Question

我有一个日志文件，其中包含一个日期/时间，在下一个日期/时间之间有不同的行数

例如。

时间日期
18/07/2 13：55：00.983

msecVal = pyparsing.Word(pyparsing.nums, max=3)
numPair = pyparsing.Word(pyparsing.nums, exact=2)
dateStr = pyparsing.Combine(numPair + '/' + numPair + '/' + numPair)

timeString = pyparsing.Combine(numPair + ':' + numPair + ':' +     numPair\               
       + '.' + msecVal)

日志文件将是

time:date:  line of text
    possible 2nd line of text
    possible 3rd line of text...
    time:date:  line of text
time:date: line of text
    possible 2nd line of text
    possible 3rd line of text...
    possible <n> line of text...
time:date:  line of text

输入将是上述格式的大文本日志文件。我想生成一个分组元素的列表

[[time],[all text until next time]],[[time],[all text until next time]...

如果每个时间/日期条目都为一行，则可以执行此操作。它跨越多个行的随机数，直到下一个我遇到问题的时间/日期条目为止。

Answer 1

这是我解释您对日志实体的定义的方式：

“行首的日期时间，后跟冒号，然后是所有内容直到行首的下一个日期时间为止，即使可能存在日期时间嵌入行中。”

您需要解决以下两种pyparsing功能：

LineStart-区分行开头和行正文中的日期时间
SkipTo-跳过非结构化文本直到找到匹配表达式的快速方法

我在您的代码中添加了这些表达式（由于我是一个懒惰的打字员，我将pyparsing导入为“ pp”）：

dateTime = dateStr + timeString

# log entry date-time keys only match if they are at the start of the line
dateTimeKey = pp.LineStart() + dateTime

# define a log entry as a date-time key, followed by everything up to the next 
# date-time key, or to the end of the input string
# (use results names to make it easy to get at the parts of the log entry)
logEntry = pp.Group(dateTimeKey("time") + ':' + pp.Empty()
                    + pp.SkipTo(dateTimeKey | pp.StringEnd())("body"))

我将您的样品转换为具有不同的日期时间进行测试，我们得到了：

sample = """\
2/07/18 13:55:00.983:  line of text
    possible 2nd line of text
    possible 3rd line of text...
    2/07/19 13:55:00.983:  line of text
2/07/20 13:55:00.983: line of text
    possible 2nd line of text
    possible 3rd line of text...
    possible <n> line of text...
2/07/21 13:55:00.983:  line of text
"""

print(pp.OneOrMore(logEntry).parseString(sample).dump())

礼物：

[['2/07/18', '13:55:00.983', ':', 'line of text\n    possible 2nd line of text\n    possible 3rd line of text...\n    2/07/19 13:55:00.983:  line of text'], ['2/07/20', '13:55:00.983', ':', 'line of text\n    possible 2nd line of text\n    possible 3rd line of text...\n    possible <n> line of text...'], ['2/07/21', '13:55:00.983', ':', 'line of text']]
[0]:
  ['2/07/18', '13:55:00.983', ':', 'line of text\n    possible 2nd line of text\n    possible 3rd line of text...\n    2/07/19 13:55:00.983:  line of text']
  - body: 'line of text\n    possible 2nd line of text\n    possible 3rd line of text...\n    2/07/19 13:55:00.983:  line of text'
  - time: ['2/07/18', '13:55:00.983']
[1]:
  ['2/07/20', '13:55:00.983', ':', 'line of text\n    possible 2nd line of text\n    possible 3rd line of text...\n    possible <n> line of text...']
  - body: 'line of text\n    possible 2nd line of text\n    possible 3rd line of text...\n    possible <n> line of text...'
  - time: ['2/07/20', '13:55:00.983']
[2]:
  ['2/07/21', '13:55:00.983', ':', 'line of text']
  - body: 'line of text'
  - time: ['2/07/21', '13:55:00.983']

我还必须将您的num_pair转换为：

numPair = pp.Word(pp.nums, max=2)

否则，它与您的采样日期中的前两位数字“ 2”不匹配。

pyparsing：在日期之间分组文本

1 个答案: