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
import pymysql
import datetime
import json
import redis
import pandas as pd
from sqlalchemy import create_engine
def get_mysql_data(host,port,user,passwd,db,sql):
db = pymysql.connect(host=host, port=port, user=user, passwd=passwd,db=db)
cursor = db.cursor()
cursor.execute(sql)
result = cursor.fetchall()
db.close()
return result
def get_esmm_users():
try:
stat_date = (datetime.date.today() - datetime.timedelta(days=1)).strftime("%Y-%m-%d")
sql = "select distinct device_id,city_id from data_feed_exposure_precise " \
"where stat_date = '{}'".format(stat_date)
result = get_mysql_data('172.16.40.170', 4000, 'root','3SYz54LS9#^9sBvC','jerry_prod',sql)
result = list(result)
return result
except:
return []
def get_user_profile(device_id,top_k = 5):
try:
r = redis.Redis(host="172.16.40.135", port=5379, password="", db=2)
key = "user:portrait_tags:cl_id:" + str(device_id)
if r.exists(key):
tmp = json.loads(r.get(key).decode('utf-8'))
tag_score = {}
for i in tmp:
if i["type"] == "tag":
tag_score[i["content"]] = i["score"]
elif i["content"] in name_tag.keys():
tag_score[name_tag[i["content"]]] = i["score"]
tag_sort = sorted(tag_score.items(), key=lambda x: x[1], reverse=True)
tags = []
if len(tag_sort) > top_k:
for i in range(top_k):
tags.append(tag_sort[i][0])
else:
for i in tag_sort:
tags.append(i[0])
return tags
else:
return []
except:
return []
def get_searchworlds_to_tagid():
try:
sql = 'select id, name from api_tag where is_online = 1 and tag_type < 4'
tag_id = get_mysql_data('172.16.30.141', 3306, 'work', 'BJQaT9VzDcuPBqkd', 'zhengxing', sql)
searchworlds_to_tagid = {}
for i in tag_id:
searchworlds_to_tagid[i[1]] = i[0]
return searchworlds_to_tagid
except Exception as e:
return {}
def get_queues(device_id,city_id):
try:
db = pymysql.connect(host='172.16.40.170', port=4000, user='root',
passwd='3SYz54LS9#^9sBvC', db='jerry_test')
cursor = db.cursor()
sql = "select native_queue, nearby_queue, nation_queue, megacity_queue from esmm_device_diary_queue " \
"where device_id = '{}' and city_id = '{}'".format(device_id, city_id)
cursor.execute(sql)
result = cursor.fetchone()
db.close()
if result is not None:
return list(result)
else:
return []
except:
return []
def tag_boost(cid_str, tag_list):
if cid_str is not None and cid_str != "" and len(tag_list) > 0:
cids = cid_str.split(",")
try:
if len(cids) > 6 and len(tag_list) > 0:
sql = "select id,group_concat(diary_id) from " \
"(select a.diary_id,b.id from src_mimas_prod_api_diary_tags a left join src_zhengxing_api_tag b " \
"on a.tag_id = b.id where b.tag_type < '4' and a.diary_id in {}) tmp " \
"where id in {} group by id".format(tuple(cids), tuple(tag_list))
result = get_mysql_data('172.16.40.170', 4000, 'root', '3SYz54LS9#^9sBvC','eagle',sql)
if len(result) > 0:
tag_cids = {}
left_cids = []
for i in result:
tmp = i[1].split(",")
tmp = [i for i in cids if i in tmp]
tag_cids[i[0]] = tmp
left_cids.extend(tmp)
left_cids = list(set(left_cids))
right_cids = [i for i in cids if i not in left_cids]
tag_cids["right"] = right_cids
tag_list.append("right")
sort_cids = []
n = 0
while n != len(tag_cids) - 1:
for i in tag_list:
if i in tag_cids.keys():
if len(tag_cids[i]) > 0:
sort_cids.append(tag_cids[i][0])
value = tag_cids[i]
value.pop(0)
tag_cids[i] = value
if len(value) == 0 and i != "right":
n = n + 1
if len(tag_cids["right"]) > 0:
sort_cids.extend(tag_cids["right"])
news_ids = []
for id in sort_cids:
if id not in news_ids:
news_ids.append(id)
new_str = ",".join([str(i) for i in news_ids])
return new_str
else:
return cid_str
else:
return cid_str
except:
#TODO 往sentry发，并且在本地也要打出日志
return cid_str
else:
return cid_str
def to_data_base(df):
sql = "select distinct device_id from esmm_resort_diary_queue"
result = get_mysql_data('172.16.40.170', 4000, 'root','3SYz54LS9#^9sBvC', 'jerry_test',sql)
old_uid = [i[0] for i in result]
if len(old_uid) > 0:
old_uid = set(df["device_id"].values)&set(old_uid)
old_number = len(old_uid)
if old_number > 0:
db = pymysql.connect(host='172.16.40.170', port=4000, user='root',
passwd='3SYz54LS9#^9sBvC', db='jerry_test')
sql = "delete from esmm_resort_diary_queue where device_id in {}".format(tuple(old_uid))
cursor = db.cursor()
cursor.execute(sql)
db.commit()
cursor.close()
db.close()
yconnect = create_engine('mysql+pymysql://root:3SYz54LS9#^9sBvC@172.16.40.170:4000/jerry_test?charset=utf8')
pd.io.sql.to_sql(df, "esmm_resort_diary_queue", yconnect, schema='jerry_test', if_exists='append', index=False,
chunksize=200)
print("insert done")
if __name__ == "__main__":
users_list = get_esmm_users()
print("user number")
print(len(users_list))
if len(users_list) > 0:
name_tag = get_searchworlds_to_tagid()
n = 500
split_users_list = [users_list[i:i + n] for i in range(0, len(users_list), n)]
for child_users_list in split_users_list:
total_samples = list()
for uid_city in child_users_list:
tag_list = get_user_profile(uid_city[0])
queues = get_queues(uid_city[0], uid_city[1])
if len(queues) > 0:
new_native = tag_boost(queues[0], tag_list)
new_nearby = tag_boost(queues[1], tag_list)
insert_time = str(datetime.datetime.now().strftime('%Y%m%d%H%M'))
sample = [uid_city[0], uid_city[1], new_native, new_nearby, queues[2], queues[3], insert_time]
total_samples.append(sample)
if len(total_samples) > 0:
df = pd.DataFrame(total_samples)
df = df.rename(columns={0: "device_id", 1: "city_id",2:"native_queue",
3:"nearby_queue",4:"nation_queue",5:"megacity_queue",6:"time"})
to_data_base(df)
else:
print("没有获取到用户")