Tracking Stock Prices

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You've now built your first Flask application! In this next section, we're going to build upon this to create a web application for more than just dice rolling which we will deploy to the internet. Over the next few chapters we are going to extend this application further to add more functionality and explore more parts of Flask.

What we're building

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Some people like tracking the price of stocks, but if you go to many stock websites, there's a lot of clutter and the largest piece of information that people care about (the stock price) is not obvious. With our Python and Flask skills, we can make an application to solve that problem.

Setting up.

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In our terminal, let's go back to our fullstack-flask folder and create a new folder for our app (which we can call stock-app)

cd ~/fullstack-flask
mkdir stock-app
cd stock-app

Again, we're going to set up a virtual environment.

python3 -m venv env
source env/bin/activate

This time, to install Flask, we're going to create a file called requirements.txt where we list all of the dependencies of our project

touch requirements.txt

We're also going to use a Python library called requests to interface with an external API to fetch the data we need about stocks.

Put these lines in your file requirements.txt:

Flask
requests

Once we've set up this file, we can install the requirements using pip by running

pip install -r requirements.txt

Then we're going to create a server.py to start out our Flask application.

touch server.py
code .  # optional: to open the folder in VS Code

Within server.py, we're going to repeat the Flask imports to initialize our Flask application. This time in addition to importing Flask, we're going to import requests, a Python library to make HTTP requests.

from flask import Flask

app = Flask(__name__)

We will also need a free API key from FinancialModelingPrep.com to get access to the raw data. You can register for your own API key for free at https://financialmodelingprep.com/developer/docs/.