# 使用Tesseract OCR识别扫描件  
import pytesseract  
from PIL import Image  text = pytesseract.image_to_string(Image.open('体检表.jpg'), lang='chi_sim')  
# 自动填充HIS系统  
driver.find_element(By.ID, "patient_name").send_keys(text.split('姓名：')[1].split('\n')[0])

# PDF文本提取与分析  
import pdfplumber  with pdfplumber.open("resume.pdf") as pdf:  text = ''.join(page.extract_text() for page in pdf.pages)  score = 0  if "Python" in text: score += 5  if "MySQL" in text: score += 3

# 表单提交前校验  
def validate_form():  if driver.find_element(By.ID, "tax_amount").text == "":  raise ValueError("税额未自动计算")  if len(driver.find_elements(By.CLASS_NAME, "error-msg")) > 0:  take_screenshot("提交前错误")  # 自动截图留证

from selenium import webdriver
from selenium.webdriver.common.by import By
import timedef export_orders():# 初始化浏览器（你可以在无头模式下运行）options = webdriver.ChromeOptions()options.add_argument("--start-maximized")driver = webdriver.Chrome(options=options)# 登录电商后台driver.get("https://manage.yourshop.com/login")driver.find_element(By.ID, "username").send_keys("your_account")driver.find_element(By.ID, "password").send_keys("your_password")driver.find_element(By.CSS_SELECTOR, ".login-btn").click()time.sleep(3)  # 等待页面加载# 导航至订单页面driver.find_element(By.XPATH, "//span[text()='订单管理']").click()time.sleep(1)# 设置筛选条件并导出driver.find_element(By.NAME, "order_date").send_keys("2023-07-21")driver.find_element(By.ID, "export_btn").click()print("订单数据已导出至downloads文件夹")# 关闭浏览器driver.quit()

import pandas as pd
from datetime import datetimedef process_data():# 读取下载的CSV文件df = pd.read_csv("downloads/orders_20230721.csv")# 数据清洗（你要删除无效订单）df = df[df['status'] != 'cancelled']  # 过滤取消订单df = df.dropna(subset=['product_id'])  # 删除无商品ID记录# 计算指标（你要生成管理层需要的KPI）df['gmv'] = df['price'] * df['quantity']daily_gmv = df['gmv'].sum()top_products = df.groupby('product_name')['quantity'].sum().nlargest(5)# 保存处理结果report_name = f"order_report_{datetime.today().strftime('%Y%m%d')}.xlsx"with pd.ExcelWriter(report_name) as writer:df.to_excel(writer, sheet_name='原始数据', index=False)top_products.to_excel(writer, sheet_name='热销商品')print(f"报表已生成：{report_name}")return report_name

import pyautogui
import timedef create_excel_charts(file_path):# 打开Excel文件（你要模拟键盘操作）pyautogui.hotkey('win', 'r')pyautogui.write('excel')pyautogui.press('enter')time.sleep(3)pyautogui.hotkey('ctrl', 'o')pyautogui.write(file_path)pyautogui.press('enter')time.sleep(5)  # 等待文件加载# 切换到热销商品工作表pyautogui.hotkey('ctrl', 'pgdn')time.sleep(1)# 生成柱状图（你要精确定位操作区域）pyautogui.click(x=300, y=200)  # 选中数据区域pyautogui.hotkey('alt', 'n', 'r')  # 插入柱状图pyautogui.click(x=1000, y=600)  # 调整图表位置# 保存并退出pyautogui.hotkey('ctrl', 's')pyautogui.hotkey('alt', 'f4')

import smtplib
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.mime.application import MIMEApplicationdef send_report(email_to, file_path):# 创建邮件对象（你要设置邮件基本信息）msg = MIMEMultipart()msg['From'] = 'rpa_system@yourcompany.com'msg['To'] = email_tomsg['Subject'] = f"每日订单报告 {datetime.today().strftime('%Y-%m-%d')}"# 添加正文内容body = "附件为自动生成的当日订单分析报告，请查收。\n\nRPA系统自动发送"msg.attach(MIMEText(body, 'plain'))# 添加Excel附件（你要处理文件编码）with open(file_path, 'rb') as f:attach = MIMEApplication(f.read(), _subtype="xlsx")attach.add_header('Content-Disposition', 'attachment', filename=file_path)msg.attach(attach)# 通过SMTP发送（你要配置企业邮箱服务器）server = smtplib.SMTP('smtp.office365.com', 587)server.starttls()server.login('your_email@domain.com', 'email_password')server.send_message(msg)server.quit()print(f"报告已发送至 {email_to}")

import schedule
import timedef daily_task():print(f"\n=== 开始执行每日任务 {datetime.now()} ===")export_orders()                # 步骤1：导出数据report_file = process_data()    # 步骤2：数据处理create_excel_charts(report_file) # 步骤3：生成图表send_report('manager@company.com', report_file)  # 步骤4：邮件发送print("=== 任务执行完成 ===")# 设置每日9:00自动执行
schedule.every().day.at("09:00").do(daily_task)# 守护进程（你可以在服务器后台运行）
while True:schedule.run_pending()time.sleep(60)  # 每分钟检查一次

# 元素加载等待策略（避免定位失败）
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC# 使用显式等待替代time.sleep()
element = WebDriverWait(driver, 10).until(EC.presence_of_element_located((By.ID, "dynamic_element"))
)

# 启用故障安全机制（鼠标移到左上角终止）
pyautogui.FAILSAFE = True# 添加随机延迟模拟人类操作
import random
pyautogui.click(x=100, y=200, duration=random.uniform(0.2, 0.5))

# 全流程异常捕获与重试
from tenacity import retry, stop_after_attempt@retry(stop=stop_after_attempt(3))
def critical_step():try:# 业务代码except ElementClickInterceptedException:# 处理弹窗干扰driver.switch_to.alert.dismiss()

# 添加详细运行日志
import logging
logging.basicConfig(filename='rpa_system.log',level=logging.INFO,format='%(asctime)s - %(levelname)s - %(message)s'
)# 在关键节点记录状态
logging.info("开始处理订单数据")
process_data()
logging.info("数据处理完成")

# 启动一个专用容器运行财务机器人  
docker run -d --name rpa_finance \  -v /data/rpa/config:/config \  rpa-runtime:latest

try:  driver.find_element(By.ID, "submit_btn").click()  
except NoSuchElementException:  # 触发邮件告警并转为人工处理  send_alert_email("登录按钮消失，请检查网页改版！")

import random  
human_delay = random.uniform(0.5, 2.0)  # 生成0.5~2秒随机延迟  
pyautogui.typewrite("text", interval=human_delay)

def clean_data(data):  # 处理金额字段中的非数字字符  if isinstance(data['amount'], str):  data['amount'] = float(''.join(filter(str.isdigit, data['amount'])))  # 自动补全省略日期（如7/21 → 2025-07-21）  if len(data['date']) < 10:  data['date'] = f"2025-{data['date']}"  return data