zone information.
In [1]: import ciso8601
In [2]: ciso8601.parse_datetime_as_naive('2014-12-05T12:30:45.123456-05:30')
Out[2]: datetime.datetime(2014, 12, 5, 12, 30, 45, 123456)
NOTE: parse_datetime_as_naive
is only useful in the case where your timestamps have time zone information, but you want to ignore it. This is somewhat unusual.
If your timestamps don't have time zone information (i.e. are naive), simply use parse_datetime
. It is just as fast.