把数据库改成腾讯云

eda/esmm/Model_pipline/feature.py

@@ -37,7 +37,7 @@ def get_data():
     validate_date = con_sql(db, sql)[0].values.tolist()[0]
     print("validate_date:" + validate_date)
     temp = datetime.datetime.strptime(validate_date, "%Y-%m-%d")
-    start = (temp - datetime.timedelta(days=300)).strftime("%Y-%m-%d")
+    start = (temp - datetime.timedelta(days=3)).strftime("%Y-%m-%d")
     print(start)
     db = pymysql.connect(host='172.16.40.158', port=4000, user='root', passwd='3SYz54LS9#^9sBvC', db='jerry_test')
     sql = "select e.y,e.z,e.stat_date,e.ucity_id,feat.level2_ids,e.ccity_name,u.device_type,u.manufacturer," \

eda/esmm/Model_pipline/to_database.py

@@ -3,7 +3,7 @@
 from sqlalchemy import create_engine
 import pandas as pd
 import pymysql
-import time
+import datetime
 
 def con_sql(sql):
     """
@@ -60,8 +60,7 @@ def main():
     df_all = pd.merge(df3,df4,on=['device_id','city_id'],how='outer').fillna("")
     df_all['device_id'] = df_all['device_id'].astype(str)
     df_all['city_id'] = df_all['city_id'].astype(str)
-    ctime = int(time.time())
-    df_all["time"] = ctime
+    df_all["time"] = str(datetime.datetime.now().strftime('%Y%m%d%H%M'))
     print("union_device_count",df_all.shape)
 
     host='172.16.40.158'

eda/esmm/Model_pipline/to_tfrecord.py

@@ -4,13 +4,11 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 import pandas as pd
-import sys
 import os
 import glob
 
 import tensorflow as tf
 import numpy as np
-import re
 from multiprocessing import Pool as ThreadPool
 
 flags = tf.app.flags

eda/esmm/Model_pipline/train.py

@@ -6,12 +6,10 @@
 
 #import argparse
 import shutil
-#import sys
 import os
 import json
 import glob
 from datetime import date, timedelta
-from time import time
 
 import random
 import tensorflow as tf