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Create and Deploy your First Flask App using Python and Heroku

Create and Deploy your First Flask App using Python and Heroku

Last Updated on August 27, 2020 by Editorial Team

Author(s): Divy Shah


Flask is a web application framework written in Python. Here I created an application using Python and deployed on Heroku.

Click here to launch my demo web app.



After installing Python install the other frameworks and libraries listed. You can easily install flask using the following command.

pip install Flask
#pip install

Define the structure of your web app


The static directory contains your CSS files, and the template contains the HTML file, which is used for rendering.

You can create a separate .py file for your logic and other operations or write code in the same I suggest creating a separate file will reduce the confusion.

Step 1:

Create your file

I used the waitress service the reason behind using this library is meant to be a production-quality pure-Python WSGI server with very acceptable performance. It has no dependencies except ones that live in the Python standard library.

Install waitress

pip install waitress
import requests
from flask import Flask, render_template, redirect, url_for, request
from datetime import datetime, timedelta
import time
import json
import os
from trending import get_trending
app = Flask(__name__)
def trending():
info = get_trending()
render_template('display.html', info=info['data'])
return res
if __name__ == "__main__":
app.debug = False
port = int(os.environ.get('PORT', 33507))
waitress.serve(app, port=port)

As shown above, we used the GET Method to send data from the server.

There are several other methods also available which are

POST: It is used to send user/form-data to the server doesn’t cache the transmitted data.

HEAD: It is similar to GET, but the difference is it is used without the response body

PUT: It is Used to replace the current resource with uploaded content

DELETE: It is used to delete the target resource provided in the URL.

Step 2:

Create file which is basically the file which contains your business logic after creation import main function in file

from trending import get_trending

Below my file looks like:

After collecting the data, we can render the output using an HTML file

The output data will be displayed on the HTML page.

Step 3:

Create an HTML file for render the output which you collected from the response object.

Below is how my display.html file looks like


You are almost done with the coding part, and now it’s time to deploy our first flask app.

Before deploying the app, first, check the flask app on the localhost.

Deployment Steps

  1. Login to your Heroku account using CLI

You can log in by writing the following command in the terminal.

heroku login

2. Create a web app on Heroku

You can create a new application on Heroku using the following command

heroku create 

3. Create requirements.txt file in the same project directory

To generate requirement.txt file, you can use the following command

pip freeze > requirements.txt

4. Create a Procfile

Procfile is a Process file which is required for all Heroku applications.

Procfile specifies the commands that are executed by the app on startup.

Click here to read more on Procfile

enter the following in Procfile

web: gunicorn app:app

Here the app is the name of your main (.py) file in my case it is

if you don’t installed gunicorn web server then install it by using the following command

pip install gunicorn

NOTE: you have to create a Procfile without any file extensions

5. Create runtime.txt to specify the python version on runtime

After creating a runtime.txt add your build python version like below


Now, we are all set!

6. Initialize empty git repository and push the code

git init

Next, is time to commit your final code using the following steps

git add .
git commit -m "My first commit"
git push heroku master

Your app is live Now you can see your web app using generated URL

Please check out my demo web application

Create and Deploy your First Flask App using Python and Heroku was originally published in Towards AI — Multidisciplinary Science Journal on Medium, where people are continuing the conversation by highlighting and responding to this story.

Published via Towards AI

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