app.py

import sqlite3
import os.path
import numpy as np
from flask import Flask, request, jsonify, render_template, session, flash
import pickle
from passlib.hash import sha256_crypt

app = Flask(__name__)
model = pickle.load(open('model.pkl', 'rb'))
BAIS_DIR = os.path.dirname((os.path.abspath(__file__)))
db_path = os.path.join(BAIS_DIR, "Login.db")
sqlite3Connection = sqlite3.connect(db_path, check_same_thread=False)
cursor = sqlite3Connection.cursor()
print("Successfully Connected to SQLite")


@app.route('/')
def home():
    if not session.get('logged_in'):
        return render_template('login.html')
    else:
        return render_template('index.html')

# C:\Users\user\OneDrive\Desktop\MuhammadWebApp\Login.db
@app.route('/login', methods=['POST'])
def do_admin_login():
    sqlite3Connection = sqlite3.connect('C:\\Users\\user\\OneDrive\\Desktop\\MuhammadWebApp\\Login.db', check_same_thread=False)
    cursor = sqlite3Connection.cursor()
    login = request.form

    userName = login['username']

    password = login['password']
    print("start")
    sqlite_select_query = ("SELECT * FROM login WHERE username= '%s'" % userName + ';')
    sqlite_select_query = str((sqlite_select_query))
    print("End query:")

    cursor.execute(sqlite_select_query)

    print("execute query:")

    data = cursor.fetchone()
    print(data)

    if sha256_crypt.verify(password, data):
        account = True

    if account:
        session['logged_in'] = True
    else:
        flash('wrong password!')
        cursor.close()
    return home()


@app.route('/predict', methods=['POST'])
def predict():

    int_features = [int(x) for x in request.form.values()]
    final_features = [np.array(int_features)]
    prediction = model.predict(final_features)

    output = round(prediction[0], 2)
    if (output == 0):
        output = "Non Fradulent"
    else:
        output = "Fradulent"

    return render_template('index.html', prediction_text='Transaction is {}'.format(output))


@app.route('/predict_api', methods=['POST'])
def predict_api():

    data = request.get_json(force=True)
    prediction = model.predict([np.array(list(data.values()))])

    output = prediction[0]
    return jsonify(output)


if __name__ == "__main__":
    app.run(debug=True)