编程Tips集锦,,以下是自己编程的一些


以下是自己编程的一些小贴士,记录,总结提高自己。

1.python中集合类型的查找,尽量用dict or set类型。

dict和set类型,在python内部的实现都是使用hash映射,查找的时间复杂度是O(1),比任何的查找算法都高效。

当在程序中使用到>1K次的查询,就应该开始考虑使用dict或set类型来进行数据的组织。

技术分享
 1 #coding:utf-8 2 from urllib.request import urlopen 3 from bs4 import BeautifulSoup 4 import re 5 import string 6 import operator 7 import datetime 8  9 commonWords = ["the", "be", "and", "of", "a", "in", "to", "have", "it", "i", "that", "for", "you", "he", "with", "on", "do", "say", "this", "they", "is", "an", "at", "but","we", "his", "from", "that", "not", "by", "she", "or", "as", "what", "go", "their","can", "who", "get", "if", "would", "her", "all", "my", "make", "about", "know", "will","as", "up", "one", "time", "has", "been", "there", "year", "so", "think", "when", "which", "them", "some", "me", "people", "take", "out", "into", "just", "see", "him", "your", "come", "could", "now", "than", "like", "other", "how", "then", "its", "our", "two", "more", "these", "want", "way", "look", "first", "also", "new", "because", "day", "more", "use", "no", "man", "find", "here", "thing", "give", "many", "well"]10 #若不注释,则为set类型,跑一遍程序,对比一下,则知优劣!11 #commonWords = set(commonWords)12 13 def isCommon(word):14     global commonWords15     if word in commonWords:16         return True17     return False18 19 20 def cleanText(input):21     input = re.sub(‘\n+‘, " ", input).lower()22     input = re.sub(‘\[[0-9]*\]‘, "", input)23     input = re.sub(‘ +‘, " ", input)24     input = re.sub("u\.s\.", "us", input)25     input = bytes(input, "UTF-8")26     input = input.decode("ascii", "ignore")27     return input28 29 def cleanInput(input):30     input = cleanText(input)31     cleanInput = []32     input = input.split(‘ ‘)33     for item in input:34         item = item.strip(string.punctuation)35         if len(item) > 1 or (item.lower() == ‘a‘ or item.lower() == ‘i‘):36             cleanInput.append(item)37 38     cleanContent = []39     for word in cleanInput:40         if not isCommon(word):41             cleanContent.append(word)42     return cleanContent43 44 def getNgrams(input, n):45     input = cleanInput(input)46     output = {}47     for i in range(len(input)-n+1):48         ngramTemp = " ".join(input[i:i+n])49         if ngramTemp not in output:50             output[ngramTemp] = 051         output[ngramTemp] += 152     return output53 54 def getFirstSentenceContaining(ngram, content):55     #print(ngram)56     sentences = content.split(".")57     for sentence in sentences:58         if ngram in sentence:59             return sentence60     return ""61 62 content = str(urlopen("http://pythonscraping.com/files/inaugurationSpeech.txt").read(), ‘utf-8‘)63 64 print(‘Use the set as the format of common words.‘)65 print(‘Begin:‘,datetime.datetime.now())66 for i in range(50):67     ngrams = getNgrams(content, 2)68     sortedNGrams = sorted(ngrams.items(), key = operator.itemgetter(1), reverse = True)69 print(‘End:‘,datetime.datetime.now())70 print(sortedNGrams)
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2.python往数据库插入数据

在插入数据之前,记得先进行一次查询,查看数据是否已经在数据库中。

一可以使程序更健壮,二也可顺便避免二次查询。

3.数据库在建表的时候,最后有索引

最近需要往数据库中插入上百万级的数据,十万级以后之后,数据库变得极慢,磁盘读写也是爆满!

后来,发现查询次数太多,重新建表,顺便加入索引。特别是unique index,我猜背后的实现机制是hash映射。

加入索引之后的数据库,大大减轻了磁盘的负担,查询速度几乎恒定,不过数据库的增大还是降低了读写的速度(实属情理之中)。

编程Tips集锦

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