How to Get Real-Time Stock Prices in Python

This guide shows how to retrieve real-time stock prices in Python using the FinancialData.Net API and the fdnpy SDK. It covers single and batch quotes, pandas, alerts, and direct REST calls.

import os
from fdnpy import FinancialDataClient

client = FinancialDataClient(api_key=os.environ["FDN_API_KEY"])
quotes = client.get_stock_quotes(identifiers=["AAPL"])
print(quotes[0])

Requirements

• Python 3.6+
• An API key from FinancialData.Net
• A plan that includes the endpoint you call. The stock-quotes endpoint requires a Premium plan, while stock-prices (daily history) is available on the free plan. See pricing.

Set the key as an environment variable.

export FDN_API_KEY="your_api_key"

Install

pip install fdnpy pandas

fdnpy wraps the REST API, paginates automatically, and retries with exponential backoff.

Get a quote

get_stock_quotes calls GET /api/v1/stock-quotes.

quote = client.get_stock_quotes(identifiers=["MSFT"])[0]

Response:

{
  "trading_symbol": "MSFT",
  "registrant_name": "MICROSOFT CORP",
  "time": "2025-09-02 15:55:57",
  "price": 502.42,
  "change": -2.7,
  "percentage_change": -0.53
}

Get multiple quotes

identifiers takes a list of ticker symbols. Each request returns quotes for up to 300 symbols.

import pandas as pd

quotes = client.get_stock_quotes(identifiers=["AAPL", "MSFT", "NVDA", "AMZN"])
df = pd.DataFrame(quotes)[["trading_symbol", "price", "change", "time"]]
print(df.sort_values("change", ascending=False))

Batch symbols instead of looping one request per ticker.

Refresh on a schedule

To keep a watchlist current, call get_stock_quotes on an interval. Each call is one request regardless of symbol count.

import os
import time

import pandas as pd
from fdnpy import FinancialDataClient

client = FinancialDataClient(api_key=os.environ["FDN_API_KEY"])

while True:
    df = pd.DataFrame(client.get_stock_quotes(identifiers=["AAPL", "MSFT", "NVDA"]))
    df = df[["trading_symbol", "price", "change", "time"]]
    print(df.sort_values("trading_symbol"))
    time.sleep(10)

Price alerts

import os
import time
from fdnpy import FinancialDataClient

client = FinancialDataClient(api_key=os.environ["FDN_API_KEY"])

ALERTS = {"AAPL": ("above", 250.00), "NVDA": ("below", 120.00)}
triggered = set()

while len(triggered) < len(ALERTS):
    for quote in client.get_stock_quotes(identifiers=list(ALERTS)):
        symbol, price = quote["trading_symbol"], quote["price"]
        direction, target = ALERTS[symbol]
        hit = price >= target if direction == "above" else price <= target

        if hit and symbol not in triggered:
            triggered.add(symbol)
            print(f"{symbol} {direction} {target}: {price}")  # replace with webhook/email
            
    time.sleep(10)

Crypto, forex, indexes, ETFs

Same call pattern, different method.

crypto  = client.get_crypto_quotes(identifiers=["BTCUSD", "ETHUSD"])
forex   = client.get_forex_quotes(identifiers=["EURUSD", "GBPUSD"])
indexes = client.get_index_quotes(identifiers=["^GSPC", "^DJI"])
etfs    = client.get_etf_quotes(identifiers=["SPY", "QQQ"])

• Crypto and forex quote times are UTC. Crypto change is over a 24-hour window.
• Index symbols use a ^ prefix.

Raw REST

All endpoints are GET. Authenticate with a key query parameter.

curl "https://financialdata.net/api/v1/stock-quotes?identifiers=MSFT,AAPL&key=$FDN_API_KEY"

import os
import requests

resp = requests.get(
    "https://financialdata.net/api/v1/stock-quotes",
    params={"identifiers": "MSFT,AAPL", "key": os.environ["FDN_API_KEY"]},
    timeout=10,
)
resp.raise_for_status()
print(resp.json())

Add format=csv to get CSV instead of JSON.

Rate limits

Troubleshooting

• Auth or permission error: confirm FDN_API_KEY is set in the running shell and that your plan includes the endpoint.
• Timestamps off by hours: stock, index, and ETF quotes are EST, while crypto and forex quotes are UTC.
• Rate limited: batch symbols, increase the refresh interval.