How is Market Data deployed?

Market Data is designed for easy deployment. You can run it locally using a uvicorn server or deploy it effortlessly via Docker containers.

What types of financial data can I fetch?

You can fetch OHLCV (Open, High, Low, Close, Volume) data, full option chains, Greek values (e.g., Delta, Gamma, Theta), and basic corporate events data.

How does Market Data assist with LLM and AI training?

It includes a specialized tool for assembling aligned and cached financial training datasets, significantly streamlining the data preparation process for LLMs and other AI models.

Can I integrate my preferred financial data provider?

Yes, Market Data features a vendor-pluggable data provider architecture. You can implement a simple DataProvider interface to swap in sources like Polygon or IEX, with yfinance serving as the default out-of-the-box provider.

Market Data

Name: Market Data
Author: pishnuke

0•

Exposes financial market data endpoints for LLMs and other clients, enabling fetching of OHLCV, option chains, Greeks, and corporate events, and facilitating training dataset assembly.

Market Data is a FastAPI server designed as a deployable, minimal, and vendor-pluggable service for accessing comprehensive financial market information. It provides robust endpoints for fetching critical data points such as OHLCV (Open, High, Low, Close, Volume), option chains, Greeks, and basic corporate events. Furthermore, it assists in assembling tailored training datasets with alignment and caching capabilities, making it ideal for LLM-driven applications, quantitative analysis, or any client requiring reliable market data. It comes with `yfinance` as a default provider, allowing it to run out-of-the-box, and can be easily extended to support other providers like Polygon or IEX.

主な機能

01FastAPI server providing financial market data

02Vendor-pluggable data provider architecture (e.g., yfinance, Polygon, IEX)

03Endpoints for OHLCV, option chains, Greeks, and corporate events

04Tool for assembling aligned and cached training datasets

05Easy deployment via Docker or local uvicorn server

060 GitHub stars

ユースケース

01Powering LLM applications with real-time and historical financial market data

02Building custom datasets for quantitative trading strategies or machine learning models

03Integrating a standardized market data API into various client applications