我有这个原始文本:

________________________________________________________________________________________________________________________________
Pos Car  Competitor/Team                Driver                   Vehicle              Cap   CL Laps     Race.Time Fastest...Lap

1     6  Jason Clements                 Jason Clements           BMW M3               3200       10     9:48.5710   3 0:57.3228*
2    42  David Skillender               David Skillender         Holden VS Commodore  6000       10     9:55.6866   2 0:57.9409 
3    37  Bruce Cook                     Bruce Cook               Ford  Escort         3759       10     9:56.4388   4 0:58.3359 
4    18  Troy Marinelli                 Troy Marinelli           Nissan  Silvia       3396       10     9:56.7758   2 0:58.4443 
5    75  Anthony Gilbertson             Anthony Gilbertson       BMW M3               3200       10    10:02.5842   3 0:58.9336 
6    26  Trent Purcell                  Trent Purcell            Mazda RX7            2354       10    10:07.6285   4 0:59.0546 
7    12  Scott Hunter                   Scott Hunter             Toyota  Corolla      2000       10    10:11.3722   5 0:59.8921 
8    91  Graeme Wilkinson               Graeme Wilkinson         Ford  Escort         2000       10    10:13.4114   5 1:00.2175 
9     7  Justin Wade                    Justin Wade              BMW M3               4000       10    10:18.2020   9 1:00.8969 
10   55  Greg Craig                     Grag Craig               Toyota  Corolla      1840       10    10:18.9956   7 1:00.7905 
11   46  Kyle Orgam-Moore               Kyle Organ-Moore         Holden VS Commodore  6000       10    10:30.0179   3 1:01.6741 
12   39  Uptiles Strathpine             Trent Spencer            BMW Mini Cooper S    1500       10    10:40.1436   2 1:02.2728 
13  177  Mark Hyde                      Mark Hyde                Ford  Escort         1993       10    10:49.5920   2 1:03.8069 
14   34  Peter Draheim                  Peter Draheim            Mazda RX3            2600       10    10:50.8159  10 1:03.4396 
15    5  Scott Douglas                  Scott Douglas            Datsun  1200         1998        9     9:48.7808   3 1:01.5371 
16   72  Paul Redman                    Paul Redman              Ford  Focus          2lt         9    10:11.3707   2 1:05.8729 
17    8  Matthew Speakman               Matthew Speakman         Toyota  Celica       1600        9    10:16.3159   3 1:05.9117 
18   74  Lucas Easton                   Lucas Easton             Toyota  Celica       1600        9    10:16.8050   6 1:06.0748 
19   77  Dean Fuller                    Dean Fuller              Mitsubishi  Sigma    2600        9    10:25.2877   3 1:07.3991 
20   16  Brett Batterby                 Brett Batterby           Toyota  Corolla      1600        9    10:29.9127   4 1:07.8420 
21   95  Ross Hurford                   Ross Hurford             Toyota  Corolla      1600        8     9:57.5297   2 1:12.2672 
DNF  13  Charles Wright                 Charles Wright           BMW 325i             2700        9     9:47.9888   7 1:03.2808 
DNF  20  Shane Satchwell                Shane Satchwell          Datsun  1200 Coupe   1998        1     1:05.9100   1 1:05.9100 

Fastest Lap Av.Speed Is 152kph, Race Av.Speed Is 148kph
R=under lap record by greatest margin, r=under lap record, *=fastest lap time
________________________________________________________________________________________________________________________________
Issue# 2 - Printed Sat May 26 15:43:31 2012                     Timing System By NATSOFT (03)63431311 www.natsoft.com.au/results
Amended 

我需要将它解析为一个对象，其中包含明显的 Position、Car、Driver 等字段。问题是我不知道使用哪种策略。如果我在空白处拆分它，我最终会得到这样一个列表:

["1", "6", "Jason", "Clements", "Jason", "Clements", "BMW", "M3", "3200", "10", "9:48.5710", "3", "0:57.3228*"]

你能看到这个问题吗？我不能只解释这个列表，因为人们可能只有 1 个名字，或者名字中有 3 个词，或者汽车中有许多不同的词。这使得仅使用索引来引用列表变得不可能。

使用列名定义的偏移量怎么样？不过，我不太明白如何使用它。

编辑:所以我目前使用的算法是这样工作的:

1. 在新行上拆分文本，给出一组行。
2. 找出每行最右边的常见空白字符。 IE。每行的位置(索引) 行包含空格。例如:
3. 根据这些常用字符拆分行。
4. 修剪线条

存在几个问题:

如果名称包含相同的长度，如下所示:

Jason Adams
Bobby Sacka
Jerry Louis

然后它会将其解释为两个单独的项目:(["Jason""Adams", "Bobby", "Sacka", "Jerry", "Louis"]).

而如果它们都像这样不同:

Dominic Bou
Bob Adams
Jerry Seinfeld

然后它会在 Seinfeld 的最后一个 'd' 处正确拆分(因此我们会得到三个名字的集合(["Dominic Bou", "Bob Adams", "Jerry Seinfeld"]).

它也很脆弱。我正在寻找更好的解决方案。

最佳答案

这不是正则表达式的好例子，你真的想发现格式然后解压行:

lines = str.split "\n"

# you know the field names so you can use them to find the column positions
fields = ['Pos', 'Car', 'Competitor/Team', 'Driver', 'Vehicle', 'Cap', 'CL Laps', 'Race.Time', 'Fastest...Lap']
header = lines.shift until header =~ /^Pos/
positions = fields.map{|f| header.index f}

# use that to construct an unpack format string
format = 1.upto(positions.length-1).map{|x| "A#{positions[x] - positions[x-1]}"}.join
# A4A5A31A25A21A6A12A10

lines.each do |line|
  next unless line =~ /^(\d|DNF)/ # skip lines you're not interested in
  data = line.unpack(format).map{|x| x.strip}
  puts data.join(', ')
  # or better yet...
  car = Hash[fields.zip data]
  puts car['Driver']
end

关于ruby - 解释这个原始文本 - 一种策略？，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/10791337/