I have CSV data files with timestamped records that are in local time. Unfortunately the data files cover the period where daylight saving time changes (Nov 3rd 2013) so th
In C#:
// Define the input values.
string[] input =
{
"2013-11-03 00:45:00",
"2013-11-03 01:00:00",
"2013-11-03 01:15:00",
"2013-11-03 01:30:00",
"2013-11-03 01:45:00",
"2013-11-03 01:00:00",
"2013-11-03 01:15:00",
"2013-11-03 01:30:00",
"2013-11-03 01:45:00",
"2013-11-03 02:00:00",
};
// Get the time zone the input is meant to be interpreted in.
TimeZoneInfo tz = TimeZoneInfo.FindSystemTimeZoneById("Eastern Standard Time");
// Create an array for the output values
DateTimeOffset[] output = new DateTimeOffset[input.Length];
// Start with the assumption that DST is active, as ambiguities occur when moving
// out of daylight time into standard time.
bool dst = true;
// Iterate through the input.
for (int i = 0; i < input.Length; i++)
{
// Parse the input string as a DateTime with Unspecified kind
DateTime dt = DateTime.ParseExact(input[i], "yyyy-MM-dd HH:mm:ss",
CultureInfo.InvariantCulture);
// Determine the offset.
TimeSpan offset;
if (tz.IsAmbiguousTime(dt))
{
// Get the possible offsets, and use the DST flag and the previous entry
// to determine if we are past the transition point. This only works
// because we have outside knowledge that the items are in sequence.
TimeSpan[] offsets = tz.GetAmbiguousTimeOffsets(dt);
offset = dst && (i == 0 || dt >= output[i - 1].DateTime)
? offsets[1] : offsets[0];
}
else
{
// The value is unambiguous, so just get the single offset it can be.
offset = tz.GetUtcOffset(dt);
}
// Use the determined values to construct a DateTimeOffset
DateTimeOffset dto = new DateTimeOffset(dt, offset);
// We can unambiguously check a DateTimeOffset for daylight saving time,
// which sets up the DST flag for the next iteration.
dst = tz.IsDaylightSavingTime(dto);
// Save the DateTimeOffset to the output array.
output[i] = dto;
}
// Show the output for debugging
foreach (var dto in output)
{
Console.WriteLine("{0:yyyy-MM-dd HH:mm:ss zzzz} => {1:yyyy-MM-dd HH:mm:ss} UTC",
dto, dto.UtcDateTime);
}
Output:
2013-11-03 00:45:00 -04:00 => 2013-11-03 04:45:00 UTC
2013-11-03 01:00:00 -04:00 => 2013-11-03 05:00:00 UTC
2013-11-03 01:15:00 -04:00 => 2013-11-03 05:15:00 UTC
2013-11-03 01:30:00 -04:00 => 2013-11-03 05:30:00 UTC
2013-11-03 01:45:00 -04:00 => 2013-11-03 05:45:00 UTC
2013-11-03 01:00:00 -05:00 => 2013-11-03 06:00:00 UTC
2013-11-03 01:15:00 -05:00 => 2013-11-03 06:15:00 UTC
2013-11-03 01:30:00 -05:00 => 2013-11-03 06:30:00 UTC
2013-11-03 01:45:00 -05:00 => 2013-11-03 06:45:00 UTC
2013-11-03 02:00:00 -05:00 => 2013-11-03 07:00:00 UTC
Note that this assumes that the first time you encounter an ambiguous time like 1:00 that it will be in DST. Say your list was truncated to just the last 5 entries - you wouldn't know that those were in standard time. There's not much you could do in that particular case.
If successive timestamps can't go backwards if expressed as time in UTC then this Python script can convert the local time into UTC:
#!/usr/bin/env python3
import sys
from datetime import datetime, timedelta
import pytz # $ pip install pytz
tz = pytz.timezone('America/New_York' if len(sys.argv) < 2 else sys.argv[1])
previous = None #XXX set it from UTC time: `first_entry_utc.astimezone(tz)`
for line in sys.stdin: # read from stdin
naive = datetime.strptime(line.strip(), "%Y/%m/%d %H:%M:%S") # no timezone
try:
local = tz.localize(naive, is_dst=None) # attach timezone info
except pytz.AmbiguousTimeError:
# assume ambiguous time always corresponds to True -> False transition
local = tz.localize(naive, is_dst=True)
if previous >= local: # timestamps must be increasing
local = tz.localize(naive, is_dst=False)
assert previous < local
#NOTE: allow NonExistentTimeError to propagate (there shouldn't be
# invalid local times in the input)
previous = local
utc = local.astimezone(pytz.utc)
timestamp = utc.timestamp()
time_format = "%Y-%m-%d %H:%M:%S %Z%z"
print("{local:{time_format}}; {utc:{time_format}}; {timestamp:.0f}"
.format_map(vars()))
2013/11/03 00:45:00
2013/11/03 01:00:00
2013/11/03 01:15:00
2013/11/03 01:30:00
2013/11/03 01:45:00
2013/11/03 01:00:00
2013/11/03 01:15:00
2013/11/03 01:30:00
2013/11/03 01:45:00
2013/11/03 02:00:00
2013-11-03 00:45:00 EDT-0400; 2013-11-03 04:45:00 UTC+0000; 1383453900
2013-11-03 01:00:00 EDT-0400; 2013-11-03 05:00:00 UTC+0000; 1383454800
2013-11-03 01:15:00 EDT-0400; 2013-11-03 05:15:00 UTC+0000; 1383455700
2013-11-03 01:30:00 EDT-0400; 2013-11-03 05:30:00 UTC+0000; 1383456600
2013-11-03 01:45:00 EDT-0400; 2013-11-03 05:45:00 UTC+0000; 1383457500
2013-11-03 01:00:00 EST-0500; 2013-11-03 06:00:00 UTC+0000; 1383458400
2013-11-03 01:15:00 EST-0500; 2013-11-03 06:15:00 UTC+0000; 1383459300
2013-11-03 01:30:00 EST-0500; 2013-11-03 06:30:00 UTC+0000; 1383460200
2013-11-03 01:45:00 EST-0500; 2013-11-03 06:45:00 UTC+0000; 1383461100
2013-11-03 02:00:00 EST-0500; 2013-11-03 07:00:00 UTC+0000; 1383462000