/
server.py
225 lines (186 loc) · 10.1 KB
/
server.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
from gevent import monkey; monkey.patch_all()
import difflib
from gevent import pywsgi
from flask import Flask
from flask import request, jsonify
from wechatpy.utils import check_signature
from wechatpy.exceptions import InvalidSignatureException
from wechatpy.replies import TextReply, ArticlesReply
from wechatpy import parse_message
from Check_duplication import Redis
import pandas as pd
import re
app = Flask(__name__)
def Reply_text(msg, reply_text):
"""
用于回复文本数据
:param msg:
:param reply_text:
:return:
"""
reply_data = TextReply(content=reply_text, message=msg)
reply_xml = reply_data.render()
return reply_xml
def Reply_Article(msg, reply_dic):
reply = ArticlesReply(message=msg)
# simply use dict as article
reply.add_article(reply_dic)
return reply.render()
def extract_que(que_path):
"""
提取所有问题回复数据
返回问题分级字典 和答案字典
:param que_path:
:return:
"""
que_df = pd.read_excel(que_path)
que_dict = {} # 序号对应问题字典
ans_dict = {} # 问题对应答案字典
for column in que_df:
que_dict[column] = {}
for que in list(que_df[column]):
if type(que) == str:
que = que.replace("\n", "")
if " " in que:
ques = que.split("答案:")[0]
ques = ques.replace(re.search("(\d+(\.\d+)?)", ques).group(), '').strip()
ans = que.split("答案:")[1]
ans_dict[ques] = ans.strip()
else:
que_index = que.split(".")[0]
if len(que_index) == 2:
que = que[3:]
else:
que = que[2:]
que_dict[column][que_index] = {}
# que_dict[column][que_index][que] = {j[2: 5]: j.split('\n')[0][5:] for j in list(que_df[column]) if " " in j and que_index+"." in j}
que_dict[column][que_index][que] = {}
ls = list(que_df[column])
# if que_index == "3":
# pass
for j in ls:
if type(j) == str:
if " " in j and que_index + "." in j:
j = j.strip()
if re.search("(\d+(\.\d+)?)", j).group().split('.')[0] != que_index:
pass
else:
if len(que_index) == 2:
que_dict[column][que_index][que][j[0: 4]] = j.split('\n')[0][4:]
else:
que_dict[column][que_index][que][j[0: 3]] = j.split('\n')[0][3:]
return que_dict, ans_dict
@app.route('/check_token', methods=['GET'])
def Check_token():
"""
用来验证微信公众号后台链接
:return:
"""
rq_dict = request.args
if len(rq_dict) == 0:
return ""
signature = request.args.get('signature') # 提取请求参数
timestamp = request.args.get('timestamp')
nonce = request.args.get('nonce')
echostr = request.args.get('echostr')
try:
check_signature(token='验证token', signature=signature, timestamp=timestamp, nonce=nonce) # 使用wechat库验证
except InvalidSignatureException as e:
print(e)
return ''
else:
print(111111)
return echostr # 返回数据
@app.route('/check_token', methods=['POST'])
def Reply_user():
"""
用于自动回复客服消息
:return:
"""
que_dict, ans_dict = extract_que('./ques_data.xlsx') # 加载问题及回复信息
req_key_word = que_dict.keys() # 所有可回复的关键词
wechat_send_data = request.data # 接收消息提醒 为xml格式
msg = parse_message(wechat_send_data) # wechat模块解析数据
FromUserName = msg.source # 消息的发送用户
CreateTime = msg.create_time # 消息的创建时间
ToUserName = msg.target # 消息的目标用户
duplication_flag = Redis.check_duplication("{}{}".format(FromUserName, CreateTime)) # 消息查重
if duplication_flag == 1:
pass
else:
print("推送重复")
return '' # 若重复 返回1
if msg.type == "event": # 为事件消息
if msg.event == "subscribe": # 关注事件回复
return Reply_text(msg, '====自动回复=====\n 欢迎关注, 回复 {} 即可获取相关信息。').format("、".join(req_key_word))
elif msg.event == "unsubscribe": # 取关事件回复
return Reply_text(msg, "====自动回复=====\n 下次再见。")
elif msg.event == "click" and msg.key == "zhinengkefu":
return Reply_text(msg, '====自动回复=====\n 回复 {} 即可获取相关信息。').format("、".join(req_key_word))
else:
return ''
elif msg.type == "text": # 为文本消息
text_type = Redis.save_uesr_rec(FromUserName) # 查询用户上次五分钟之内的浏览记录
send_text = msg.content # 用户发送的文本消息
if text_type != False: # 用户具有上次浏览记录
text_type = text_type.decode("utf-8")
if send_text in req_key_word: # 如果输入为关键词
Redis.save_uesr_rec(user_id=FromUserName, type='save', rec=send_text) # 存储本次浏览记录
ques = que_dict[send_text]
reply_text = '====自动回复=====\n{}\n 请回复问题前序号, 例"1"'.format(
''.join(["{}.{}\n".format(i, list(ques[i].keys())[0]) for i in ques]))
return Reply_text(msg, reply_text)
elif text_type in req_key_word: # 具有上次浏览记录
if re.search("(\d+(\.\d+)?)", send_text): # 如果可以提取出数字
Redis.save_uesr_rec(user_id=FromUserName, type='save', rec=text_type) # 存储本次浏览记录
ques_index = re.search("(\d+(\.\d+)?)", send_text).group()
try:
if "." not in ques_index: # 询问1级标题
ques = list(que_dict[text_type][str(send_text)].values())[0]
reply_text = '====自动回复=====\n{}\n 请回复问题前序号, 例"1.1"'.format(
''.join(["{}{}\n".format(i, ques[i]) for i in ques]))
else: # 询问二级标题
ques = list(que_dict[text_type][str(send_text.split('.')[0])].values())[0]
que_ans = ans_dict[ques[str(send_text)]]
if "(图文)" in que_ans:
que_ans = que_ans.replace("(图文)", "").split("=")
reply_dic = {
'title': que_ans[0],
'description': que_ans[1],
'image': '',
'url': 'https://mp.weixin.qq.com/s/ZuXJAHOPt3y5sRr4hJmhuQ'
}
return Reply_Article(msg, reply_dic)
reply_text = '====自动回复=====\n{}\n'.format(que_ans)
except Exception as e:
print("失败 输入信息为 {}-{} {}".format(send_text, text_type, e))
reply_text = '====自动回复=====\n 我不懂您的意思, 请回复 {} 即可获取相关信息。'.format("、".join(req_key_word))
else: # 无法提取出数字 首先进行模糊匹配 匹配失败 返回 如下
pro_que = difflib.get_close_matches(send_text, ans_dict.keys(), 1, cutoff=0.6)
if pro_que == []:
reply_text = '====自动回复=====\n 我不懂您的意思, 请回复 {} 即可获取相关信息。'.format("、".join(req_key_word))
else:
que = pro_que[0]
que_ans = ans_dict[que]
reply_text = '====自动回复=====\n 请问您要询问的问题是否是？\n {} \n回复:{}'.format(que, que_ans)
return Reply_text(msg, reply_text)
else: # 用户不具有上次浏览记录
if send_text in req_key_word: # 根据用户回复关键字 返回相关问题
Redis.save_uesr_rec(user_id=FromUserName, type='save', rec=send_text) # 存储本次浏览记录
ques = que_dict[send_text]
reply_text = '====自动回复=====\n{}\n 请回复问题前序号, 例"1"'.format(
''.join(["{}.{}\n".format(i, list(ques[i].keys())[0]) for i in ques]))
else: # 若无关键字 首先进行模糊匹配 匹配失败 返回建议信息
pro_que = difflib.get_close_matches(send_text, ans_dict.keys(), 1, cutoff=0.6)
if pro_que == []:
reply_text = '====自动回复=====\n 我不懂您的意思, 请回复 {} 即可获取相关信息。'.format("、".join(req_key_word))
else:
que = pro_que[0]
que_ans = ans_dict[que]
reply_text = '====自动回复=====\n 请问您要询问的问题是否是？\n {} \n回复:{}'.format(que, que_ans)
return Reply_text(msg, reply_text)
if __name__ == '__main__':
app.debug = True # 1.0以后版本不通过本方法启动调试模式
server = pywsgi.WSGIServer(('0.0.0.0', 80), app)
server.serve_forever()
# app.run(debug=True, processes=True)