Use Python, Requests, BeautifulSoup, CSV Writer, and MatPlotLib to scrape, write, and visualize a day on the stock market.

dow_visualizer.py

# From Python's Standard Library
from time import sleep
import datetime
import csv
# Third-party
import requests
import bs4
import matplotlib.pyplot as plt

times = []
prices = []

# Gets Dow Jones Industrial Average every 30 seconds for 6.5 hours, 780 total data points
for i in range(780):
    try:
        dj_page = "https://www.bloomberg.com/quote/INDU:IND"
        html = requests.get(dj_page).text
        soup = bs4.BeautifulSoup(html, "html.parser")
        price_div = soup.find("div", class_="price").text
        price = price_div.replace(",", "") # remove comma for float conversion in ln 29
        date_time = datetime.datetime.now()

        # Write datetime and price to CSV file for future reference
        with open("dj.csv", "a", newline="") as f:
          writer = csv.writer(f)
          writer.writerow([date_time, price])

        times.append(date_time)
        prices.append(float(price))

        print(f"{i}: Dow at {price} on {date_time}") # fstring literals require Python 3.6+
        sleep(30)  
    except:
        continue

# Visualize data in times list (x axis) and prices list (y axis) 
plt.plot(times,prices)
plt.gcf().autofmt_xdate()
plt.show()