7个Python自动化脚本实例

以下是经过Python3.6.4调试通过的七个实用Python自动化脚本，与大家分享：

1. 抓取知乎图片，只用30行代码

<code>from selenium import webdriver import time import urllib.request import re 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=\"(.+?)\" ", 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</code>

2. 没事闲的时候，听两个聊天机器人互相聊天

<code>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'])</code>

3. 分析唐诗的作者是李白还是杜甫

<code>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("\n") 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))</code>

4. 彩票随机生成35选7

<code>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('\033[0;31;;1m') print(*list[0:6], end="") print('\033[0;34;;1m', end=" ") print(list[-1])</code>

5. 自动写检讨书

<code>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"+"\n"+"老师：") print("我不应该" + str(x)+"，", *i) print("再次请老师原谅！")</code>

6. 屏幕录相机，抓屏软件

<code>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</code>

7. 制作Gif动图

<code>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,)</code>

希望这些脚本对你有所帮助，欢迎尝试并探索更多Python自动化的可能性！