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/.

Thinking about our Flask Application design

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When building Flask applications, it is helpful to think about the URL structure of your final product. For the first version of our stock ticker application, we might want two endpoints if our application was hosted at FlaskFinance.com.

If we hit the root page of the application (FlaskFinance.com), we would want to see the prices of our favorite stocks, and there might be another page to render just the price of a single stock (for example FlaskFinance.com/stocks/APPL or FlaskFinance.com/stocks/GOOG)

Once we have an idea for what the routes should look like, Flask makes it easy to define these. We'll dive deeper into routing in a later chapter. We've already seen an example for the decorator for the index page (@app.route('/')) but to accept an arbitrary string like we would need to for FlaskFinance.com/stocks/AAPL, we can tell Flask to expect a parameter by @app.route('/stocks/<ticker>'), and then Flask will pass in an argument into the function based on what followed the in the URL path. For FlaskFinance.com/stocks/AAPL, the value of ticker would be AAPL.

Every route we define needs to point to a different function that will handle requests to that route. Let's create two routes in server.py for this.

@app.route('/')
def home():
    return "This is the home page. Try going to /stocks/AAPL"

@app.route('/stocks/<ticker>')
def stock(ticker):
    return "This is the page for the {} ticker".format(ticker)

We can try this in our browser by launching the Flask development server and see what we get.

FLASK_ENV=development FLASK_APP=server flask run

Your terminal output should look something like this:

Once your server is running you can pull up a page at 127.0.0.1:5000/stocks/AAPL

Now, we should try to get the actual prices of stocks using the API.

Let's write a function to fetch data from the API endpoint. I've already written it out here, and you can use it.

def fetch_price(ticker):
    data = requests.get('https://financialmodelingprep.com/api/v3/stock/real-time-price/{}'.format(ticker.upper()), params={'apikey': 'demo'}).json()
    return data["price"]

What this does: Issues a HTTP request to an API provided by financialmodelingprep.com which returns the price of the stock as a JSON object. Our function returns the price as a numeric value.

Once we have that we can integrate the fetch_price function into our stock function.

@app.route('/stocks/<ticker>')
def stock(ticker):
    stock_price = fetch_price(ticker)
    return "The price of {} is {}".format(ticker, stock_price)

Now if launch our Flask server and navigate to 127.0.0.1:5000/stocks/AAPL

FLASK_ENV=development FLASK_APP=server flask run

We should see the actual price of AAPL in our browser.