[7323fc]: / app.py

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import os
import xlrd
import pickle
import openpyxl
import numpy as np
import urllib.request, json
from flask import Flask, render_template
from flask import request, jsonify
from werkzeug.utils import secure_filename
from livereload import Server
app = Flask(__name__)
model = pickle.load(open('model.pkl', 'rb'))
@app.route('/')
def home():
return render_template('home.html')
@app.route('/page')
def page():
return render_template('page.html')
@app.route('/result')
def result():
return render_template('result.html')
@app.route('/gene')
def gene():
return render_template('gene.html')
@app.route('/predict',methods=['GET', 'POST'])
def predict():
'''
For rendering results on HTML GUI
'''
if request.method == 'POST':
f = request.files['file']
f.filename = 'patient_data.xlsx'
f.save(secure_filename(f.filename))
# return 'file uploaded successfully'
path = 'patient_data.xlsx'
wb_obj = openpyxl.load_workbook(path)
sheet_obj = wb_obj.active
# print(sheet_obj.cell(row = 2, column = 1).value)
d1 = sheet_obj.cell(row = 2, column = 2).value
d2 = sheet_obj.cell(row = 2, column = 3).value
d3 = sheet_obj.cell(row = 2, column = 4).value
d4 = sheet_obj.cell(row = 2, column = 5).value
d5 = sheet_obj.cell(row = 2, column = 6).value
d6 = sheet_obj.cell(row = 2, column = 7).value
d7 = sheet_obj.cell(row = 2, column = 8).value
d8 = sheet_obj.cell(row = 2, column = 9).value
d9 = sheet_obj.cell(row = 2, column = 10).value
d10= sheet_obj.cell(row = 2, column = 11).value
d11= sheet_obj.cell(row = 2, column = 12).value
d12= sheet_obj.cell(row = 2, column = 13).value
d13= sheet_obj.cell(row = 2, column = 14).value
d14= sheet_obj.cell(row = 2, column = 15).value
d15= sheet_obj.cell(row = 2, column = 16).value
d16= sheet_obj.cell(row = 2, column = 17).value
d17= sheet_obj.cell(row = 2, column = 18).value
d18= sheet_obj.cell(row = 2, column = 19).value
d19= sheet_obj.cell(row = 2, column = 20).value
d20= sheet_obj.cell(row = 2, column = 21).value
arr=np.array([[d1,d2,d3,d4,d5,d6,d7,d8,d9,d10,d11,d12,d13,d14,d15,d16,d17,d18,d19,d20]])
#int_features = [int(x) for x in request.form.values()]
#final_features = [np.array(int_features)]
prediction = model.predict(arr)
output = prediction[0]
if output==0:
print("Chemotherapy Not Suitable")
else:
print("Chemotherapy Suitable")
return render_template('result.html', data=prediction, prediction_text='{}'.format(output))
@app.route('/predict1',methods=['POST'])
def predict1():
'''
For rendering results on HTML GUI
'''
d1= request.form['a']
d2= request.form['b']
d3= request.form['c']
d4= request.form['d']
d5= request.form['e']
d6= request.form['f']
d7= request.form['g']
d8= request.form['h']
d9= request.form['i']
d10= request.form['j']
d11=request.form['k']
d12= request.form['l']
d13= request.form['m']
d14= request.form['n']
d15= request.form['o']
d16= request.form['p']
d17= request.form['q']
d18= request.form['r']
d19= request.form['s']
d20= request.form['t']
arr=np.array([[d1,d2,d3,d4,d5,d6,d7,d8,d9,d10,d11,d12,d13,d14,d15,d16,d17,d18,d19,d20]])
#int_features = [int(x) for x in request.form.values()]
#final_features = [np.array(int_features)]
prediction1 = model.predict(arr)
output = prediction1[0]
if output==0:
print("Chemotherapy Not Suitable")
else:
print("Chemotherapy Suitable")
return render_template('result.html', data=prediction1, prediction_text='{}'.format(output))
@app.route('/search',methods=['POST'])
def search():
if request.method == 'POST':
word = request.form['query']
search_word = word.upper()
print(search_word)
link = "https://clinicaltables.nlm.nih.gov/api/ncbi_genes/v3/search?terms="+search_word
with urllib.request.urlopen(link) as url:
data = json.loads(url.read().decode())
# print(data)
return jsonify({ 'htmlresponse': render_template('table.html', data = data, n = int(len(data[1])), word = search_word ) })
if __name__ == "__main__":
# app.run(debug=True)
server = Server(app.wsgi_app)
server.serve()