你都用 Python 来做什么？

import re
from selenium import webdriver
import time
import urllib.request

driver = webdriver.Chrome()
driver.maximize_window()
driver.get("https://www.某某乎.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'])

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('\033[0;31;;1m')
print(*list[0:6], end="")
print('\033[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！")

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")

# -*- coding: utf-8 -*-#
from aip import AipSpeech
import speech_recognition as sr
import os

# 生成音频文件
def my_record(rate=16000):
    r = sr.Recognizer()
    with sr.Microphone(sample_rate=rate) as source:
        print("请说话")
        audio = r.listen(source)
    with open("audio.wav", "wb") as f:
        f.write(audio.get_wav_data())

# 2、音频文件转文字

APP_ID = '这三个参数要，自己去百度申请'
API_KEY = '这三个参数要，自己去百度申请'
SECRET_KEY = '这三个参数要，自己去百度申请'
client = AipSpeech(APP_ID, API_KEY, SECRET_KEY)
path = 'audio.wav'

def listen():
    # 读取录音文件
    with open(path, 'rb') as fp:
        voices = fp.read()
    try:
        # 常用dev_pid参数：1537普通话(纯中文识别)、1737英语、1637粤语、1837四川话
        result = client.asr(voices, 'wav', 16000, {'dev_pid': 1537, })
        result_text = result["result"][0]
        print("我说: " + result_text)
        if result_text=="结束程序。":
            print("再见！")
            os._exit(0)

    # return result_text
    except KeyError:
        print("未知问题")

while True:
    my_record()
    request = listen()

# coding=UTF8
import pythoncom

class PythonDemo:
    _public_methods_ = ['Test']
    _reg_progid_ = 'Demos'
    _reg_clsid_ = pythoncom.CreateGuid()

    def Test(self, val, val2):
        val = val + val2
        return val

if __name__ == '__main__':
    import win32com.server.register
    print('启动COM服务.')
    win32com.server.register.UseCommandLine(PythonDemo)

Private Sub Command1_Click()

    Set PythonUtils = CreateObject("Demos")
    response = PythonUtils.Test(a, b)

    a = Val(Text1.Text)
    b = Val(Text2.Text)
    Print response
    
End Sub

pip install python-miio
pip install yeelight

from miio.chuangmi_plug import ChuangmiPlug #小米智能家居的模块
from yeelight import Bulb #YeeLight的模块
import tkinter #为了写一个丑点的窗口

ip='192.168.31.41'
token='24dfac257f5940d4b30046c16e81ea52' # 输入之前获得的token

d = ChuangmiPlug(ip=ip, token=token) #智能插座
d2 = Bulb("192.168.31.131") #YeeLight灯

def kai():
    d.on()
    d2.turn_on()
def guan():
    d.off()
    d2.turn_off()
def usb_on():
    d.usb_on()
def usb_off():
    d.usb_off()

# 创建一个比较丑的界面，总比没有强
win = tkinter.Tk()
win.title("米家Python By:JeffersLi")
win.geometry("600x400+200+50")
button1 = tkinter.Button(win, text="打开", command=kai, width=10, height=1)
button1.pack()
button2 = tkinter.Button(win, text="关闭", command=guan, width=10, height=1)
button2.pack()
button3 = tkinter.Button(win, text="打开USB", command=usb_on, width=10, height=1)
button3.pack()
button4 = tkinter.Button(win, text="关闭USB", command=usb_off, width=10, height=1)
button4.pack()
win.mainloop()

import face_recognition #版本1.3.0
import numpy as np #版本1.21.5
import cv2 #版本4.5.5.62
from keras.models import load_model #版本2.7.0
#另外还需要dlib（版本19.22.1），cmake（版本号3.22.1）
cap = cv2.VideoCapture(0) #内置摄像头为0，外置摄像头为1
i = 0

def draw_guide_line(image_np):
    # 画辅助线
    [h1, h2, h3] = image_np.shape
    point_color = (100, 100, 255)  # BGR
    thickness = 1
    lineType = 8
    image_np = np.ascontiguousarray(image_np, dtype=np.uint8)  # 原来的图像在内存上的保存是不连续的
    cv2.line(image_np, [200, 0],[200, 480], point_color, thickness, lineType) #竖线
    cv2.line(image_np, [440, 0],[440, 480], point_color, thickness, lineType) #竖线
    cv2.line(image_np, [0, 100],[640, 100], point_color, thickness, lineType) #竖线
    cv2.line(image_np, [0, 380],[640, 380], point_color, thickness, lineType) #竖线
    return image_np

while (1):
    ret, frame = cap.read()
    key = cv2.waitKey(1)
    if key == 27: #按ESC键退出
        break
    elif key == ord('c') or key == ord('C'):  #按下C键拍照
        cv2.imwrite(str(i) + '.jpg', frame)
        file_path = str(i) + '.jpg'
        i += 1
        emotion_dict = {'生气': 0, '悲伤': 5, '中性': 4, '厌恶': 1, '惊讶': 6, '恐惧': 2, '高兴': 3}
        image = face_recognition.load_image_file(file_path)  # .载入图像
        face_locations = face_recognition.face_locations(image)  # 寻找脸部
        top, right, bottom, left = face_locations[0]  # 将脸部框起来
        face_image = image[top:bottom, left:right]
        face_image = cv2.resize(face_image, (48, 48))
        face_image = cv2.cvtColor(face_image, cv2.COLOR_BGR2GRAY)
        face_image = np.reshape(face_image, [1, face_image.shape[0], face_image.shape[1], 1])  # 调整到可以进入该模型输入的大小
        model = load_model("./model_v6_23.hdf5")  # 要下载三年前的这个老模型https://github.com/priya-dwivedi/face_and_emotion_detection/raw/master/emotion_detector_models/model_v6_23.hdf5
        predicted_class = np.argmax(model.predict(face_image))  # 分类情绪
        label_map = dict((v, k) for k, v in emotion_dict.items())
        predicted_label = label_map[predicted_class]  # 根据情绪映射表输出情绪
        print(predicted_label)
    frame = draw_guide_line(frame)
    cv2.imshow("capture", frame)
cap.release()
cv2.destroyAllWindows()

from pptx import Presentation
import win32com.client
import pyautogui as pg
import time
import tkinter
import tkinter as tk
from tkinter import filedialog
import sys

speaker = win32com.client.Dispatch("SAPI.SpVoice")

def start():
    file_path = filedialog.askopenfilename()
    ppt = win32com.client.Dispatch('PowerPoint.Application')
    ppt.Visible = 1
    ppt.Presentations.Open(file_path)
    win32com.client.gencache.EnsureDispatch('PowerPoint.Application')
    obj=Presentation(file_path)
    for index, slide in enumerate(obj.slides,start=1):
        print(f'第{index}页幻灯片'.center(20,'='))
        pg.press('enter')
        time.sleep(1)
        #PowePoint自带模板中每页幻灯片顶部的文本为title#如果自定义模板中没有title，返回空值None
        title=slide.shapes.title
        subtitle = slide.placeholders[0]

        if title:
            speaker.Speak(title.text)
        else:
            print('这一页幻灯片没有标题')

        if slide.placeholders[0]:
            speaker.Speak(subtitle.text)
        else:
            print('这一页幻灯片没有内容')

        if slide.has_notes_slide:
            speaker.Speak(slide.notes_slide.notes_text_frame.text)
        else:
            print('这一页幻灯片没有备注')

        if index==len(obj.slides):
            speaker.Speak('讲解完毕，谢谢大家！')
            sys.exit()
        else:
            time.sleep(1)

def stop():
    sys.exit()

# 创建主窗口
win = tkinter.Tk()
# 设置标题
win.title("自动朗读PPT By:JeffersLi")
# 设置大小和位置
win.geometry("600x400+200+50")
# 进入消息循环，可以写控件
# 创建按钮
button1 = tkinter.Button(win, text="打开PPT", command=start, width=10, height=1)
button2 = tkinter.Button(win, text="退出", command=stop, width=10, height=1)
button1.pack()
button2.pack()

win.mainloop()

import sys
from PyQt5.QtCore import QUrl
from PyQt5.QtWidgets import QApplication
from PyQt5.QtWebEngineWidgets import QWebEnginePage, QWebEngineView
from PyQt5.QtGui import QIcon
from PyQt5.QtCore import Qt #调用窗口状态

app = QApplication(sys.argv)

browser = QWebEngineView()
browser.setWindowIcon(QIcon("map.ico"))
browser.setWindowTitle("百度地图")
browser.load(QUrl("http://map.baidu.com/"))
browser.setWindowState(Qt.WindowMaximized) #窗口最大化
browser.show()

app.exec_()