We Keep Coding

Whats wrong with this code for checking age?

I want to know if inputed date of birth is over 18 or under.
def is_under_18(birth):
now = date.today()
return (
now.year - birth.year < 18
or now.year - birth.year == 18 and (
now.month < birth.month
or now.month == birth.month and now.day <= birth.day
)
)
And then:
year = int(input("Year born: "))
month = int(input("Month born: "))
day = int(input("Day born: "))`
birth = date(year,month,day)
if is_under_18(birth):
print('Under 18')
else:
print('Adult')
However, the only thing is, say I add a user which his birthday is the 25th of November 2004. The program lets me add it because it does not count the month. If I add a user which was born the 1st of January 2005, it doesn't allow me because 2022-2005=17.

Your original code doesn't seem to have a problem with the dates you mention, but does have a bug as Nov 22, 2004 is "Under 18" and today's date is Nov 22, 2022 (18th birthday). Use now.day < birth.day instead.
But if you compute the birthday required to be 18 by replacing today's year with 18 less, then directly compare the dates, you don't have to have a complicated comparison:
from datetime import date
def is_under_18(birth):
# today = date.today()
today = date(2022,11,22) # for repeatability of results
born_on_or_before = today.replace(year=today.year - 18)
return birth > born_on_or_before
print(f'Today is {date.today()}')
for year,month,day in [(2004,11,21), (2004,11,22), (2004,11,23), (2004,11,25), (2005,1,1)]:
birth = date(year,month,day)
if is_under_18(birth):
print(f'{birth} Under 18')
else:
print(f'{birth} Adult')
Output:
Today is 2022-11-22
2004-11-21 Adult
2004-11-22 Adult
2004-11-23 Under 18
2004-11-25 Under 18
2005-01-01 Under 18

Not able to figure how to write if-else statement for one of the user defined cases in python

I have two API.
Australia API- This API works only for year 1985 to 2024.
USA API- I wanted this API need should work only before 1985.
Taking 4 things from user.
-Start Year
-End Year
-latitude
-longitude
sample command: python test.py -latitude '' -longitude '' -startYear '' -endYear ''
User can enter 3 ways of input.
Case 1. Start year=before 1985, end year= After 1985 ---->both AUSTRALIA and USA api run.
Case 2. Start year=At 1985 or later, end year= after 1985 ---->only AUSTRALIA api should run.
Case 3. Start year=before 1985, end year=before 1985 ------>only USA api run
Problem is that I am not able to figure out how to write the code for Case 1 after writing the code for case 2(Australia API) and case 3(USA API).
import requests
import json
import argparse
import time
import pandas as pd
import warnings
warnings.filterwarnings("ignore")
parser = argparse.ArgumentParser(description="Process some integers.")
parser.add_argument("-latitude", help="Latitude(Degress)")
parser.add_argument("-longitude", help="Longitude(Degress)")
parser.add_argument("-startYear", help="Start of the Year")
parser.add_argument("-endYear", help="End of the Year")
parser.add_argument("--verbose", help="display processing information")
start = time.time()
def main(latitude,longitude,startYear,endYear,verbose):
parameters = {
"latd": latitude, # [deg]
"latm": 00, # [deg]
"lats": 00, # [deg]
"lond": longitude, # [deg]
"lonm": 00, # [deg]
"lons": 00, # [deg]
"elev" : 00, # [km]
"year" : None, # [YYYY]
"month" : '07', # [MM]
"day": '01', # [DD]
"Ein": 'D' # [Model]
}
hostname = "https://api.geomagnetism.ga.gov.au/agrf"
hostname1 = "http://www.ngdc.noaa.gov/geomag-web/calculators/calculateDeclination?%s"
df_1=pd.DataFrame()
for year in range(startYear, endYear):
if (startYear>=1985 and endYear>1985):
-----
elif (startYear<1985 and endYear<1985):
-------

if endYear < 1985:
if startYear < 1985:
# Case 3
elif startYear >= 1985:
# Case 2
elif startYear < 1985:
# Case 1
else:
# Case where endYear < 1985 and startYear > 1985 (probably an input error)

if end > 1985:
australia
if start < 1985:
usa
else:
usa

How does Python convert date value from excel

I am reading a csv file with a CDATE column. The structure of the column is:
|CDATE |
|08/28/2018|
|08/28/2018|
|08/29/2018|
|08/30/2018|
|09/02/2018|
|09/04/2018|
...
|04/10/2019|
As you can see there is duplicate date as well as missing dates in this column, and I would like to find the missing dates and add them to my dataframe.
My code is:
import matplotlib.pyplot as plt
warnings.filterwarnings("ignore")
plt.style.use('fivethirtyeight')
import pandas as pd
df = pd.read_csv("XXX.csv")
dateCol = df['CDATE'].values.tolist()
dates = pd.to_datetime(dateCol, format='%m/%d/%Y')
startDate = dates.min()
endDate = dates.max()
df = df.sort_values('CDATE')
df_plastic = df['PLASTIC'].unique()
dateRange = pd.date_range(startDate, endDate)
df_date = df['CDATE'].unique()
for cursorDate in dateRange:
if (cursorDate in df_date) is False:
print('Data is missing date {} from range {}'.format(cursorDate, df_date))
But the output is:
Data is missing date 2019-02-21 00:00:00 from ['01/01/2019' '01/02/2019' '01/03/2019' '01/04/2019' '01/05/2019'
'01/07/2019' '01/08/2019' '01/09/2019' '01/10/2019' '01/11/2019'
'01/12/2019' '01/14/2019' '01/15/2019' '01/16/2019' '01/17/2019'
'01/18/2019' '01/19/2019' '01/21/2019' '01/22/2019' '01/23/2019'
'01/24/2019' '01/25/2019' '01/26/2019' '01/28/2019' '01/29/2019'
'01/30/2019' '01/31/2019' '02/01/2019' '02/02/2019' '02/04/2019'
'02/05/2019' '02/06/2019' '02/07/2019' '02/08/2019' '02/09/2019'
'02/11/2019' '02/12/2019' '02/13/2019' '02/14/2019' '02/15/2019'
'02/16/2019' '02/19/2019' '02/20/2019' '02/21/2019' '02/22/2019'
'02/23/2019' '02/25/2019' '02/26/2019' '02/27/2019' '02/28/2019'
'03/01/2019' '03/02/2019' '03/03/2019' '03/04/2019' '03/05/2019'
'03/06/2019' '03/07/2019' '03/08/2019' '03/09/2019' '03/11/2019'
'03/12/2019' '03/13/2019' '03/14/2019' '03/15/2019' '03/16/2019'
'03/18/2019' '03/19/2019' '03/20/2019' '03/21/2019' '03/22/2019'
'03/23/2019' '03/25/2019' '03/26/2019' '03/27/2019' '03/28/2019'
'03/29/2019' '03/30/2019' '04/01/2019' '04/02/2019' '04/03/2019'
'04/04/2019' '04/05/2019' '04/06/2019' '04/08/2019' '04/09/2019'
'04/10/2019' '05/29/2018' '05/30/2018' '05/31/2018' '06/01/2018'
'06/02/2018' '06/04/2018' '06/05/2018' '06/06/2018' '06/07/2018'
'06/08/2018' '06/09/2018' '06/11/2018' '06/12/2018' '06/13/2018'
'06/14/2018' '06/15/2018' '06/16/2018' '06/18/2018' '06/19/2018'
'06/20/2018' '06/21/2018' '06/22/2018' '06/23/2018' '06/25/2018'
'06/26/2018' '06/27/2018' '06/28/2018' '06/29/2018' '06/30/2018'
'07/03/2018' '07/04/2018' '07/05/2018' '07/06/2018' '07/07/2018'
'07/09/2018' '07/10/2018' '07/11/2018' '07/12/2018' '07/13/2018'
'07/14/2018' '07/16/2018' '07/17/2018' '07/18/2018' '07/19/2018'
'07/20/2018' '07/21/2018' '07/23/2018' '07/24/2018' '07/25/2018'
'07/26/2018' '07/27/2018' '07/28/2018' '07/30/2018' '07/31/2018'
'08/01/2018' '08/02/2018' '08/03/2018' '08/04/2018' '08/07/2018'
'08/08/2018' '08/09/2018' '08/10/2018' '08/11/2018' '08/13/2018'
'08/14/2018' '08/15/2018' '08/16/2018' '08/17/2018' '08/18/2018'
'08/20/2018' '08/21/2018' '08/22/2018' '08/23/2018' '08/24/2018'
'08/25/2018' '08/27/2018' '08/28/2018' '08/29/2018' '08/30/2018'
'08/31/2018' '09/01/2018' '09/04/2018' '09/05/2018' '09/06/2018'
'09/07/2018' '09/08/2018' '09/10/2018' '09/11/2018' '09/12/2018'
'09/13/2018' '09/14/2018' '09/15/2018' '09/17/2018' '09/18/2018'
'09/19/2018' '09/20/2018' '09/21/2018' '09/22/2018' '09/24/2018'
'09/25/2018' '09/26/2018' '09/27/2018' '09/28/2018' '09/29/2018'
'10/01/2018' '10/02/2018' '10/03/2018' '10/04/2018' '10/05/2018'
'10/06/2018' '10/09/2018' '10/10/2018' '10/11/2018' '10/12/2018'
'10/13/2018' '10/15/2018' '10/16/2018' '10/17/2018' '10/18/2018'
'10/19/2018' '10/20/2018' '10/22/2018' '10/23/2018' '10/24/2018'
'10/25/2018' '10/26/2018' '10/29/2018' '10/30/2018' '10/31/2018'
'11/01/2018' '11/02/2018' '11/03/2018' '11/05/2018' '11/06/2018'
'11/07/2018' '11/08/2018' '11/09/2018' '11/10/2018' '11/13/2018'
'11/14/2018' '11/15/2018' '11/16/2018' '11/18/2018' '11/19/2018'
'11/20/2018' '11/21/2018' '11/22/2018' '11/23/2018' '11/24/2018'
'11/26/2018' '11/27/2018' '11/28/2018' '11/29/2018' '11/30/2018'
'12/01/2018' '12/03/2018' '12/04/2018' '12/05/2018' '12/06/2018'
'12/07/2018' '12/08/2018' '12/09/2018' '12/10/2018' '12/11/2018'
'12/12/2018' '12/13/2018' '12/14/2018' '12/15/2018' '12/17/2018'
'12/18/2018' '12/19/2018' '12/20/2018' '12/21/2018' '12/22/2018'
'12/24/2018' '12/25/2018' '12/27/2018' '12/28/2018' '12/29/2018'
'12/31/2018']
Somehow the data type of cursorDate is changed to Timestamp, making the value comparison not work.
How is it converting the datetime formats?

Building on my comment above. Change the last line before your loop to this:
df_date = df['CDATE'].apply(pd.to_datetime).unique()

Python List of dates between x and z (dd//mm/year) [duplicate]

This question already has answers here:
How to print a date in a regular format?
(25 answers)
Closed 6 years ago.
from datetime import date, timedelta as td
d1 = date(1980, 1, 1)
d2 = date(2000, 1, 1)
delta = d2 - d1
for i in range(delta.days + 1):
print d1 + td(days=i)
How would I make it so it displays it in this form: dd/mm/yy
Thanks :)

Use strftime:
print your_date.strftime("%d/%m/%y")

Simply add this to your Print statement:
from datetime import date, timedelta as td
d1 = date(1980, 1, 1)
d2 = date(2000, 1, 1)
delta = d2 - d1
for i in range(delta.days + 1):
print ((d1 + td(days=i)).strftime("%d/%m/%Y"))
Output:
...
10/05/1996
11/05/1996
12/05/1996
13/05/1996
14/05/1996
15/05/1996
16/05/1996
17/05/1996
18/05/1996
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01/01/2000

How to calculate the total time a log file covers in Python 2.7?

So I have several log files, they are structured like this:
Sep 9 12:42:15 apollo sshd[25203]: pam_unix(sshd:auth): authentication failure; logname= uid=0 euid=0 tty=ssh ruser= rhost=189.26.255.11
Sep 9 12:42:15 apollo sshd[25203]: pam_succeed_if(sshd:auth): error retrieving information about user ftpuser
Sep 9 12:42:17 apollo sshd[25203]: Failed password for invalid user ftpuser from 189.26.255.11 port 44061 ssh2
Sep 9 12:42:17 apollo sshd[25204]: Received disconnect from 189.26.255.11: 11: Bye Bye
Sep 9 19:12:46 apollo sshd[30349]: Did not receive identification string from 199.19.112.130
Sep 10 03:29:48 apollo unix_chkpwd[4549]: password check failed for user (root)
Sep 10 03:29:48 apollo sshd[4546]: pam_unix(sshd:auth): authentication failure; logname= uid=0 euid=0 tty=ssh ruser= rhost=221.12.29.170 user=root
Sep 10 03:29:51 apollo sshd[4546]: Failed password for root from 221.12.29.170 port 56907 ssh2
There are more dates and times, But this is an example. I was wondering how I would calculate the total time that the file covers. I've tried a few things, and have had about 5 hours of no success.
I tried this first, and it was close, but it didn't work like I wanted it to, it kept repeating dates:
with open(filename, 'r') as file1:
lines = file1.readlines()
for line in lines:
linelist = line.split()
date2 = int(linelist[1])
time2 = linelist[2]
print linelist[0], linelist[1], linelist[2]
if date1 == 0:
date1 = date2
dates.append(linelist[0] + ' ' + str(linelist[1]))
if date1 < date2:
date1 = date2
ttimes.append(datetime.strptime(str(ltime1), FMT) - datetime.strptime(str(time1), FMT))
time1 = '23:59:59'
ltime1 = '00:00:00'
dates.append(linelist[0] + ' ' + str(linelist[1]))
if time2 < time1:
time1 = time2
if time2 > ltime1:
ltime1 = time2

If the entries are in a chronological order, you can just look at the first and at the last entry:
entries = lines.split("\n")
first_date = entries[0].split("apollo")[0]
last_date = entries[len(entries)-1].split("apollo")[0]

We don't have the year, so I took the current year. Read all the lines, convert the month to month index, and parse each date.
Then sort it (so works even if logs mixed) and take first & last item. Substract. Enjoy.
from datetime import datetime
months = ["","Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"]
current_year = datetime.now().year
dates = list()
with open(filename, 'r') as file1:
for line in file1:
linelist = line.split()
if linelist: # filter out possible empty lines
linelist[0] = str(months.index(linelist[0])) # convert 3-letter months to index
date2 = int(linelist[1])
z=datetime.strptime(" ".join(linelist[0:3])+" "+str(current_year),"%m %d %H:%M:%S %Y") # compose & parse the date
dates.append(z) # store in list
dates.sort() # sort the list
first_date = dates[0]
last_date = dates[-1]
# print report & compute time span
print("start {}, end {}, time span {}".format(first_date,last_date,last_date-first_date))
result:
start 2016-09-09 12:42:15, end 2016-09-10 03:29:51, time span 14:47:36
Note that it won't work properly between december 31st and january the 1st because of the missing year info. I suppose we could make a guess if we find January & December in the log then assume that it's january from the next year. Unsupported yet.