$ python -m venv venv
$ venv\Scripts\activate

$ pip install selenium
$ pip install tensorflow
$ pip install pandas
$ pip install pillow

from selenium import webdriver

def login(driver, ac, pa):
    driver.find_element_by_id("username").clear()
    driver.find_element_by_id("password").clear()
    username = driver.find_element_by_id("username")
    password = driver.find_element_by_id("password")
    username.send_keys(ac)
    password.send_keys(pa)
    
driver = webdriver.Chrome()
driver.get("放入網址")

ac = "輸入自己的學號"
pa = "輸入自己的密碼"
login(driver, ac, pa)

def get_captcha(driver):
    element = driver.find_elements_by_tag_name("img")
    img = element[1]
    img.screenshot("captcha.png")
    
get_captcha(driver)

import numpy as np
from tensorflow.keras import models
from tensorflow.keras.preprocessing.image import img_to_array
from tensorflow.keras.preprocessing.image import load_img

digits_in_img = 4
img_rows = None
img_cols = None

def split_digits_in_img(img_array, img_rows, img_cols):
    x_list = []
    for i in range(digits_in_img):
        step = img_cols // digits_in_img
        x_list.append(img_array[:, i * step:(i + 1) * step] / 255)
    return x_list

def number():
    np.set_printoptions(suppress=True, linewidth=150, precision=9, formatter={'float': '{: 0.9f}'.format})
    model = models.load_model('cnn_model.h5')
    img_filename = './captcha.png'
    img = load_img(img_filename, color_mode='grayscale')
    img_array = img_to_array(img)
    img_rows, img_cols, _ = img_array.shape
    x_list = split_digits_in_img(img_array, img_rows, img_cols)
    varification_code = []
    for i in range(digits_in_img):
        confidences = model.predict(np.array([x_list[i]]), verbose=0)
        result_class = model.predict_classes(np.array([x_list[i]]), verbose=0)
        varification_code.append(result_class[0])
        guess = ""
    for i in varification_code:
        guess = guess+str(i)
    return guess

def capt(driver):
    get_captcha(driver)
    guess = number()
    driver.find_element_by_id("captcha").clear()
    captcha = driver.find_element_by_id("captcha")
    captcha.send_keys(guess)
    driver.find_element_by_class_name("btn-submit").click()
 
# 加在login(driver, ac, pa)下
 capt(driver)

title = driver.title

while title == "天主教輔仁大學 - 登入 Tronclass":
    login(driver, ac, pa)
    capt(driver)
    title = driver.title

from time import sleep

driver.get("https://elearn2.fju.edu.tw/bulletin-list/")
sleep(3)

info_dic = {"title":[], "class":[], "content":[]}

title_class = driver.find_elements_by_css_selector("div.bulletin-title span.ng-binding")
for i in range(0,10):
    print(title_class[i].text)
    info_dic["title"].append(title_class[i].text)

op = driver.find_elements_by_css_selector("div.bulletin-update-info")
for i in op:
    i.click()
contents = driver.find_elements_by_css_selector("div.content-container")

for i in range(0,10): # 剛剛的for迴圈
    print(contents[i].text)
    info_dic["content"].append(contents[i].text)
    print()

f = open(檔名, 模式, encoding=解碼方式)
"""
執行的動作
"""
f.close()

with open(檔名, 模式, encoding=解碼方式) as f:
    """
    執行的動作
    """

with open('example.txt', 'w', encoding = 'utf-8') as f:
    for i in range(0,10):
        f.write(info_dic["title"][i] + "\n")
        f.write(info_dic["class"][i] + "\n")
        f.write(info_dic["content"][i] + "\n")
        f.write("----------------我是分隔線----------------\n")

import pandas as pd
import csv

anouce = pd.DataFrame(info_dic)
anouce.to_csv("./anouce.csv")