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Tutorial 4: Connecting to a Market Data API

Learn how to fetch fresh OHLCV data from a public API, process it into a DataFrame, and analyze it with PyTechnicalIndicators.
This workflow enables automated, up-to-date, and repeatable research pipelines.

Series so far:

🎯 Goal

  • Fetch OHLCV (Open, High, Low, Close, Volume) data from a free market data API
  • Parse JSON into a pandas DataFrame
  • Clean and align the data for use with PyTechnicalIndicators
  • Run your existing indicator pipeline on fresh data

📦 Prerequisites

  • Python 3.10+
  • pandas
  • requests (for HTTP queries)
  • PyTechnicalIndicators
pip install pandas requests pytechnicalindicators

🔍 Using a Free Market Data API (Binance)

We'll use Binance's public API, which provides free cryptocurrency OHLCV data with no API key required.

Docs: Binance API - Kline/Candlestick Data

Example endpoint for daily candles of BTCUSDT:

https://api.binance.com/api/v3/klines?symbol=BTCUSDT&interval=1d&limit=365
  • Replace BTCUSDT with any supported crypto symbol.
  • interval can be 1d (daily), 1h (hourly), etc.
  • limit controls how many bars.

🧑‍💻 Fetching Data from marketdata.app

import requests
import pandas as pd

def fetch_marketdata_ohlcv(symbol="BTCUSDT", interval="1d", limit=365):
    url = "https://api.binance.com/api/v3/klines"
    params = {"symbol": symbol, "interval": interval, "limit": limit}
    resp = requests.get(url, params=params)
    resp.raise_for_status()
    data = resp.json()
    # Binance returns a list of lists:
    # [Open time, Open, High, Low, Close, Volume, Close time, ...]
    df = pd.DataFrame(data, columns=[
        "OpenTime", "Open", "High", "Low", "Close", "Volume",
        "CloseTime", "QuoteAssetVolume", "NumTrades", "TakerBuyBase", "TakerBuyQuote", "Ignore"
    ])
    df["Date"] = pd.to_datetime(df["OpenTime"], unit="ms")
    cols = ["Date", "Open", "High", "Low", "Close", "Volume"]
    df = df[cols].astype({"Open": float, "High": float, "Low": float, "Close": float, "Volume": float})
    df = df.sort_values("Date").reset_index(drop=True)
    return df

# Example usage
df = fetch_marketdata_ohlcv(symbol="BTCUSDT", interval="1d", limit=365)
print(df.head())

⚙️ Running Indicators on API Data

You can now pass the df to the indicators just as we did in Tutorial 1.

📊 Visualization

Use Plotly as shown in Tutorial 2 to quickly visualize live data with overlays:

API Dashboard

🔄 Extending Further

  • Loop over multiple symbols and concatenate results for batch analysis.
  • Use your custom indicator pipelines from previous tutorials on this fresh data.
  • Add logic to check for new bars and only update as needed.
  • Save or visualize your results for reporting or algorithmic research.

🧩 Putting It All Together

A runnable example of the full code can be found in 04_api_connection

🛡️ Disclaimer

Always observe API rate limits and terms of use.
This example is for educational purposes; for production, add robust error handling and logging.

Happy fetching! 🦀🐍🌐