Alpha Vantage API Integration
Financial data API providing stocks, forex, crypto, technical indicators, fundamental data, economic indicators, and AI-powered news sentiment analysis.
Quick Start
Authentication
# Environment variable (recommended)
export ALPHAVANTAGE_API_KEY="your_api_key"
# Or in .env file
ALPHAVANTAGE_API_KEY=your_api_key
Basic Usage (Python)
import requests
import os
API_KEY = os.getenv("ALPHAVANTAGE_API_KEY")
BASE_URL = "https://www.alphavantage.co/query"
def get_quote(symbol: str) -> dict:
"""Get real-time quote for a symbol."""
response = requests.get(BASE_URL, params={
"function": "GLOBAL_QUOTE",
"symbol": symbol,
"apikey": API_KEY
})
return response.json().get("Global Quote", {})
# Example
quote = get_quote("AAPL")
print(f"AAPL: ${quote['05. price']} ({quote['10. change percent']})")
Using Python Package
from alpha_vantage.timeseries import TimeSeries
from alpha_vantage.techindicators import TechIndicators
# Time series data
ts = TimeSeries(key=API_KEY, output_format='pandas')
data, meta = ts.get_daily(symbol='AAPL', outputsize='compact')
# Technical indicators
ti = TechIndicators(key=API_KEY, output_format='pandas')
rsi, meta = ti.get_rsi(symbol='AAPL', interval='daily', time_period=14)
API Functions Reference
Stock Time Series
| Function | Description | Free |
|---|
TIME_SERIES_INTRADAY | 1-60min intervals | ✅ |
TIME_SERIES_DAILY | Daily OHLCV | ✅ |
TIME_SERIES_DAILY_ADJUSTED | With splits/dividends | ⚠️ Premium |
TIME_SERIES_WEEKLY | Weekly OHLCV | ✅ |
TIME_SERIES_MONTHLY | Monthly OHLCV | ✅ |
GLOBAL_QUOTE | Latest quote | ✅ |
SYMBOL_SEARCH | Search symbols | ✅ |
Fundamental Data
| Function | Description | Free |
|---|
OVERVIEW | Company overview | ✅ |
INCOME_STATEMENT | Income statements | ✅ |
BALANCE_SHEET | Balance sheets | ✅ |
CASH_FLOW | Cash flow statements | ✅ |
EARNINGS | Earnings history | ✅ |
EARNINGS_CALENDAR | Upcoming earnings | ✅ |
IPO_CALENDAR | Upcoming IPOs | ✅ |
Forex
| Function | Description | Free |
|---|
CURRENCY_EXCHANGE_RATE | Real-time rate | ✅ |
FX_INTRADAY | Intraday forex | ✅ |
FX_DAILY | Daily forex | ✅ |
FX_WEEKLY | Weekly forex | ✅ |
FX_MONTHLY | Monthly forex | ✅ |
Cryptocurrency
| Function | Description | Free |
|---|
CURRENCY_EXCHANGE_RATE | Crypto rate | ✅ |
DIGITAL_CURRENCY_DAILY | Daily crypto | ✅ |
DIGITAL_CURRENCY_WEEKLY | Weekly crypto | ✅ |
DIGITAL_CURRENCY_MONTHLY | Monthly crypto | ✅ |
Technical Indicators (50+)
| Category | Indicators |
|---|
| Trend | SMA, EMA, WMA, DEMA, TEMA, KAMA, MAMA, T3, TRIMA |
| Momentum | RSI, MACD, STOCH, WILLR, ADX, CCI, MFI, ROC, AROON, MOM |
| Volatility | BBANDS, ATR, NATR, TRANGE |
| Volume | OBV, AD, ADOSC |
| Hilbert | HT_TRENDLINE, HT_SINE, HT_PHASOR, etc. |
Economic Indicators
| Function | Description | Free |
|---|
REAL_GDP | US GDP | ✅ |
CPI | Consumer Price Index | ✅ |
INFLATION | Inflation rate | ✅ |
UNEMPLOYMENT | Unemployment rate | ✅ |
FEDERAL_FUNDS_RATE | Fed funds rate | ✅ |
TREASURY_YIELD | Treasury yields | ✅ |
Alpha Intelligence
| Function | Description | Free |
|---|
NEWS_SENTIMENT | AI sentiment analysis | ✅ |
TOP_GAINERS_LOSERS | Market movers | ✅ |
INSIDER_TRANSACTIONS | Insider trades | ⚠️ Premium |
ANALYTICS_FIXED_WINDOW | Analytics | ⚠️ Premium |
Rate Limits
| Tier | Daily | Per Minute | Price |
|---|
| Free | 25 | 5 | $0 |
| Premium | Unlimited | 75-1,200 | $49.99-$249.99/mo |
Important: Rate limits are IP-based, not key-based.
Common Tasks
Task: Get Daily Stock Data
def get_daily_data(symbol: str, full: bool = False) -> dict:
"""Get daily OHLCV data."""
response = requests.get(BASE_URL, params={
"function": "TIME_SERIES_DAILY",
"symbol": symbol,
"outputsize": "full" if full else "compact",
"apikey": API_KEY
})
return response.json().get("Time Series (Daily)", {})
# Example
data = get_daily_data("AAPL")
latest = list(data.items())[0]
print(f"{latest[0]}: Close ${latest[1]['4. close']}")
Task: Get Technical Indicator
def get_rsi(symbol: str, period: int = 14) -> dict:
"""Get RSI indicator values."""
response = requests.get(BASE_URL, params={
"function": "RSI",
"symbol": symbol,
"interval": "daily",
"time_period": period,
"series_type": "close",
"apikey": API_KEY
})
return response.json().get("Technical Analysis: RSI", {})
# Example
rsi = get_rsi("AAPL")
latest_rsi = list(rsi.values())[0]["RSI"]
print(f"AAPL RSI(14): {latest_rsi}")
Task: Get Company Overview
def get_company_overview(symbol: str) -> dict:
"""Get comprehensive company information."""
response = requests.get(BASE_URL, params={
"function": "OVERVIEW",
"symbol": symbol,
"apikey": API_KEY
})
data = response.json()
return {
"name": data.get("Name"),
"description": data.get("Description"),
"sector": data.get("Sector"),
"industry": data.get("Industry"),
"market_cap": data.get("MarketCapitalization"),
"pe_ratio": data.get("PERatio"),
"dividend_yield": data.get("DividendYield"),
"eps": data.get("EPS"),
"52_week_high": data.get("52WeekHigh"),
"52_week_low": data.get("52WeekLow"),
"beta": data.get("Beta")
}
Task: Get Forex Rate
def get_forex_rate(from_currency: str, to_currency: str) -> dict:
"""Get currency exchange rate."""
response = requests.get(BASE_URL, params={
"function": "CURRENCY_EXCHANGE_RATE",
"from_currency": from_currency,
"to_currency": to_currency,
"apikey": API_KEY
})
return response.json().get("Realtime Currency Exchange Rate", {})
# Example
rate = get_forex_rate("USD", "EUR")
print(f"USD/EUR: {rate['5. Exchange Rate']}")
Task: Get Crypto Price
def get_crypto_price(symbol: str, market: str = "USD") -> dict:
"""Get cryptocurrency price."""
response = requests.get(BASE_URL, params={
"function": "CURRENCY_EXCHANGE_RATE",
"from_currency": symbol,
"to_currency": market,
"apikey": API_KEY
})
data = response.json().get("Realtime Currency Exchange Rate", {})
return {
"symbol": symbol,
"price": data.get("5. Exchange Rate"),
"last_updated": data.get("6. Last Refreshed")
}
# Example
btc = get_crypto_price("BTC")
print(f"BTC: ${float(btc['price']):,.2f}")
Task: Get News Sentiment
def get_news_sentiment(tickers: str = None, topics: str = None) -> list:
"""Get AI-powered news sentiment analysis."""
params = {
"function": "NEWS_SENTIMENT",
"apikey": API_KEY
}
if tickers:
params["tickers"] = tickers
if topics:
params["topics"] = topics
response = requests.get(BASE_URL, params=params)
return response.json().get("feed", [])
# Example
news = get_news_sentiment(tickers="AAPL")
for article in news[:3]:
sentiment = article.get("overall_sentiment_label", "N/A")
print(f"{article['title'][:50]}... [{sentiment}]")
Task: Get Economic Indicators
def get_economic_indicator(indicator: str) -> dict:
"""Get US economic indicator data."""
response = requests.get(BASE_URL, params={
"function": indicator,
"apikey": API_KEY
})
return response.json()
# Examples
gdp = get_economic_indicator("REAL_GDP")
cpi = get_economic_indicator("CPI")
unemployment = get_economic_indicator("UNEMPLOYMENT")
fed_rate = get_economic_indicator("FEDERAL_FUNDS_RATE")
Task: Get Earnings Calendar
def get_earnings_calendar(horizon: str = "3month") -> list:
"""Get upcoming earnings releases."""
import csv
from io import StringIO
response = requests.get(BASE_URL, params={
"function": "EARNINGS_CALENDAR",
"horizon": horizon, # 3month, 6month, 12month
"apikey": API_KEY
})
# Returns CSV format
reader = csv.DictReader(StringIO(response.text))
return list(reader)
# Example
earnings = get_earnings_calendar()
for e in earnings[:5]:
print(f"{e['symbol']}: {e['reportDate']}")
Error Handling
def safe_api_call(params: dict) -> dict:
"""Make API call with error handling."""
params["apikey"] = API_KEY
try:
response = requests.get(BASE_URL, params=params)
data = response.json()
# Check for rate limit
if "Note" in data:
print(f"Rate limit: {data['Note']}")
return {}
# Check for error message
if "Error Message" in data:
print(f"API Error: {data['Error Message']}")
return {}
# Check for information message (often rate limit)
if "Information" in data:
print(f"Info: {data['Information']}")
return {}
return data
except Exception as e:
print(f"Request error: {e}")
return {}
Free vs Premium Features
Free Tier Includes
- 25 requests per day
- 5 requests per minute
- Historical time series (20+ years)
- 50+ technical indicators
- Fundamental data
- Forex and crypto
- Economic indicators
- News sentiment
Premium Required
- Unlimited daily requests
- Adjusted time series
- Realtime US market data
- 15-minute delayed data
- Insider transactions
- Advanced analytics
- Priority support
Best Practices
- Cache responses - Data doesn't change frequently
- Use compact outputsize - Unless you need full history
- Batch requests wisely - 25/day limit is strict
- Handle rate limits - Check for "Note" key in response
- Use pandas output - With alpha_vantage package
- Store historical data - Avoid re-fetching same data
Installation
# Official Python wrapper
pip install alpha_vantage pandas
# For async support
pip install aiohttp
Usage with Pandas
from alpha_vantage.timeseries import TimeSeries
from alpha_vantage.techindicators import TechIndicators
import pandas as pd
# Initialize with pandas output
ts = TimeSeries(key=API_KEY, output_format='pandas')
ti = TechIndicators(key=API_KEY, output_format='pandas')
# Get daily data
data, meta = ts.get_daily(symbol='AAPL', outputsize='compact')
# Get indicators
sma, _ = ti.get_sma(symbol='AAPL', interval='daily', time_period=20)
rsi, _ = ti.get_rsi(symbol='AAPL', interval='daily', time_period=14)
# Combine
analysis = data.join([sma, rsi])
Related Skills
finnhub-api - Real-time quotes and news
twelvedata-api - More indicators, better rate limits
fmp-api - Fundamental analysis focus
References