Data API

Alpha Vantage API Review for Developers

Item: Alpha Vantage API
Author: CodeForFinance

Alpha Vantage provides a free REST API for financial data including stocks, forex, crypto, and pre-calculated technical indicators. It is one of the few legitimate free APIs with a proper API key system, documentation, and structured JSON responses. The free tier gives you 25 requests per day, while paid plans unlock more.

Pricing

Free$0/month

✓ 25 requests/day
✓ All endpoints
✓ JSON/CSV output
✓ Technical indicators
✓ Fundamental data

Premium$49.99/month

✓ 75 requests/minute
✓ All endpoints
✓ Priority support
✓ Higher rate limits

EnterpriseCustom

✓ Unlimited requests
✓ Dedicated support
✓ SLA
✓ Custom endpoints

Pros

+ Legitimate free tier with API key
+ Pre-calculated technical indicators (SMA, RSI, MACD, etc.)
+ Covers stocks, forex, and crypto
+ Clean JSON response format
+ Good documentation

Cons

- Free tier limited to 25 requests/day (very restrictive)
- Historical data limited on free tier
- Response times can be slow
- Some data quality issues with fundamentals
- No websocket/streaming support

Who Is It For?

Alpha Vantage is ideal for students, hobbyists, and developers building proof-of-concepts. The free tier is too limited for anything production-grade. The paid tier at $50/month is reasonable for small projects that need reliable data.

Code Example

import requests
import pandas as pd

API_KEY = "YOUR_FREE_KEY"  # Get at alphavantage.co
BASE_URL = "https://www.alphavantage.co/query"

# Daily stock prices
def get_daily_prices(symbol: str) -> pd.DataFrame:
    params = {
        "function": "TIME_SERIES_DAILY",
        "symbol": symbol,
        "outputsize": "compact",  # Last 100 days
        "apikey": API_KEY
    }
    r = requests.get(BASE_URL, params=params)
    data = r.json().get("Time Series (Daily)", {})
    df = pd.DataFrame(data).T
    df.columns = ["open", "high", "low", "close", "volume"]
    df = df.astype(float)
    df.index = pd.to_datetime(df.index)
    return df.sort_index()

# Technical indicator (RSI)
def get_rsi(symbol: str, period: int = 14) -> pd.DataFrame:
    params = {
        "function": "RSI",
        "symbol": symbol,
        "interval": "daily",
        "time_period": period,
        "series_type": "close",
        "apikey": API_KEY
    }
    r = requests.get(BASE_URL, params=params)
    data = r.json().get("Technical Analysis: RSI", {})
    df = pd.DataFrame(data).T
    df.columns = ["RSI"]
    df = df.astype(float)
    return df.sort_index()

# Company overview (fundamentals)
def get_fundamentals(symbol: str) -> dict:
    params = {
        "function": "OVERVIEW",
        "symbol": symbol,
        "apikey": API_KEY
    }
    r = requests.get(BASE_URL, params=params)
    return r.json()

prices = get_daily_prices("AAPL")
print(prices.tail())

Alternatives

Yahoo Finance (yfinance)Polygon.ioTwelve Data