-
Notifications
You must be signed in to change notification settings - Fork 0
/
app.py
131 lines (126 loc) · 4.57 KB
/
app.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
from flask import Flask,Response,render_template
from flask import request
import pandas as pd
from werkzeug.utils import secure_filename
import json
import pickle
import os
path = os.getcwd()
#template_path=path+'/templates'
port = int(os.getenv("PORT", 3000))
upload_folder = path
ALLOWED_EXTENSIONS = set(['pkl','txt'])
app = Flask(__name__)
app.config['UPLOAD_FOLDER'] = upload_folder
@app.route('/upload')
def upload():
return render_template('upload.html')
@app.route('/uploader', methods = ['GET','POST'])
def upload_file():
try:
f = request.files['file']
f.save(secure_filename(f.filename))
print('file uploaded successfully')
return 'file uploaded successfully'
except Exception as e:
print(e)
@app.route('/predict', methods=['POST'])
def predict():
try:
linReg1 = pickle.load(open('predict1.pkl', 'rb'))
linReg2 = pickle.load(open('predict2.pkl', 'rb'))
linReg3 = pickle.load(open('predict3.pkl', 'rb'))
linReg4 = pickle.load(open('predict4.pkl', 'rb'))
linReg5 = pickle.load(open('predict5.pkl', 'rb'))
column_data = pd.read_csv(path+'/columns.csv')
column_1 = (column_data.columns[0])
print("column 1",column_1) #size
column_2 = (column_data.columns[1])
print("column 2", column_2) #bedrooms
column_3 = (column_data.columns[2])
print("column 3", column_3) #age
column_4 = (column_data.columns[3])
print("column 4", column_4) #bathrooms
column_5 = (column_data.columns[4])
print("column 5", column_5) #Price
req_body = request.get_json(force=True)
print(req_body)
# For Size
if req_body[column_1] == '':
param1 = req_body[column_2]
param2 = req_body[column_3]
param3 = req_body[column_4]
param4 = req_body[column_5]
pred = linReg1.predict([[param1, param2, param3, param4]])
result = pred
msg = {
"Predicted value is": "%s" % (result)
}
resp = Response(response=json.dumps(msg),
status=200,
mimetype="application/json")
return resp
# For Bedrooms
if req_body[column_2] == '':
param1 = req_body[column_1]
param2 = req_body[column_3]
param3 = req_body[column_4]
param4 = req_body[column_5]
pred = linReg2.predict([[param1, param2, param3, param4]])
result = pred
msg = {
"Predicted value is": "%s" % (result)
}
resp = Response(response=json.dumps(msg),
status=200,
mimetype="application/json")
return resp
# For Age
if req_body[column_3] == '':
param1 = req_body[column_1]
param2 = req_body[column_2]
param3 = req_body[column_4]
param4 = req_body[column_5]
pred = linReg3.predict([[param1, param2, param3, param4]])
result = pred
msg = {
"Predicted value is": "%s" % (result)
}
resp = Response(response=json.dumps(msg),
status=200,
mimetype="application/json")
return resp
# For Bathrooms
if req_body[column_4] == '':
param1 = req_body[column_1]
param2 = req_body[column_2]
param3 = req_body[column_3]
param4 = req_body[column_5]
pred = linReg4.predict([[param1, param2, param3, param4]])
result = pred
msg = {
"Predicted value is ": "%s" % (result)
}
resp = Response(response=json.dumps(msg),
status=200,
mimetype="application/json")
return resp
# For Price
if req_body[column_5] == '':
param1 = req_body[column_1]
param2 = req_body[column_2]
param3 = req_body[column_3]
param4 = req_body[column_4]
pred = linReg5.predict([[param1, param2, param3, param4]])
result = pred
msg = {
"Predicted value is ": "%s" % (result)
}
resp = Response(response=json.dumps(msg),
status=200,
mimetype="application/json")
return resp
except Exception as e:
print(e)
if __name__ == '__main__':
app.run(host='0.0.0.0',port=port)