yfinance rate limited: migrating Python price pulls to a keyed market data API
yfinance rate limited or throwing Too Many Requests? A call-for-call map to move daily history, intraday bars, and latest-price pulls to a keyed API in Python.
Category · Developer Tutorials
Developer Tutorials
Practical guides for using the SiftingIO API and WebSocket streams.
Latest in Developer Tutorials
Bid ask spread: how to read a quote and flag a wide or stale one in code
How to read bid and ask from a quote snapshot, compute the bid ask spread in basis points, and flag wide or stale quotes in Python before users see them.
Why financial platforms need a clear market data methodology
A market data methodology explains where a price comes from and how it is validated. Here is why that documentation matters and how to read it in an API.
Building Financial AI Agents With Real-Time and Historical Market Data
Why financial AI agents need structured market data APIs instead of web search, and how to wire prices, OHLCV, and fundamentals in as agent tools.
What is OHLCV data? Bars, candles, and how providers build them
What OHLCV data is, how bars are built from ticks, why two providers disagree on the same candle, adjusted vs unadjusted bars, and how to pull bars via API.
How to Get Real-Time Forex Prices in Python
Get real-time forex prices in Python: a requests call for a snapshot, a websockets feed for live updates, the official siftingio SDK with sync and async clients, and buffering ticks into a pandas DataFrame.
REST vs WebSocket for Real-Time Market Data: When to Use Each
REST or WebSocket for live market data? A plain guide to how each works, when to pull on demand versus stream, why fast polling scales badly, and how to use both together.