Yahoo Finance is a good source for extracting financial data, be it – stock market data, trading prices or business related news.

In this tutorial, we will extract the trading summary for a public company from Yahoo Finance ( like http://finance.yahoo.com/quote/AAPL?p=AAPL ). We’ll be extracting the following fields for this tutorial.

1. Previous Close
2. Open
3. Bid
4. Ask
5. Day’s Range
6. 52 Week Range
7. Volume
8. Average Volume
9. Market Cap
10. Beta
11. PE Ratio
12. EPS
13. Earning’s Date
14. Dividend & Yield
15. Ex-Dividend Date
16. 1yr Target EST

Below is a screenshot of what data we’ll be extracting from Yahoo Finance.

Scraping Logic

1. Construct the URL of the search results page from Yahoo Finance. For example, here is the one for Apple-http://finance.yahoo.com/quote/AAPL?p=AAPL
2. Download HTML of the search result page using Python Requests
3. Parse the page using LXML – LXML lets you navigate the HTML Tree Structure using Xpaths. We have predefined the XPaths for the details we need in the code.
4. Save the data to a JSON file.

Requirements

For this web scraping tutorial using Python, we will need some packages for downloading and parsing the HTML. Below are the package requirements.

• Python 2.7 ( https://www.python.org/downloads/ )
• PIP to install the  following packages in Python ( https://pip.pypa.io/en/stable/installing/)
• Python Requests, to make requests and download the HTML content of the pages ( http://docs.python-requests.org/en/master/user/install/).
• Python LXML, for parsing the HTML Tree Structure using Xpaths ( Learn how to install that here – http://lxml.de/installation.html )

The Code

The code is self explanatory.

You can download the code from the link here, if the embed above does not work.

Running the Scraper

Assume the script is named yahoo_finance.py.  If you type in the script name in command prompt or terminal with a  -h

python yahoo_finance.py -h
usage: yahoo_finance.py [-h] ticker

positional arguments:
  ticker

optional arguments:
  -h, --help  show this help message and exit

The ticker argument is the ticker symbol or  stock symbol to identify a company .

To find the stock data for Apple Inc we would put the argument like this:

 python yahoo_finance.py aapl

This should create a JSON file called aapl-summary.json that will be in the same folder as the script.

The output file would look similar to this:

{
    "Previous Close": "139.52", 
    "Open": "138.92", 
    "Bid": "138.69 x 100", 
    "Ask": "139.01 x 4600", 
    "Day's Range": "138.82 - 139.80", 
    "52 Week Range": "89.47 - 140.28", 
    "Volume": "16,641,812", 
    "Avg. Volume": "28,451,631", 
    "Market Cap": "729.58B", 
    "Beta": "1.36", 
    "PE Ratio (TTM)": "16.69", 
    "EPS (TTM)": 8.33, 
    "Earnings Date": "2017-04-24 to 2017-04-28", 
    "Dividend & Yield": "2.28 (1.63%)", 
    "Ex-Dividend Date": "N/A", 
    "1y Target Est": 142.48, 
    "url": "http://finance.yahoo.com/quote/aapl?p=aapl", 
    "ticker": "aapl"
}

You can download the code at https://gist.github.com/scrapehero/516fc801a210433602fe9fd41a69b496

Let us know in the comments how this scraper worked for you.

Known Limitations

This code should work for grabbing stock market data of most companies. However, if you want to scrape for thousands of pages and do it frequently  (say, multiple times per hour) there are some important things you should be aware of, and you can read about them at How to build and run scrapers on a large scale and How to prevent getting blacklisted while scraping.

If you need some professional help with scraping complex websites contact us by filling up the form below.

Disclaimer: Any code provided in our tutorials is for illustration and learning purposes only. We are not responsible for how it is used and assume no liability for any detrimental usage of the source code. The mere presence of this code on our site does not imply that we encourage scraping or scrape the websites referenced in the code and accompanying tutorial. The tutorials only help illustrate the technique of programming web scrapers for popular internet websites. We are not obligated to provide any support for the code, however, if you add your questions in the comments section, we may periodically address them.