Creating a WebApp using Flask+Gunicorn on Ubuntu Server: End-to-End Series (Part — 4)

What is Flask?

  • Flask is a micro web framework written in Python. It is classified as a microframework because it does not require particular tools or libraries.
  • It has no database abstraction layer, form validation, or any other components where pre-existing third-party libraries provide common functions.
  • Flask depends on the Jinja template engine and the Werkzeug WSGI toolkit.

Need for Gunicorn

  • Python Web Server Gateway Interface (WSGI) HTTP server.
  • It is a pre-fork worker model, ported from Ruby’s Unicorn project.
  • Gunicorn server is broadly compatible with a number of web frameworks, simply implemented, light on server resources, and fairly fast.
  • It does not support windows but will work on a Linux machine.
  • It helps complete one of the major drawbacks of the flask web app.
  • Flask web app is only restricted to one request at a time, all other request goes into waiting or are discarded.
  • Gunicorn distributes the load into multiple threads in which multiple workers can run parallelly.
  • The optimum amount of workers to be launched depends on the core of the server.
    workers = (2*number of cores) +1

Also, Check out our Article on:

  1. Data Abstraction: End-to-End Series (Part — 1)
  2. Data Preprocessing and EDA: End-to-End Series (Part — 2)
  3. Model Building and Experimentation: End-to-End Series (Part — 3)
  4. Containerizing the WebApp using Docker: End-to-End Series (Part — 5)
  5. Scaling our Docker Container using Kubernetes: End-to-End Series (Part — 6)
  6. Automating building and deployment using Jenkins: End-to-End Series (Part — 7)

Creating a Python Script using Flask

  • Create a file
from flask import Flask, render_template, request
import pickle
import numpy as np
app = Flask(__name__)model = pickle.load(open("randomforest.pkl", "rb"))@app.route('/')
def man():
return render_template('home.html')
@app.route('/predict', methods = ['POST'])
def home():
tenure = request.form['a']
PS = request.form['b']
C = request.form['c']
PB = request.form['d']
PM = request.form['e']
MC = request.form['f']
array = np.array([[tenure, PS, C, PB, PM, MC]])
pred = model.predict(array)
return render_template("result.html", data = pred)
if __name__ == "__main__": = '',port = 8000,debug = True)

Creating an HTML File

→ Home Template

  • Create a home.html file
<!DOCTYPE html>
<html lang="en">
<meta charset="UTF-8">
<title>Churn Prediction</title>
<body bgcolor=#F0F8FF>
<center><img src="static\LOGO.png" align="middle"></center><table style="width:100%">
<img src="static\customer_churn.jpg" align="middle" width="600" height="400">
<h1 style="font-family:verdana;font-size:250%;color:Red;"> Customer Churn Prediction</h1><br><form method="POST" action = "{{url_for('home')}}">
Tenure of the Customer: <input type="text", name="a", placeholder="enter 1"/><br><br>
Phone Service: <input type="text", name="b", placeholder="enter 2"/><br><br>
Contract: <input type="text", name="c", placeholder="enter 3"/><br><br>
Paperless Billing: <input type="text", name="d", placeholder="enter 4"/><br><br>
Payment Method: <input type="text", name="e", placeholder="enter 5"/><br><br>
Monthly Charges: <input type="text", name="f", placeholder="enter 6"/><br><br><br></b>
<button type="submit" class="btn btn-primary btn-block btn-large">Predict</button>
<marquee><i>International School of AI and Data Science</i></marquee>

→ Result Template

  • Create a result.html file
<!DOCTYPE html>
<html lang="en">
<meta charset="UTF-8">
<body bgcolor=#ADD8E6>
<h1 style="font-family:verdana;font-size:350%;"> Prediction</h1>
{%if data == 0%}
<h1 style="font-family:verdana;font-size:250%;color:Green;"> Customer will Not Churn</h1>
<img src="static\not_churn.gif">
<h1 style="font-family:verdana;font-size:250%;color:Red;"> Customer will Churn</h1>
<img src="static\churn.gif">
<a href="/">go back to home page</a>


  • After running the app go to your browser and on the address bar write localhost:8000 and press enter

Connecting to server

  • In order to connect to any server remotely in the windows machine, we will be using a bitwise SSH client.
    You download it from this link.
  • Open the bitwise SSH client and log into your server.
    I am using server IP, username, and password to log into the server.
  • Then open a terminal and update the ubuntu using the command
  • Create a directory using the command
  • Then on the bitwise SSH click on SFTP to transfer files from the local system to the server.
  • After the files have been copied to the server we need to start installing the libraries.
  • After installing the libraries we can now run the flask app on the server.
  • Once the app starts running. Go to your browser type in the server IP followed by port.
  • You can now access your web app from anywhere in the world.

Running the app using Gunicorn

→ Installing Gunicorn in the ubuntu server

sudo apt install gunicorn

→ Create a file

  • nano and press enter
  • Then write the following code and press Ctrl + X.
from flaskapp import appif __name__ == “__main__”:
  • Once the is created, on the Terminal type
gunicorn -w 5 --threads 3 --bind wsgi:flaskapp
  • You have now launched your web app using gunicorn on your server.

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