1. 读取原始数据html = urlopen(url).read()2. 数据清洗raw = nltk.clean_html(html)3. 数据切片raw = raw[111:2222222]4. 数据分词tokens = nltk.wordpunct_tokenize(raw)5. 分词切片tokens = tokens[2

1.概要金融领域交通领域医疗领域零售领域工业领域农业领域司法领域物流领域2.详情待续

1. 读取原始数据html = urlopen(url).read()2. 数据清洗raw = nltk.clean_html(html)3. 数据切片raw = raw[111:2222222]4. 数据分词tokens = nltk.wordpunct_tokenize(raw)5. 分词切片tokens = tokens[2

#! /usr/bin/env pythonfrom operator import add, subfrom random import randint, choiceops = {'+': add, '-': sub}MAXTRIES = 2def doprob():op = choice('+-')nums = [randint(1,10) for i i

#! /usr/bin/env pythonqueue = []def enQ():queue.append(raw_input('Enter new string: ').strip())def deQ():if len(queue) == 0:print 'Cannot pop from an empty queue!'else:

#! /usr/bin/env pythonimport os, socket, errno, types, tempfileclass NetworkError(IOError):passclass FileError(IOError):passdef updArgs(args, newarg=None):if isinstance(args, IO

文本朗读（Text to speech）/语音合成（Speech synthesis）语音识别（Speech recognition）中文自动分词（Chinese word segmentation）词性标注（Part-of-speech tagging）句法分析（Parsing）自然语言生成（Natural language generation）文本分类（Text categori

#!/usr/bin/env pythondef identifierChecker():import stringalphas = string.ascii_letters + '_'nums = string.digitsprint 'Welcome to the Identifier Checker v1.0'print 'Test

#! /usr/bin/env pythonfrom operator import add, subfrom random import randint, choiceops = {'+': add, '-': sub}MAXTRIES = 2def doprob():op = choice('+-')nums = [randint(1,10) for i i

#! /usr/bin/env pythondb = {}def newuser():prompt = 'login desired: 'while True:name = raw_input(prompt)if db.has_key(name):prompt = 'name taken, try anoth