There is a famous saying about Python: Don’t reinvent the wheel.
But there are three problems:
1. You don’t know which wheels have been built and which one is suitable for you. There are more than 400 famous wheels with names and surnames, not to mention the wheels that are being manufactured by themselves without names or surnames.
2. It is true that we are not reinventing the wheel, but we are reinventing the car. Including hundreds of lines of code written by many masters, in order to solve a mature function that Excel itself has.
3. Many people use it to capture pictures, data, pictures, videos, and weather forecasts for their own entertainment. What next? What is the use of big data after capturing it? For example, a certain beer sells quickly, but what next? For example, a certain movie has a lot of box office, and then what?
The following is the code that has been debugged with Python 3.6.4 and is shared with everyone:
1. Grab Zhihu pictures
2. Listen to two chatbots chatting with each other
3. AI analysis of whether the author of Tang poetry is Li Bai or Du Fu
4. Lottery randomly generates 7 out of 35
5. Automatically writes a letter of apology
6. Screen recorder
7. Make Gif animation
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="(.+?)" ", 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":"(.+?)\r\n"', 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("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))
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"+"n"+"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, duration=1, comment=b"aaabb")
You can try it out.
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