Parse time from string in UTC format in a way comparable with the current time stamp

user_3057855 0
Viewed 864

I would like to do create a pandas date range ranging from a parsed time to the current time, both in UTC. This is my best effort so far:

import dateutil
from datetime import datetime, timezone

start_time = dateutil.parser.isoparse ('2021-01-01T00Z')
end_time = datetime.now (timezone.utc)

Both timestamps are in the UTC timezone now, but creating the date range fails nevertheless:

> timestamps = pd.date_range (start=start_time, end=end_time, freq='H')
TypeError: Start and end cannot both be tz-aware with different timezones

Cause is that the tzinfo objects of both timestaps are UTC like, but of different types:

> print (start_time, end_time, type (start_time.tzinfo), type (end_time.tzinfo))
datetime.datetime(2020, 1, 1, 0, 0, tzinfo=tzutc()),
datetime.datetime(2021, 5, 13, 5, 45, 56, 866181, tzinfo=datetime.timezone.utc),
dateutil.tz.tz.tzutc,
datetime.timezone

So I'm stuck here. Is there a valid way to do this ? This could be either by parsing an ISO time format in UTC via 'datetime' or getting the current system time in UTC via dateutil. I did not find a solution for any of these.

Edit: Copy/paste error in the code examples

pandas utc timezone datetime python
2 Answers

I'm not a pro but I made some research and found this solution using astimezone():

import dateutil
from datetime import datetime, timezone

start_time = dateutil.parser.isoparse ('2021-01-01T00Z').astimezone(timezone.utc)
end_time = datetime.now (timezone.utc)
timestamps = pd.date_range (start=start_time, end=end_time, freq='H')
timestamps

which gives :

DatetimeIndex(['2021-01-01 00:00:00+00:00', '2021-01-01 01:00:00+00:00',
               '2021-01-01 02:00:00+00:00', '2021-01-01 03:00:00+00:00',
               '2021-01-01 04:00:00+00:00', '2021-01-01 05:00:00+00:00',
               '2021-01-01 06:00:00+00:00', '2021-01-01 07:00:00+00:00',
               '2021-01-01 08:00:00+00:00', '2021-01-01 09:00:00+00:00',
               ...
               '2021-05-12 21:00:00+00:00', '2021-05-12 22:00:00+00:00',
               '2021-05-12 23:00:00+00:00', '2021-05-13 00:00:00+00:00',
               '2021-05-13 01:00:00+00:00', '2021-05-13 02:00:00+00:00',
               '2021-05-13 03:00:00+00:00', '2021-05-13 04:00:00+00:00',
               '2021-05-13 05:00:00+00:00', '2021-05-13 06:00:00+00:00'],
              dtype='datetime64[ns, UTC]', length=3175, freq='H')
user_151606010

Ok, with that hint of zazz in the comment above, I got it !

start_time = dateutil.parser.isoparse ('2020-01-01T00Z').astimezone (timezone.utc)
end_time = datetime.now (timezone.utc)

pd.date_range (start=start_time, end=end_time, freq='D')

The secret ingredient here is the 'Z' modifier in the parsed string which tags it to be in UTC time. Then, 'astimezone (timezone.utc)' does only change the timezone tag, but does not convert the timestamp value. Works !

Thank you very much for your help !

user_30578550
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