7个实用的Python自动化代码，建议收藏！

from selenium import webdriver import time import urllib.request driver = webdriver.Chrome() driver.maximize_window() driver.get( "https://www.zhihu.com/question/29134042" ) i = 0 while i < 10 : driver.execute_script( "window.scrollTo(0, document.body.scrollHeight);" ) time.sleep( 2 ) try : driver.find_element_by_css_selector( ’button.QuestionMainAction’ ).click() print( "page" + str(i)) time.sleep( 1 ) except : break result_raw = driver.page_source content_list = re.findall( "img src="http://www.cnmhg.com/e/admin126459646/showimg.php?url=(.+?)" " , str(result_raw)) n = 0 while n < len(content_list): i = time.time() local = ( r"%s.jpg" % (i)) urllib.request.urlretrieve(content_list[n], local) print( "编号：" + str(i)) n = n + 1

from time import sleep import requests s = input( "请主人输入话题：" ) while True: resp = requests.post( "http://www.tuling123.com/openapi/api" ,data={ "key" : "4fede3c4384846b9a7d0456a5e1e2943" , "info" : s , }) resp = resp.json() sleep ( 1 ) print ( ’小鱼：’ , resp[ ’text’ ]) s = resp[ ’text’ ] resp = requests.get( "http://api.qingyunke.com/api.php" , { ’key’ : ’free’ , ’appid’ : 0 , ’msg’ : s }) resp.encoding = ’utf8’ resp = resp.json() sleep ( 1 ) print ( ’菲菲：’ , resp[ ’content’ ]) #网上还有一个据说智商比较高的小i机器人，用爬虫的功能来实现一下： import urllib.request import re while True: x = input( "主人：" ) x = urllib.parse.quote( x ) link = urllib.request.urlopen( "http://nlp.xiaoi.com/robot/webrobot?&callback=__webrobot_processMsg&data=%7B%22sessionId%22%3A%22ff725c236e5245a3ac825b2dd88a7501%22%2C%22robotId%22%3A%22webbot%22%2C%22userId%22%3A%227cd29df3450745fbbdcf1a462e6c58e6%22%2C%22body%22%3A%7B%22content%22%3A%22" + x + "%22%7D%2C%22type%22%3A%22txt%22%7D" ) html_doc = link.read().decode() reply_list = re.findall(r ’"content":"(.+?)rn"’ , html_doc) print ( "小i：" + reply_list[- 1 ])

import jieba from nltk.classify import NaiveBayesClassifier # 需要提前把李白的诗收集一下，放在libai.txt文本中。 text1 = open( r"libai.txt" , "rb" ).read() list1 = jieba.cut(text1) result1 = " " .join(list1) # 需要提前把杜甫的诗收集一下，放在dufu.txt文本中。 text2 = open( r"dufu.txt" , "rb" ).read() list2 = jieba.cut(text2) result2 = " " .join(list2) # 数据准备 libai = result1 dufu = result2 # 特征提取 def word_feats (words) : return dict([(word, True ) for word in words]) libai_features = [(word_feats(lb), ’lb’ ) for lb in libai] dufu_features = [(word_feats(df), ’df’ ) for df in dufu] train_set = libai_features + dufu_features # 训练决策 classifier = NaiveBayesClassifier.train(train_set) # 分析测试 sentence = input( "请输入一句你喜欢的诗：" ) print( " " ) seg_list = jieba.cut(sentence) result1 = " " .join(seg_list) words = result1.split( " " ) # 统计结果 lb = 0 df = 0 for word in words: classResult = classifier.classify(word_feats(word)) if classResult == ’lb’ : lb = lb + 1 if classResult == ’df’ : df = df + 1 # 呈现比例 x = float(str(float(lb) / len(words))) y = float(str(float(df) / len(words))) print( ’李白的可能性：%.2f%%’ % (x * 100 )) print( ’杜甫的可能性：%.2f%%’ % (y * 100 ))

import random temp = [i + 1 for i in range( 35 )] random.shuffle(temp) i = 0 list = [] while i < 7 : list .append(temp[i]) i = i + 1 list .sort() print ( ’33[0;31;;1m’ ) print (* list [ 0 : 6 ], end= "" ) print ( ’33[0;34;;1m’ , end= " " ) print ( list [ -1 ])

import random import xlrd ExcelFile = xlrd.open_workbook( r’test.xlsx’ ) sheet = ExcelFile.sheet_by_name( ’Sheet1’ ) i = [] x = input( "请输入具体事件：" ) y = int(input( "老师要求的字数：" )) while len(str(i)) < y * 1.2 : s = random.randint( 1 , 60 ) rows = sheet.row_values(s) i.append(*rows) print( " " * 8 + "检讨书" + " " + "老师：" ) print( "我不应该" + str(x)+ "，" , *i) print( "再次请老师原谅！" ) ’’’ 以下是样稿： 请输入具体事件：抽烟 老师要求的字数：200 检讨书 老师： 我不应该抽烟， 学校一开学就三令五申， 一再强调校规校纪，提醒学生不要违反校规， 可我却没有把学校和老师的话放在心上， 没有重视老师说的话，没有重视学校颁布的重要事项， 当成了耳旁风，这些都是不应该的。 同时也真诚地希望老师能继续关心和支持我， 并却对我的问题酌情处理。 无论在学习还是在别的方面我都会用校规来严格要求自己， 我会把握这次机会。 但事实证明，仅仅是热情投入、刻苦努力、钻研学业是不够的， 还要有清醒的政治头脑、大局意识和纪律观念， 否则就会在学习上迷失方向，使国家和学校受损失。 再次请老师原谅！ ’’’

from time import sleep from PIL import ImageGrab m = int(input( "请输入想抓屏几分钟：" )) m = m * 60 n = 1 while n < m: sleep( 0.02 ) im = ImageGrab.grab() local = ( r"%s.jpg" % (n)) im.save(local, ’jpeg’ ) n = n + 1

from PIL import Image im = Image. open ( "1.jpg" ) images = [] images.append(Image. open ( ’2.jpg’ )) images.append(Image. open ( ’3.jpg’ )) im.save( ’gif.gif’ , save_all=True, append_images=images, loop= 1 ,)