datetime - python converting string in localtime to UTC epoch timestamp

Question

I have strings in YMD hms format that had the timezone stripped. But I know they are in Eastern time with daylight savings time.

I am trying to convert them into epoch timestamps for UTC time.

I wrote the following function:

def ymdhms_timezone_dst_to_epoch(input_str,  tz="US/Eastern"):
    print(input_str)
    dt = datetime.datetime.fromtimestamp(time.mktime(time.strptime(input_str,'%Y-%m-%d %H:%M:%S')))
    local_dt = pytz.timezone(tz).localize(dt)
    print(local_dt.strftime('%Y-%m-%d %H:%M:%S %Z%z'))
    utc_dt = local_dt.astimezone(pytz.utc)
    print(utc_dt.strftime('%Y-%m-%d %H:%M:%S %Z%z'))    
    e = int(utc_dt.strftime("%s"))
    print(e)
    return e

Given string `2015-04-20 21:12:07` this prints:

    2015-04-20 21:12:07
    2015-04-20 21:12:07 EDT-0400 #<- so far so good?
    2015-04-21 01:12:07 UTC+0000 #<- so far so good?
    1429596727

which looks ok up to the epoch timestamp. But http://www.epochconverter.com/epoch/timezones.php?epoch=1429596727 says it should mao to Greenwich Mean Time Apr 21 2015 06:12:07 UTC.

What is wrong?

Answer 1

I have strings in YMD hms format that had the timezone stripped. But I know they are in Eastern time with daylight savings time.

A portable way is to use pytz:

#!/usr/bin/env python
from datetime import datetime
import pytz # $ pip install pytz

naive_dt = datetime.strptime('2015-04-20 21:12:07', '%Y-%m-%d %H:%M:%S')
tz = pytz.timezone('US/Eastern')
eastern_dt = tz.normalize(tz.localize(naive_dt))
print(eastern_dt)
# -> 2015-04-20 21:12:07-04:00

I am trying to convert them into epoch timestamps for UTC time.

timestamp = (eastern_dt - datetime(1970, 1, 1, tzinfo=pytz.utc)).total_seconds()
# -> 1429578727.0

See Converting datetime.date to UTC timestamp in Python.

---

There are multiple issues in your code:

• time.mktime() may return a wrong result for ambiguous input time (50% chance) e.g., during "fall back" DST transition in the Fall

• time.mktime() and datetime.fromtimestamp() may fail for past/future dates if they have no access to a historical timezone database on a system (notably, Windows)

• localize(dt) may return a wrong result for ambiguous or non-existent time i.e., during DST transitions. If you know that the time corresponds to the summer time then use is_dst=True. tz.normalize() is necessary here, to adjust possible non-existing times in the input

• utc_dt.strftime("%s") is not portable and it does not respect tzinfo object. It interprets input as a local time i.e., it returns a wrong result unless your local timezone is UTC.

---

Can I just always set is_dst=True?

You can, if you don't mind getting imprecise results for ambiguous or non-existent times e.g., there is DST transition in the Fall in America/New_York time zone:

>>> from datetime import datetime
>>> import pytz # $ pip install pytz
>>> tz = pytz.timezone('America/New_York')
>>> ambiguous_time = datetime(2015, 11, 1, 1, 30)
>>> time_fmt = '%Y-%m-%d %H:%M:%S%z (%Z)'
>>> tz.localize(ambiguous_time).strftime(time_fmt)
'2015-11-01 01:30:00-0500 (EST)'
>>> tz.localize(ambiguous_time, is_dst=False).strftime(time_fmt) # same
'2015-11-01 01:30:00-0500 (EST)'
>>> tz.localize(ambiguous_time, is_dst=True).strftime(time_fmt) # different
'2015-11-01 01:30:00-0400 (EDT)'
>>> tz.localize(ambiguous_time, is_dst=None).strftime(time_fmt) 
Traceback (most recent call last):
...
pytz.exceptions.AmbiguousTimeError: 2015-11-01 01:30:00

The clocks are turned back at 2a.m. on the first Sunday in November:

is_dst disambiguation flag may have three values:

• False -- default, assume the winter time
• True -- assume the summer time
• None -- raise an exception for ambiguous/non-existent times.

is_dst value is ignored for existing unique local times.

Here's a plot from PEP 0495 -- Local Time Disambiguation that illustrates the DST transition:

The local time repeats itself twice in the fold (summer time -- before the fold, winter time -- after).

To be able to disambiguate the local time automatically, you need some additional info e.g., if you read a series of local times then it may help if you know that they are sorted: Parsing of Ordered Timestamps in Local Time (to UTC) While Observing Daylight Saving Time.