NASDAQ API

A comprehensive Python library for fetching stock data from the NASDAQ API

---

Features

• 📈 Complete Stock Data: Fetch quotes, financials, dividends, historical prices, and more
• 🏢 Ownership Information: Institutional holdings and insider trades
• 📊 Financial Statements: Income statements, balance sheets, cash flow (annual & quarterly)
• 📰 News & Filings: SEC filings, press releases, and news articles
• 🔄 Normalized Data: Clean, structured data ready for analysis
• ⚡ Easy to Use: Simple, intuitive API with both modern and backward-compatible interfaces
• 🎯 Type Hints: Full type annotations for better IDE support
• 🧪 Well Tested: Comprehensive test suite

Installation

pip install nasdaqapi

Quick Start

Modern API (v0.2.0+)

from nasdaqapi import NasdaqClient

# Create client
client = NasdaqClient()

# Get real-time quote
quote = client.get_quote("AAPL")
print(f"${quote['price']} ({quote['change_percent']:.2%})")

# Get comprehensive data
data = client.get_symbol_data("AAPL", include=['quote', 'financials'])
print(data.keys())

# Search for symbols
tech_stocks = client.search_symbols(sector="Technology")

Legacy API (backward compatible)

from nasdaqapi import fetch_all_symbol_data

# Still works with existing code!
data = fetch_all_symbol_data("AAPL")
print(f"Company: {data['quote']['company_name']}")

Features

Quick Functions

from nasdaqapi import get_quote, get_symbol_data, search_symbols

# Quick quote lookup
quote = get_quote("MSFT")

# Get specific data categories
data = get_symbol_data("GOOGL", include=['financials', 'ownership'])

# Search symbols
nasdaq_stocks = search_symbols(exchange="NASDAQ")

Detailed Data Access

from nasdaqapi import NasdaqClient

client = NasdaqClient()

# Financial statements
financials = client.get_financials("AAPL", period="annual")
income_stmt = financials['income_statement']
balance_sheet = financials['balance_sheet']

# Dividends
dividends = client.get_dividends("MSFT")
print(f"Yield: {dividends['yield']:.2%}")

# Institutional ownership
ownership = client.get_ownership("GOOGL")
top_holders = ownership['institutional']['top_holders']

# Historical prices
prices = client.get_historical("TSLA", period="1month")
for day in prices:
    print(f"{day['date']}: ${day['close']}")

# News articles
news = client.get_news("NVDA", limit=10)
for article in news:
    print(f"{article['title']} - {article['source']}")

Metadata

• Company name, symbol, exchange
• Stock type and asset class
• Market status (pre-market, regular, after-hours)

Quote Data

• Current price, change, volume
• Bid/ask prices and sizes
• Previous close, timestamp

Key Metrics

• P/E ratio, dividend yield
• 52-week high/low
• Shares outstanding
• Market cap (when available)

Financial Statements

• Income Statement (annual & quarterly)
• Balance Sheet (annual & quarterly)
• Cash Flow Statement (annual & quarterly)
• Financial Ratios

Dividends

• Yield, annual amount, payout ratio
• Ex-dividend date, payment date
• Complete dividend history (80+ years for some stocks)

Historical Prices

• Daily historical prices
• 5-day and 1-month periods
• Open, high, low, close, volume

Ownership

• Institutional holdings and changes
• Top holders (Vanguard, BlackRock, etc.)
• Insider trades
• Ownership percentages

Analyst Data

• PEG ratio
• P/E ratio trends
• Growth rate estimates

Short Interest

• Shares short
• Average daily volume
• Days to cover

News & Filings

• SEC filings (10-K, 10-Q, 8-K, etc.)
• Press releases
• News articles

Advanced Usage

Fetch Specific Data Categories

from nasdaqapi import (
    fetch_symbol_info,
    fetch_symbol_dividends,
    fetch_company_financials,
    fetch_institutional_holdings
)

# Fetch only what you need
info = fetch_symbol_info("MSFT")
dividends = fetch_symbol_dividends("MSFT")
financials = fetch_company_financials("MSFT", frequency=1)  # 1=annual, 2=quarterly
holdings = fetch_institutional_holdings("MSFT", limit=50)

Fetch Multiple Exchanges

from nasdaqapi import fetch_all_exchanges, get_unique_symbols

# Get all tickers from NASDAQ, NYSE, and AMEX
tickers = fetch_all_exchanges()
symbols = get_unique_symbols(tickers)

print(f"Total symbols: {len(symbols)}")

Data Structure

The normalized data follows this structure:

{
    "metadata": {
        "symbol": "AAPL",
        "company_name": "Apple Inc. Common Stock",
        "exchange": "NASDAQ-GS",
        "stock_type": "Common Stock",
        ...
    },
    "quote": {
        "price": 277.90,
        "change": 0.93,
        "change_percent": 0.0034,
        "volume": 55881,
        ...
    },
    "key_metrics": {
        "pe_ratio": 45.26,
        "week_52_high": 280.38,
        "week_52_low": 169.21,
        "dividend_yield": 0.0038,
        "shares_outstanding": 14776000000,
        ...
    },
    "dividends": {
        "summary": {...},
        "history": [...]
    },
    "financials": {
        "annual": {
            "income_statement": [...],
            "balance_sheet": [...],
            "cash_flow": [...],
            "financial_ratios": [...]
        },
        "quarterly": {...}
    },
    "ownership": {
        "institutional": {
            "summary": {...},
            "top_holders": [...]
        },
        "insider_trades": [...]
    },
    "analyst_data": {...},
    "short_interest": {...},
    "sec_filings": [...],
    "news": {
        "press_releases": [...],
        "articles": [...]
    },
    "historical_prices": {
        "daily": [...],
        "period_5d": [...],
        "period_1m": [...]
    }
}

Requirements

• Python 3.8+
• requests >= 2.31.0

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Disclaimer

This library fetches data from NASDAQ's public API. Please review NASDAQ's terms of service and ensure your usage complies with their policies. This library is not affiliated with or endorsed by NASDAQ.

Author

Created with ❤️ for the financial data community