Python date/time conversion between text files
I have a hydrologic model text file output (export.txt) that looks like:
Units CFS
Type INST-VAL 1 01 Jan 1997, 02:00 1933.0 2 01 Jan 1997, 04:00 1918.0 3 01 Jan 1997, 06:00 1918.0 4 01 Jan 1997, 08:00 1904.0 5 01 Jan 1997, 10:00 1904.0 ...And have Python (2.6) coded the following to format for input to an optimization process:
import开发者_开发百科 re
o=open("C:\documents and settings\cmjawdy\desktop\PyOut.txt","w")
data=open("C:\documents and settings\cmjawdy\desktop\export.txt").read()
Step1=re.sub(":00",":00:00",data)
Step2=re.sub(" Jan ","/01/",Step1)
Step3=re.sub(",","",Step2)
FindIDs=re.compile("^[0-9]*\s",re.M)
Step4=re.sub(FindIDs,"SiteXXX ",Step3)
o.write(Step4)
o.close()
Yielding:
Units CFS
Type INST-VAL SiteXXX 01/01/1997 02:00:00 1933.0 SiteXXX 01/01/1997 04:00:00 1918.0 SiteXXX 01/01/1997 06:00:00 1918.0 SiteXXX 01/01/1997 08:00:00 1904.0 SiteXXX 01/01/1997 10:00:00 1904.0 ...The problem is that my optimization software can't take 24 as the hour, rather it must take 00 as the hour on the following day. So I need to convert 24:00:00 on day X to 00:00:00 on day X+1 while maintaining the same format. It looks as though strptime/strftime don't take 24 either. These are my absolute first lines of any computer language and I can't find an elegant way to convert this text.
import datetime
s = '''1 01 Jan 1997, 02:00 1933.0
2 01 Jan 1997, 04:00 1918.0
3 01 Jan 1997, 06:00 1918.0
4 01 Jan 1997, 08:00 1904.0
5 01 Jan 1997, 10:00 1904.0
6 01 Jan 1997, 24:00 1000.0'''
for row in s.split('\n'):
prefix = row[:2]
sdate = row[2:-7]
suffix = row[-7:]
if sdate[13:15] == '24':
offset = datetime.timedelta(1)
sdate = sdate[:13] + '00' + sdate[15:]
else:
offset = datetime.timedelta(0)
dt = datetime.datetime.strptime(sdate, '%d %b %Y, %H:%M') + offset
print prefix + dt.strftime('%d/%m/%Y %H:%M:%S') + suffix
result:
1 01/01/1997 02:00:00 1933.0
2 01/01/1997 04:00:00 1918.0
3 01/01/1997 06:00:00 1918.0
4 01/01/1997 08:00:00 1904.0
5 01/01/1997 10:00:00 1904.0
6 02/01/1997 00:00:00 1000.0
The following code solves the problem of the day next after some particular days to find when there is '24:00' in a line: January 31, February 28, February 29, June 30, December 31, etc
import re
ss1 = '''Units CFS
Type INST-VAL
1 01 Jan 1997, 02:00 1933.0
2 12 Feb 1997, 04:00 1918.0
3 26 May 1997, 06:00 1918.0
4 15 Aug 1997, 08:00 1904.0
5 09 Dec 1997, 10:00 1904.0'''
ss2 = '''Units CFS
Type INST-VAL
1 31 Jan 1997, 11:00 1933.0
2 28 Feb 1997, 11:00 1918.0
2 29 Feb 1997, 11:00 1918.0
3 31 Mar 1997, 11:00 1918.0
4 30 Sep 1997, 11:00 1904.0
5 31 Dec 1997, 11:00 1904.0'''
ss3 = '''Units CFS
Type INST-VAL
1 31 Jan 1997, 24:00 1933.0
2 28 Feb 2011, 24:00 1700.2
2 29 Feb 2011, 24:00 1700.0
2 28 Feb 2012, 24:00 1801.8
2 29 Feb 2012, 24:00 1801.0
3 31 Mar 1997, 24:00 1918.0
4 30 Sep 1997, 24:00 1904.0
5 31 Dec 1997, 24:00 1904.0'''
bis = ('1904', '1908', '1912', '1916', '1920', '1924', '1928', '1932', '1936', '1940',
'1944', '1948', '1952', '1956', '1960', '1964', '1968', '1972', '1976', '1980',
'1984', '1988', '1992', '1996', '2000', '2004', '2008', '2012', '2016', '2020',
'2024', '2028', '2032', '2036', '2040', '2044', '2048', '2052', '2056', '2060',
'2064', '2068', '2072', '2076', '2080', '2084', '2088', '2092', '2096', '2104')
months = dict(zip('Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec'.split(),xrange(1,13)))
firstday_nextmonth = {('31','Jan'):'01/02/', ('31','Mar'):'01/04/',
('30','Apr'):'01/05/', ('31','May'):'01/06/', ('30','Jun'):'01/07/',
('31','Jul'):'01/08/', ('31','Aug'):'01/09/', ('30','Sep'):'01/10/',
('31','Oct'):'01/11/', ('30','Nov'):'01/12/', ('31','Dec'):'01/01/'}
di = {'1':'MADRID ','2':'HUAHINE','3':'MOSCOW ','4':'OSAKA ','5':'VALPAR.'}
def repl(mat, fdnm = firstday_nextmonth, months = months, sites = di, bisextiles = bis):
d,m,y = mat.group(2,3,4)
if mat.group(5)=='24:00':
if (d,m)==('31','Dec'):
dmy = '01/01/%d' % (int(y)+1)
elif (d,m) == ('29','Feb'):
if y in bisextiles:
dmy = '01/03/' + y
else:
dmy = '!!!!!!!!!!'
elif (d,m)==('28','Feb'):
if y in bisextiles:
dmy = '29/02/' + y
else:
dmy = '01/03/' + y
elif (d,m) in fdnm:
dmy = fdnm[(d,m)] + y
else:
dmy = '%02d/%02d/%s' % (int(mat.group(2))+1,months[m],y)
elif (d,m) == ('29','Feb') and y not in bisextiles:
dmy = '!!!!!!!!!!'
else:
dmy = '%s/%02d/%s' % (d,months[m],y)
return '%s %s %s:00' % (sites[mat.group(1)],
dmy,
mat.group(5).replace('24:00','00:00'))
reg = re.compile('^(\d+) ([012]\d|30|31) ([a-z]+) (\d{4}), (\d\d:\d\d)(?= \d+.\d+)',
re.IGNORECASE|re.MULTILINE)
for ss in (ss1,ss2,ss3):
print ss
print
print reg.sub(repl,ss)
print '\n=========================================================\n'
result
Units CFS
Type INST-VAL
1 01 Jan 1997, 02:00 1933.0
2 12 Feb 1997, 04:00 1918.0
3 26 May 1997, 06:00 1918.0
4 15 Aug 1997, 08:00 1904.0
5 09 Dec 1997, 10:00 1904.0
Units CFS
Type INST-VAL
MADRID 01/01/1997 02:00:00 1933.0
HUAHINE 12/02/1997 04:00:00 1918.0
MOSCOW 26/05/1997 06:00:00 1918.0
OSAKA 15/08/1997 08:00:00 1904.0
VALPAR. 09/12/1997 10:00:00 1904.0
=========================================================
Units CFS
Type INST-VAL
1 31 Jan 1997, 11:00 1933.0
2 28 Feb 1997, 11:00 1918.0
2 29 Feb 1997, 11:00 1918.0
3 31 Mar 1997, 11:00 1918.0
4 30 Sep 1997, 11:00 1904.0
5 31 Dec 1997, 11:00 1904.0
Units CFS
Type INST-VAL
MADRID 31/01/1997 11:00:00 1933.0
HUAHINE 28/02/1997 11:00:00 1918.0
HUAHINE !!!!!!!!!! 11:00:00 1918.0
MOSCOW 31/03/1997 11:00:00 1918.0
OSAKA 30/09/1997 11:00:00 1904.0
VALPAR. 31/12/1997 11:00:00 1904.0
=========================================================
Units CFS
Type INST-VAL
1 31 Jan 1997, 24:00 1933.0
2 28 Feb 2011, 24:00 1700.2
2 29 Feb 2011, 24:00 1700.0
2 28 Feb 2012, 24:00 1801.8
2 29 Feb 2012, 24:00 1801.0
3 31 Mar 1997, 24:00 1918.0
4 30 Sep 1997, 24:00 1904.0
5 31 Dec 1997, 24:00 1904.0
Units CFS
Type INST-VAL
MADRID 01/02/1997 00:00:00 1933.0
HUAHINE 01/03/2011 00:00:00 1700.2
HUAHINE !!!!!!!!!! 00:00:00 1700.0
HUAHINE 29/02/2012 00:00:00 1801.8
HUAHINE 01/03/2012 00:00:00 1801.0
MOSCOW 01/04/1997 00:00:00 1918.0
OSAKA 01/10/1997 00:00:00 1904.0
VALPAR. 01/01/1998 00:00:00 1904.0
=========================================================
精彩评论