Verify Ticker Presence in yfinance

Handling Invalid Tickers with yfinance in Python

In today’s blog post, I’ll be addressing a common issue that surfaces when employing the yfinance library in Python. Specifically, I’ll address how to handle invalid stock tickers effectively. When working with financial data, handling errors gracefully is crucial because malformed or non-existent ticker symbols can often lead to unexpected outcomes, or worse, misinformed financial decisions.

Understanding the Challenge

While working on a personal finance project, I encountered a challenge with the yfinance library. My goal was rather straightforward: fetch data for stock tickers. However, not all ticker inputs are valid, and invalid tickers can lead to unhelpful error messages and an inability to execute specific error-handling code. Here’s a snippet of what I tried initially:

import yfinance as yf

ticker = yf.Ticker("ABCDE")

try:
    info = ticker.info
    print(info)
except KeyError:
    print(f"Cannot get info of {ticker}, it probably does not exist")

The problem with the above approach is that it doesn’t work as intended because yfinance doesn’t throw an exception for non-existent tickers; it still returns a Ticker object and attempts to fetch the data. If the ticker does not exist, it doesn’t raise a KeyError but manages the situation internally, leading to a somewhat misleading outcome where the program prints partial or inaccurate information.

A Better Way: Custom Error Checking

To resolve this and make my error-handling robust, I needed a way to verify if the fetched information was valid or if the ticker was indeed incorrect. Here’s how I approached it:

import yfinance as yf

def get_ticker_info(symbol):
    ticker = yf.Ticker(symbol)
    info = ticker.info

    # Check if the retrieved data includes an error indication
    if "symbol" not in info or info.get("regularMarketPrice") is None:
        raise ValueError(f"No data found for {symbol}. It might be an invalid ticker.")

    return info

ticker_symbol = "ABCDE"

try:
    ticker_data = get_ticker_info(ticker_symbol)
    print(ticker_data)
except ValueError as e:
    print(e)

Explanation

In the revised version, I added a function called get_ticker_info which:

1. Fetches the ticker information.

1. Checks crucial keys in the returned dictionary. If key fields like symbol and regularMarketPrice are missing or if these fields are set to None, we can reasonably assume the ticker symbol is invalid or data is not available.

1. If the check fails, it raises a ValueError, which I then catch explicitly in my main program block.

By checking the content of the info dictionary for expected keys and valid data, this method offers a direct way to validate the existence and correctness of a stock ticker. If the validation fails, the program raises a ValueError, allowing us to handle this specific situation in a predictable manner.

Conclusion

To sum up, when leveraging APIs or external libraries like yfinance for financial data retrieval, ensuring accurate input validation and error handling is key. By implementing a custom check as demonstrated, you can ensure more reliable application behavior and clearer error reporting, leading to better data integrity and user experience in your financial applications. This approach keeps your code both readable and resilient to common input errors.