文本文件之间的Python日期/时间转换

时间:2011-10-03 16:54:18

标签: python date text time format

我有一个水文模型文本文件输出(export.txt),如下所示:

单位CFS
输入INST-VAL
1997年1月1日,02:00 1933.0
1997年1月2日,04:00 1918.0
1997年1月3日,06:00 1918.0
1997年1月4日,08:00 1904.0
1997年1月5日,10:00 1904.0
...


让Python(2.6)编写以下代码来格式化输入到优化过程:

import 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()

产量:

单位CFS
输入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
...


问题是我的优化软件不能以24小时为单位,而是必须在第二天以小时为00。因此,我需要在第X天将24:00:00转换为第X + 1天的00:00:00,同时保持相同的格式。看起来strptime / strftime也不需要24。这些是我对任何计算机语言的绝对第一行,我找不到一种优雅的方式来转换这段文字。

2 个答案:

答案 0 :(得分:3)

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

结果:

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

答案 1 :(得分:0)

以下代码解决了某些特定日子之后的下一天的问题,以便找到一行中的'24:00':1月31日,2月28日,2月29日,6月30日,12月31日等

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'

结果

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

=========================================================