Deep-Learning-Project/test_putThemBack.py at master · novking/Deep-Learning-Project · GitHub

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
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 15 17:30:28 2016

@author: yiz613
"""
import re
import sqlite3
import os
import random
import math
import pickle
import unPickle

conn = sqlite3.connect(r'matchTest.sqlite')
cur = conn.cursor()
#print ('Generating SQL file...')
cur.executescript('''
DROP TABLE IF EXISTS drugNameTable;
CREATE TABLE drugNameTable ( id INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT UNIQUE,
    drug_Name   INTEGER  NOT NULL);
''')

def afunc(inputDataFile):
    def load(filename):
        with open(filename, "rb") as f:
            while True:
                try:
                    yield pickle.load(f)
                except EOFError:
                    break


    items = load(inputDataFile)

    unpickleList=list(items)

    targetResult = list()

    for eachSample in unpickleList:
        targetResult.append(int(eachSample[0]))

    return targetResult


Druglist =list()
DrugList =  afunc("encoded_train_pickle")

for drug in DrugList:
    cur.execute('''INSERT INTO drugNameTable (drug_Name) VALUES ( ? )''',  (drug, ) )
conn.commit()

DrugList =  afunc("encoded_valid_pickle")

for drug in DrugList:
    cur.execute('''INSERT INTO drugNameTable (drug_Name) VALUES ( ? )''',  (drug, ) )
conn.commit()

DrugList =  afunc("encoded_test_pickle")

for drug in DrugList:
    cur.execute('''INSERT INTO drugNameTable (drug_Name) VALUES ( ? )''',  (drug, ) )
conn.commit()


cur.close()