我是Python的新手，我希望用它来解析文本文件。该文件包含以下格式的250-300行：
---- Mark Grey (mark.grey@gmail.com) changed status from Busy to Available @ 14/07/2010 16:32:36 ----
---- Silvia Pablo (spablo@gmail.com) became Available @ 14/07/2010 16:32:39 ----
我需要将以下信息存储到此文件中所有条目的另一个文件（excel或文本）中
UserName/ID Previous Status New Status Date Time
所以我的结果文件对于上面提到的
应该是这样的Mark Grey/mark.grey@gmail.com Busy Available 14/07/2010 16:32:36
Silvia Pablo/spablo@gmail.com NaN Available 14/07/2010 16:32:39
提前致谢，
任何帮助都会非常感激
答案 0 :(得分：15)
为了帮助您入门：
result = []
regex = re.compile(
r"""^-*\s+
(?P<name>.*?)\s+
\((?P<email>.*?)\)\s+
(?:changed\s+status\s+from\s+(?P<previous>.*?)\s+to|became)\s+
(?P<new>.*?)\s+@\s+
(?P<date>\S+)\s+
(?P<time>\S+)\s+
-*$""", re.VERBOSE)
with open("inputfile") as f:
for line in f:
match = regex.match(line)
if match:
result.append([
match.group("name"),
match.group("email"),
match.group("previous")
# etc.
])
else:
# Match attempt failed
会为你提供一系列匹配的部分。然后，我建议您使用csv module以标准格式存储结果。
答案 1 :(得分：6)
import re
pat = re.compile(r"----\s+(.*?) \((.*?)\) (?:changed status from (\w+) to|became) (\w+) @ (.*?) ----\s*")
with open("data.txt") as f:
for line in f:
(name, email, prev, curr, date) = pat.match(line).groups()
print "{0}/{1} {2} {3} {4}".format(name, email, prev or "NaN", curr, date)
这假设了空白，并假设每一行都符合模式。如果要优雅地处理脏输入，可能需要添加错误检查（例如检查pat.match()不返回None）。
答案 2 :(得分：6)
感兴趣的两种RE模式似乎是......：
p1 = r'^---- ([^(]+) \(([^)]+)\) changed status from (\w+) to (\w+) (\S+) (\S+) ----$'
p2 = r'^---- ([^(]+) \(([^)]+)\) became (\w+) (\S+) (\S+) ----$'
所以我会这样做：
import csv, re, sys
# assign p1, p2 as above (or enhance them, etc etc)
r1 = re.compile(p1)
r2 = re.compile(p2)
data = []
with open('somefile.txt') as f:
for line in f:
m = p1.match(line)
if m:
data.append(m.groups())
continue
m = p2.match(line)
if not m:
print>>sys.stderr, "No match for line: %r" % line
continue
listofgroups = m.groups()
listofgroups.insert(2, 'NaN')
data.append(listofgroups)
with open('result.csv', 'w') as f:
w = csv.writer(f)
w.writerow('UserName/ID Previous Status New Status Date Time'.split())
w.writerows(data)
如果我描述的两种模式不够通用，当然可能需要调整它们，但我认为这种通用方法很有用。虽然Stack Overflow上的许多Python用户非常不喜欢RE，但我觉得它们对于这种实用的临时文本处理非常有用。
也许其他人希望将RE用于荒谬的用途，例如对CSV，HTML，XML的临时解析，以及许多其他类型的结构化文本格式哪个非常好的解析器存在！而且，其他任务远远超出了RE的“舒适区”，而是需要像pyparsing这样的可靠的通用解析器系统。或者用简单的字符串完成其他极端超级简单的任务（例如我记得最近使用if re.search('something', s):代替if 'something' in s:的SO问题！ - ）。
但是对于相当广泛的任务（不包括一端最简单的任务，以及另一方面的结构化或有些复杂的语法解析）RE是合适的，使用它们确实没有错，并且我建议所有程序员至少学习RE的基础知识。
答案 3 :(得分：4)
Alex提到了pyparsing，因此这是针对同一问题的一种pyparsing方法：
from pyparsing import Word, Suppress, Regex, oneOf, SkipTo
import datetime
DASHES = Word('-').suppress()
LPAR,RPAR,AT = map(Suppress,"()@")
date = Regex(r'\d{2}/\d{2}/\d{4}')
time = Regex(r'\d{2}:\d{2}:\d{2}')
status = oneOf("Busy Available Idle Offline Unavailable")
statechange1 = 'changed status from' + status('fromstate') + 'to' + status('tostate')
statechange2 = 'became' + status('tostate')
linefmt = (DASHES + SkipTo('(')('name') + LPAR + SkipTo(RPAR)('email') + RPAR +
(statechange1 | statechange2) +
AT + date('date') + time('time') + DASHES)
def convertFields(tokens):
if 'fromstate' not in tokens:
tokens['fromstate'] = 'NULL'
tokens['name'] = tokens.name.strip()
tokens['email'] = tokens.email.strip()
d,mon,yr = map(int, tokens.date.split('/'))
h,m,s = map(int, tokens.time.split(':'))
tokens['datetime'] = datetime.datetime(yr, mon, d, h, m, s)
linefmt.setParseAction(convertFields)
for line in text.splitlines():
fields = linefmt.parseString(line)
print "%(name)s/%(email)s %(fromstate)-10.10s %(tostate)-10.10s %(datetime)s" % fields
打印：
Mark Grey/mark.grey@gmail.com Busy Available 2010-07-14 16:32:36
Silvia Pablo/spablo@gmail.com NULL Available 2010-07-14 16:32:39
pyparsing允许您将名称附加到结果字段（就像Tom Pietzcker的RE样式答案中的命名组一样），以及用于处理或操纵已解析操作的分析时操作 - 请注意单独日期的转换和时间字段成为一个真正的日期时间对象，已经转换并准备好在解析之后进行处理，没有额外的麻烦。
这是一个修改过的循环，只是转出解析的标记和每行的命名字段：
for line in text.splitlines():
fields = linefmt.parseString(line)
print fields.dump()
打印：
['Mark Grey ', 'mark.grey@gmail.com', 'changed status from', 'Busy', 'to', 'Available', '14/07/2010', '16:32:36']
- date: 14/07/2010
- datetime: 2010-07-14 16:32:36
- email: mark.grey@gmail.com
- fromstate: Busy
- name: Mark Grey
- time: 16:32:36
- tostate: Available
['Silvia Pablo ', 'spablo@gmail.com', 'became', 'Available', '14/07/2010', '16:32:39']
- date: 14/07/2010
- datetime: 2010-07-14 16:32:39
- email: spablo@gmail.com
- fromstate: NULL
- name: Silvia Pablo
- time: 16:32:39
- tostate: Available
我怀疑在您继续解决此问题时，您会发现输入文本格式的其他变体，指定用户状态的更改方式。在这种情况下，您只需添加其他定义，例如statechange1或statechange2，然后将其与其他定义一起插入linefmt。我觉得pyparsing的解析器定义结构可以帮助开发人员在事情发生变化后回到解析器，并轻松扩展他们的解析程序。
答案 4 :(得分：1)
好吧，如果我要解决这个问题，我可能会先将每个条目拆分成自己独立的字符串。这看起来可能是面向行的，因此inputfile.split('\n')可能就足够了。从那里我可能会创建一个正则表达式来匹配每个可能的状态更改，子组包含每个重要的字段。
答案 5 :(得分：1)
非常感谢你的所有评论。它们非常有用。我使用目录功能编写了代码。它的作用是读取文件，并为每个用户创建一个输出文件，并提供所有状态更新。这是下面粘贴的代码。
#Script to extract info from individual data files and print out a data file combining info from these files
import os
import commands
dataFileDir="data/";
#Dictionary linking names to email ids
#For the time being, assume no 2 people have the same name
usrName2Id={};
#User id to user name mapping to check for duplicate names
usrId2Name={};
#Store info: key: user ids and values a dictionary with time stamp keys and status messages values
infoDict={};
#Given an array of space tokenized inputs, extract user name
def getUserName(info,mailInd):
userName="";
for i in range(mailInd-1,0,-1):
if info[i].endswith("-") or info[i].endswith("+"):
break;
userName=info[i]+" "+userName;
userName=userName.strip();
userName=userName.replace(" "," ");
userName=userName.replace(" ","_");
return userName;
#Given an array of space tokenized inputs, extract time stamp
def getTimeStamp(info,timeStartInd):
timeStamp="";
for i in range(timeStartInd+1,len(info)):
timeStamp=timeStamp+" "+info[i];
timeStamp=timeStamp.replace("-","");
timeStamp=timeStamp.strip();
return timeStamp;
#Given an array of space tokenized inputs, extract status message
def getStatusMsg(info,startInd,endInd):
msg="";
for i in range(startInd,endInd):
msg=msg+" "+info[i];
msg=msg.strip();
msg=msg.replace(" ","_");
return msg;
#Extract and store info from each line in the datafile
def extractLineInfo(line):
print line;
info=line.split(" ");
mailInd=-1;userId="-NONE-";
timeStartInd=-1;timeStamp="-NONE-";
becameInd="-1";
statusMsg="-NONE-";
#Find indices of email id and "@" char indicating start of timestamp
for i in range(0,len(info)):
#print (str(i)+" "+info[i]);
if(info[i].startswith("(") and info[i].endswith("@in.ibm.com)")):
mailInd=i;
if(info[i]=="@"):
timeStartInd=i;
if(info[i]=="became"):
becameInd=i;
#Debug print of mail and time stamp start inds
"""print "\n";
print "Index of mail id: "+str(mailInd);
print "Index of time start index: "+str(timeStartInd);
print "\n";"""
#Extract IBM user id and name for lines with ibm id
if(mailInd>=0):
userId=info[mailInd].replace("(","");
userId=userId.replace(")","");
userName=getUserName(info,mailInd);
#Lines with no ibm id are of the form "Suraj Godar Mr became idle @ 15/07/2010 16:30:18"
elif(becameInd>0):
userName=getUserName(info,becameInd);
#Time stamp info
if(timeStartInd>=0):
timeStamp=getTimeStamp(info,timeStartInd);
if(mailInd>=0):
statusMsg=getStatusMsg(info,mailInd+1,timeStartInd);
elif(becameInd>0):
statusMsg=getStatusMsg(info,becameInd,timeStartInd);
print userId;
print userName;
print timeStamp
print statusMsg+"\n";
if not(userName in usrName2Id) and not(userName=="-NONE-") and not(userId=="-NONE-"):
usrName2Id[userName]=userId;
#Store status messages keyed by user email ids
timeDict={};
#Retrieve user id corresponding to user name
if userName in usrName2Id:
userId=usrName2Id[userName];
#For valid user ids, store status message in the dict within dict data str arrangement
if not(userId=="-NONE-"):
if not(userId in infoDict.keys()):
infoDict[userId]={};
timeDict=infoDict[userId];
if not(timeStamp in timeDict.keys()):
timeDict[timeStamp]=statusMsg;
else:
timeDict[timeStamp]=timeDict[timeStamp]+" "+statusMsg;
#Print for each user a file containing status
def printStatusFiles(dataFileDir):
volNum=0;
for userName in usrName2Id:
volNum=volNum+1;
filename=dataFileDir+"/"+"status-"+str(volNum)+".txt";
file = open(filename,"w");
print "Printing output file name: "+filename;
print volNum,userName,usrName2Id[userName]+"\n";
file.write(userName+" "+usrName2Id[userName]+"\n");
timeDict=infoDict[usrName2Id[userName]];
for time in sorted(timeDict.keys()):
file.write(time+" "+timeDict[time]+"\n");
#Read and store data from individual data files
def readDataFiles(dataFileDir):
#Process each datafile
files=os.listdir(dataFileDir)
files.sort();
for i in range(0,len(files)):
#for i in range(0,1):
file=files[i];
#Do not process other non-data files lying around in that dir
if not file.endswith(".txt"):
continue
print "Processing data file: "+file
dataFile=dataFileDir+str(file);
inpFile=open(dataFile,"r");
lines=inpFile.readlines();
#Process lines
for line in lines:
#Clean lines
line=line.strip();
line=line.replace("/India/Contr/IBM","");
line=line.strip();
#Skip header line of the file and L's sign in sign out times
if(line.startswith("System log for account") or line.find("signed")>-1):
continue;
extractLineInfo(line);
print "\n";
readDataFiles(dataFileDir);
print "\n";
printStatusFiles("out/");