#auther :keepython
import pandas as pd
import numpy as np
import os
import time
import randomword_file_path = 'word/六级核心词汇表(EXCEL表格).xls'
data_log_path = 'data/data_log.csv'
# data_log = pd.read_csv(data_log_path)
words = pd.read_excel(word_file_path,header=0)
# print(len(words)+1)#求出一共多少列，从1开始算
# print(words.columns)#列索引名称
# print(words.index)#行索引名称words_index = words.index#函数功能：传入随机生成的单词索引，返回单词dataframe相关信息
def find_word(random_word_index,words):print(type(random_word_index))#根据随机单词的索引导出单词的相关信息random_words = words.loc[list(random_word_index)]# print(random_words)return random_words#函数功能: 在进行random_80函数操作以后对word.csv进行同步记录,注意传进来的必须是列表的形式
def word_csv_log(random_words,time_stamp):word_path = 'data/word.csv'word_log = pd.read_csv(word_path,index_col=0)#读取单词日志文件,同时将索引设置为对应的时间for random_word in random_words:#将对应的随机抽取的单词5min,30min,12hour分别标记为1word_log.loc['time'][random_word] = time_stampword_log.iloc[0:3][random_word][0] = 1word_log.iloc[0:3][random_word][1] = 1word_log.iloc[0:3][random_word][2] = 1word_log.to_csv(word_path)print('标记完成'.center(40,'='))#函数功能:读取日志已经选择的单词索引内容返回列表
def data_log_read(data_log_path):data_logs = pd.read_csv(data_log_path)data_log_index = np.array(data_logs).tolist()return data_log_index#函数功能：通过索引提取dataframe中的行，返回对应的dataframe数据方便生成csv文件
def random_80_word_to_csv(random_index,words):random_80_word_df = words.iloc[random_index,:]return random_80_word_df#函数功能：随机从传入的单词索引列表中抽取80个词
def random_80_word(words_indexs,words):data_log_path = 'data/data_log.csv'# print(type(words_index))#显示传入索引格式try:data_log_index = data_log_read(data_log_path)#返回日志中的索引words_index = [i for  i in words_indexs if i not in data_log_index]except :words_index= list(words_indexs)random_word = random.sample(list(words_index),80)#同时记录被选中的索引数据print(len(random_word))random_words = find_word(random_word,words)[['单词']]random_words = np.array(random_words).tolist()#这里是列表嵌套的形式需要解套random_words = [i[0] for i in random_words]#将随机抽取的#time模块的使用还要考虑到后面everyday_word.csv文件命名的问题，文件名称中不能有特殊符号time_stamp = time.strftime("%Y-%m-%d-%H-%M", time.localtime())#使用time模块以对应的年-月-日-小时-分钟的形式返回的数据为字符串every_day_word_path = 'every_day_word/'+str(time_stamp)+'.csv'random_80_word_df = random_80_word_to_csv(random_word,words)#在这一步调用函数同时生成对应random文件数据word_csv_log(random_words,time_stamp)print(type(random_80_word_df))random_80_word_df.to_csv(every_day_word_path)data = {time_stamp: random_word}#用于data_log.csv路径不存在情况if os.path.exists(data_log_path):#将今天生成的随机单词存入日志csv文件中备用datas = pd.read_csv(data_log_path)datas.loc[:, str(time_stamp)] = pd.Series(random_word)# datas[time_stamp] = random_word #注意，由于日期的原因无法输入列索引相同的数据，dataframe本质有点像优化的数据库datas.to_csv(data_log_path,index=False)#注意这里的mode的设置，必须设置为覆盖模式else:datas = pd.DataFrame(data)datas.to_csv(data_log_path, index=False)return random_word,every_day_word_path#将随机索引的80个词返回random_word_index,every_day_word_path = random_80_word(words_indexs=words_index,words= words)
# print(random_word_index)random_words_df = find_word(random_word_index,words)#返回的依然是dataframe格式的数据
# print(type(random_words))#返回索引到的单词数据用于建立日期表
random_words = random_words_df[['单词']]#对列进行操作这里还是dataframe格式
random_words_lists = np.array(random_words).tolist()#注意这里的random_words_list每一个random_word都是单独的列表，迭代时需要[0]for random_word in random_words_lists:print('今日随机单词'.center(80,'='))print(random_word[0])
#这里借助numpy将dataframe转换为list格式方便后面进行文件重组时间文件#word_read_pro.py的最终目的就是提供80个随机单词，不具备判断能力,但是记录随机筛选的单词的索引#在随后的返回函数中根据csv时间文件判断是否需要call_back
# random_words_lists = np.array(random_words).tolist()#注意这里的random_words_list每一个random_word都是单独的列表，迭代时需要[0]

# auther : keepython
import pandas as pd
import numpy as np
import random
file_name = '六级核心词汇表(EXCEL表格)'
word_file_path = '/word_recording_project/word/' + file_name+'.xls'
words = pd.read_excel(word_file_path,header=0)
words_index = words.indexwords = words[['单词']]
print(len(np.array(words).tolist()))
words = np.array(words).tolist()#将所有单词转换为列索引，行索引转换为天数
print(len(words))
datas = {}
for word in words :datas[word[0]] = {"5min":0,"30min":0,'12hour':0,'day1':0,'day2':0,'day4':0,'day7':0,'day15':0,'time':'1111-11-11-11-11'}words_df = pd.DataFrame(data=datas)
print(words_df)
words_df.to_csv('/word_recording_project/data/word.csv')
# print(words_df)

import time
import datetime
import pandas as pd
import numpy as np
from  word_read_project import every_day_word_path
from mail_send_project import mail_send_fuc#函数功能：负责time时间的相减,并分别返回时间间隔时间为1day 2day 4day 7day 15day 的路径列表
def read_log_remind():word_log_path = '/word_recording_project/data/word.csv'word_log = pd.read_csv(word_log_path,index_col=0)word_log = word_log.Tword_log = word_log[word_log.time != '1111-11-11-11-11']  # 提取word.csv文件中time所有不等于‘1111-11-11-11-11’的模块#将矩阵转置方便使用index提取路径time_stamp = time.strftime("%Y-%m-%d-%H-%M", time.localtime()).split('-')log_times = np.array(word_log['time']).tolist()today = datetime.datetime(int(time_stamp[0]),int(time_stamp[1]),int(time_stamp[2]),int(time_stamp[3]),int(time_stamp[4]))#分别设置对应天数的路径列表day_1_path = []day_2_path = []day_4_path = []day_7_path = []day_15_path = []for log_time in log_times:log_timed = log_time.split('-')# print(log_timed)last_day = datetime.datetime(int(log_timed[0]),int(log_timed[1]),int(log_timed[2]),int(log_timed[3]),int(log_timed[4]))reduce = today - last_day#用于判断天数if reduce.days == 1:path  = '/word_recording_project/every_day_word/'+log_time+'.csv'day_1_path.append(path)elif reduce.days == 2:path = '/word_recording_project/every_day_word/' + log_time+'.csv'day_2_path.append(path)elif reduce.days == 4:path = '/word_recording_project/every_day_word/' + log_time+'.csv'day_4_path.append(path)elif reduce.days == 7:path = '/word_recording_project/every_day_word/' + log_time+'.csv'day_7_path.append(path)elif reduce.days == 15:path = '/word_recording_project/every_day_word/' + log_time+'.csv'day_15_path.append(path)#列表收集完路径后还需要去重day_1_path = list(set(day_1_path))day_2_path = list(set(day_2_path))day_4_path = list(set(day_4_path))day_7_path = list(set(day_7_path))day_15_path = list(set(day_15_path))return day_1_path,day_2_path,day_4_path,day_7_path,day_15_path#负责当天的推进5 min 30 min 12小时
def today_word_count():today_path = every_day_word_pathprint('今日要推送的地址是： ',today_path)time_stamp = time.strftime("%Y-%m-%d", time.localtime())subject = '艾宾浩斯 '+time_stamp+' 第一次单词提醒'mail_send_fuc(today_path,subject)time.sleep(300)#5min提醒mail_send_fuc(today_path,subject)time.sleep(1500)#30min提醒mail_send_fuc(today_path,subject)time.sleep(41400)#12小时提醒mail_send_fuc(today_path,subject)

import smtplib
from email.header import Header
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
from email.mime.application import MIMEApplication
#从word.csv文件传入文件everyday文件路径就可以直接发送邮件
# everyday_file_path = '2020-02-02.csv'#函数功能：传入附件路径，邮件的主题发送邮件并返回发送状态def mail_send_fuc(everyday_file_path,subject):message = MIMEMultipart()msg_from = '***********'  # 发送方邮箱地址。password = '***************'  # 发送方QQ邮箱授权码，不是QQ邮箱密码。msg_to = '*************'msg_to_1 = '******************'  # 收件人邮箱地址。message = MIMEMultipart()message['From'] = msg_from  # 发送者message['To'] = msg_to  # 接收者# 邮件标题message['Subject'] = Header(subject, 'utf-8')# 邮件正文内容message.attach(MIMEText('艾宾浩斯根据你的遗忘曲线提醒单词'.center(20,'+'), 'plain', 'utf-8'))#打开文件part = MIMEApplication(open(everyday_file_path, 'rb').read())part.add_header('Content-Disposition', 'attachment', filename=everyday_file_path)message.attach(part)#添加文件try:client = smtplib.SMTP_SSL('smtp.qq.com', smtplib.SMTP_SSL_PORT)print("连接到邮件服务器成功")client.login(msg_from, password)print("登录成功")client.sendmail(msg_from, msg_to, message.as_string())print("发送成功")except smtplib.SMTPException as e:print("发送邮件异常")finally:client.quit()# mail_send_fuc(everyday_file_path)

import pandas as pd
import numpy as np
import os
import time
import random
from every_day_count_pro import *#总的执行函数包括写入word.csv日志的功能if __name__ == '__main__':day_1_paths, day_2_paths, day_4_paths, day_7_paths, day_15_paths = read_log_remind()today_word_count()time.sleep(3600)#1小时后再复习昨天的知识if len(day_1_paths) != False:for day_1_path in day_1_paths:subject = '1 天前的单词复习'.center(20,'=')mail_send_fuc(day_1_path,subject)time.sleep(900)if len(day_2_paths) != False:for day_2_path in day_2_paths:subject = '2 天前的单词复习'.center(20,'=')mail_send_fuc(day_2_path,subject)time.sleep(900)if len(day_4_paths) != False:for day_4_path in day_4_paths:subject = '4 天前的单词复习'.center(20,'=')mail_send_fuc(day_4_path,subject)time.sleep(900)if len(day_7_paths) != False:for day_7_path in day_7_paths:subject = '4 天前的单词复习'.center(20,'=')mail_send_fuc(day_7_path,subject)time.sleep(900)if len(day_15_paths) != False:for day_15_path in day_15_paths:subject = '15 天前的单词复习'.center(20,'=')mail_send_fuc(day_15_path,subject)

crontab -e

service crond restart