I have a variable assigned as start time and want to subtract the same with current system time inorder to calculate total ours.
eg:
from datetime import datetime
start = "9:45:00"
total_hours = start - datetime.now().strftime("%H:%M:%S")
is this a correct approach?
Related
I have a date variable calls today_date as below. I need to get the 1st calendar day of the current and next month.
In my case, today_date is 4/17/2021, I need to create two more variables calls first_day_current which should be 4/1/2021, and first_day_next which should be 5/1/2021.
Any suggestions are greatly appreciated
import datetime as dt
today_date
'2021-04-17'
Getting just the first date of a month is quite simple - since it equals 1 all the time. You can even do this without needing the datetime module to simplify calculations for you, if today_date is always a string "Year-Month-Day" (or any consistent format - parse it accordingly)
today_date = '2021-04-17'
y, m, d = today_date.split('-')
first_day_current = f"{y}-{m}-01"
y, m = int(y), int(m)
first_day_next = f"{y+(m==12)}-{m%12+1}-01"
If you want to use datetime.date(), then you'll anyway have to convert the string to (year, month, date) ints to give as arguments (or do today_date = datetime.date.today().
Then .replace(day=1) to get first_day_current.
datetime.timedelta can't add months (only upto weeks), so you'll need to use other libraries for this. But it's more imports and calculations to do the same thing in effect.
I found out pd.offsets could accomplish this task as below -
import datetime as dt
import pandas as pd
today_date #'2021-04-17' this is a variable that is being created in the program
first_day_current = today_date.replace(day=1) # this will be 2021-04-01
next_month = first_day_current + pd.offsets.MonthBegin(n=1)
first_day_next = next_month.strftime('%Y-%m-%d') # this will be 2021-05-01
my time zone is "Australia/Melbourne" (I have multiple zones like this when I give this to my function) and I need the output like this ASET(GMT +10). How can I reach my answer?
Thank you
assuming you have date and time available (see my comment), the easiest way is probably strftime:
from datetime import datetime
from dateutil import tz
timezone = tz.gettz("Australia/Melbourne")
dt = datetime.now(timezone)
print(f"{dt.strftime('%Z')}(GMT{dt.strftime('%z')})")
# AEST(GMT+1000)
If you exactly want to get the specified output, I suppose you have to go a little more sophisticated:
total_minutes, seconds = divmod(dt.utcoffset().total_seconds(), 60)
hours, minutes = divmod(total_minutes, 60)
utcoff = f"{int(hours):+d}:{int(minutes):02d}" if minutes else f"{int(hours):+d}"
print(f"{dt.strftime('%Z')}(GMT{utcoff})")
# AEST(GMT+10)
I have a code which I have it's performance timestamped, and I want to measure the average of time it took to run it on multiple computers, but I just cant figure out how to use the datetime module in python.
Here is how my procedure looks:
1) I have the code which simply writes into a text file the log, where the timestamp looks like
t1=datetime.datetime.now()
...
t2=datetime.datetime.now()
stamp= t2-t1
And that stamp variable is just written in say log.txt so in the log file it looks like 0:07:23.160896 so it seems like it's %H:%M:%S.%f format.
2) Then I run a second python script which reads in the log.txt file and it reads the 0:07:23.160896 value as a string.
The problem is I don't know how to work with this value because if I import it as a datetime it will also append and imaginary year and month and day to it, which I don't want, I simply just want to work with hours and minutes and seconds and microseconds to add them up or do an average.
For example I can just open it in Libreoffice and add the 0:07:23.160896 to 0:00:48.065130 which will give 0:08:11.226026 and then just divide by 2 which will give 0:04:05.613013, and I just can't possibly do that in python or I dont know how to do it.
I have tried everything, but neither datetime.datetime, nor datetime.timedelta allows simply multiplication and division like that. If I just do a y=datetime.datetime.strptime('0:07:23.160896','%H:%M:%S.%f') it will just give out 1900-01-01 00:07:23.160896 and I can't just take a y*2 like that, it doesnt allow arithmetic operations, plus if if I convert it into a timedelta it will also multiply the year,which is ridiculous. I simply just want to add and subtract and multiply time.
Please help me find a way to do this, and not just for 2 variables but possibly even a way to calculate the average of an entire list of timestamps like average(['0:07:23.160896' , '0:00:48.065130', '0:00:14.517086',...]) way.
I simply just want a way to calculate the average of many timestamps and give out it's average in the same format, just as you can just select a column in Libreoffice and take the AVERAGE() function which will give out the average timestamp in that column.
As you have done, you first read the string into a datetime-object using strptime: t = datetime.datetime.strptime(single_time,'%H:%M:%S.%f')
After that, convert the time part of your datestring into a timedelta, so you can easily calculate with times: tdelta = datetime.timedelta(hours=t.hour, minutes=t.minute, seconds=t.second, microseconds=t.microsecond)
Now you can easily calculate with the timedelta object, and convert at the end of the calculations back into a string by str(tdsum)
import datetime
times = ['0:07:23.160896', '0:00:48.065130', '0:12:22.324251']
# convert times in iso-format into timedelta list
tsum = datetime.timedelta()
count = 0
for single_time in times:
t = datetime.datetime.strptime(single_time,'%H:%M:%S.%f')
tdelta = datetime.timedelta(hours=t.hour, minutes=t.minute, seconds=t.second, microseconds=t.microsecond)
tsum = tsum + tdelta
count = count + 1
taverage = tsum / count
average_time = str(taverage)
print(average_time)
is there a readily-available command in Python's datetime to understand a discrete time range given as HH:MM-HH:MM or HH:MM:ss-HH:MM:ss (e.g. 07:30-12:45)? Such a range would be entered like that in a single cell from a CSV file that the script would access.
Or, might specifying just the start time and then a timedelta value be a better idea?
You can just use split() to separate the two time values, then parse each as a datetime.datetime type and then calculate the timedelta.
Example:
from datetime import datetime
time_string = "07:30-12:45"
separate_times = time_string.split("-")
parsed_times = [datetime.strptime(t, "%H:%M") for t in separate_times]
difference = parsed_times[1] - parsed_times[0]
Calling difference.total_seconds() will return the total seconds between the two times and if you aren't interested in the direction of the difference between the times, you can use abs(difference.total_seconds()).
Thats a code a friend of mine helped me with in order to get files from diferent measurement systems, timestamps and layout into on .csv file.
You enter the timeperiod or like in the case below 1 day and the code looks for this timestamps in different files and folders, adjusts timestamps (different Timezone etc.) and puts everything into one .csv file easy to plot. Now I need to rewrite that stuff for different layouts. I managed to get everything working but now I don't want to enter every single day manually into the code :-( , cause I'd need to enter it 3 times in a row --> in order to get the day for one day into one file, dateFrom and dateTo needs to be the same and in the writecsv...section you'd have to enter the date again.
here's the code:
from importer import cloudIndices, weatherall, writecsv,averagesolar
from datetime import datetime
from datetime import timedelta
dateFrom = datetime.strptime("2010-06-21", '%Y-%m-%d')
dateTo = datetime.strptime("2010-06-21", '%Y-%m-%d')
....
code
code
....
writecsv.writefile("data_20100621", header, ciData)
what can I change here so that I get an automatic loop for all data between e.g 2010-06-21 to 2011-06-21
p.s. if i'd entered 2010-06-21in dataFromand 2011-06-21 in dateTo i'd get a huge cvs. file with all the data in it ..... I thought that would be a great idea but it's not really good for plotting so I enden up manually entering day after day which isn't bad if you do it on a regular basis for 2 or 3 days but now a dates showed up and I need to rund the code over it :-(
Generally speaking you should be using datetime.datetime and datetime.timedelta, here is an example of how:
from datetime import datetime
from datetime import timedelta
# advance 5 days at a time
delta = timedelta(days=5)
start = datetime(year=1970, month=1, day=1)
end = datetime(year=1970, month=2, day=13)
print("Starting from: %s" % str(start))
while start < end:
print("advanced to: %s" % str(start))
start += delta
print("Finished at: %s" % str(start))
This little snippet creates a start and end time and a delta to advance using the tools python provides. You can modify it to fit your needs or apply it in your logic.