伙计们，我正在编写这个程序，它会遍历推文列表并返回最常用的单词。
我想让它更快，但我想知道您是否可以帮助指出一些我可以提高速度的问题或领域。谢谢
见下面的代码
#import string
import re
from string import punctuation
from operator import itemgetter
import pprint
class Tweet:
def __init__(self, timestamp, userId, message):
self.timestamp = timestamp
self.userId = userId
self.message = message
def getDate(self):
tokens = re.split(' ', self.timestamp)
return tokens[0]
def __repr__(self):
return "[timestamp=%s userId=%s message=%s]" % (self.timestamp, self.userId, self.message)
outfile = file
def readOneTweet(file):
""" Reads a single tweet from the file, and returns the string containing the tweet.
This will often just be a single line from the file, but may be more if it ends with a slash.
"""
lineBuffer = ""
while True:
# TODO: read the line and strip it
rawLine = file.readline().strip('\n')
if (len(rawLine)== 0):
break
lineBuffer +=rawLine
if (rawLine[(len(rawLine)-1)]!= "\\"):
break
return lineBuffer
def readTweets():
tweets = []
inputfile = raw_input("Enter filename: ")
# move the try / except around a single tweet.
# so that we can keep going if we encounter a line with an error.
try:
f = open(inputfile , "r")
while True:
tweet = readOneTweet(f) # readOneTweet is method
if not tweet:
break
try:
lineStrip = tweet.rstrip()
split_word = re.split('\t', lineStrip.lower()) #('/([^a-z])([A-Z]) ([0-9])/n:.;\]+/', line.lower())
tweetTime = split_word[1]
userId = split_word[0]
message = split_word[2]
tweets.append(Tweet(tweetTime, userId, message))
if len(tweets) % 10000 == 0:
print 'read', len(tweets), 'tweets'
except IndexError, e:
print "bad tweet", tweet
except IOError:
print "file not found!"
return tweets
######################DATA ##############
"""
- Need to separate tweets
- Obtain information about each tweet - UserID, Time, words
"""
def writeWordFile(word):
toWrite = 'test.txt'
fileHandle = open ( toWrite, 'w' )
for i in word:
fileHandle.write (i)
def dailyMessages(twt):
dailyMsg =dict ()
for i in twt:
date =i.getDate()
#print i.message
#dailyMsg[date] =messageList
if dailyMsg.has_key(date):
dailyMsg[date].append(twt)
else:
dailyMsg[date] =[twt]
#for k, v in dailyMsg.items():
#print k, v, '\n'
return dailyMsg
"""
Takes dailyTweets and perform word coun.
"""
def dailyWord(tweetsByDay):
dailyTweetsWordCount = { }
for date in tweetsByDay.keys():
dayTweets =tweetsByDay[date]
if len(dayTweets) != 0:
count = wordCount(dayTweets)
dailyTweetsWordCount[date] = count
return dailyTweetsWordCount
def wordCount(tweets):
"""Takes a list of tweets and returns a dictionary of counts for words"""
N = 100
# we'll build a dictionary mapping each word to a SET of users who have used it
wordTweeters = {}
for tweet in tweets:
# print tweet
for i in tweet:
for word in i.message.split():
if not wordTweeters.has_key(word):
wordTweeters[word] = set()
wordTweeters[word].add(i.userId)
# we'll build up a dictionary mapping each word to the number of users who have used it.
p = dict ()
#print wordTweeters
for day in wordTweeters.keys():
usersNo = len (wordTweeters[day])
p[day] = usersNo
#print wordTweeters
return p #wordTweeters, p
def searchForMemes(tweetUserCounts):
for key in tweetsUserCounts.keys():
# for pmeme in tweetUserCounts
pass
"""Takes information returned by daily word"""
def isMeme(word, day1Count, day2Count, day3Count):
#takes the daily count
# check if it is a meme
#First - check count
#check count in different days
# determine the if it qualifies as a tweet
# if not drop it do not do below checks
#Second - time stamp
#CHECK ITS TIME TRACK
#How is the count of over time
# rise and fall
#
#Third - user id
# check if is form different users
#how many of those counts are from different users
pass
def dayUserCount(z,word, d1, d2, d3):
""" assume dictionary will be input"""
# check if the word exist in the dictionary
if z.has_key(d1):
date1 =z[d1]
#print value.keys()
if date1.has_key(word):
print date1
c1 =date1[word]
else:
print "word not used in %s"%d1
c1 =0
else:
print 'date does not exist'
if z.has_key(d2):
#print value.keys()
date2 =z[d2]
if date2.has_key(word):
print date2
c2 =date2[word]
else:
print "word not used in %s"%d2
c2 =0
else:
print 'date does not exist'
if z.has_key(d3):
date3 = z[d3]
if date3.has_key(word):
print date3
c3 =date3[word]
else:
print "word not used in %s" %d3
c3 =0
else:
print 'date does not exist'
result = "Word: %s , %s count: %s, %s count: %s, %s count: %s"%(word,d1,c1,d2,c2, d3,c3)
return result
# supportive functions
def hashtag(tw):
hasht =[]
for word in tw.split():
if word.startswith('#'):
hasht.append(word)
return hasht
def httpTag(tw):
http =[]
for word in tw.split():
if word.startswith('http'):
http.append(word)
return http
def reply(tw):
reply =[]
for word in tw.split():
if word.startswith('@'):
reply.append(word)
return reply
def reTweet(tw):
rt =[]
for word in tw.split():
if word.startswith('rt') or word.startswith('RT'):
rt.append(word)
return rt
"""
Old functions
"""
def writeToFile(tweet):
#filename = test.txt
filek = open('test.txt', 'w')
print "writing on the file: "
filek.write(tweet)
# print " _____--------______" + tweet
filek.close()
# count word frequency.
def f2count():
N = 100000000000
words = {}
words_gen = (word.strip(punctuation).lower()
for line in open('c.txt')
for word in line.split())
for word in words_gen:
words[word] = words.get(word, 0) + 1
top_words = sorted(words.iteritems(),
key=lambda(word, count): (-count, word))[:N]
for word, frequency in top_words:
print "%s: %d" % (word, frequency)