Athenarabetaathenara:~$ registry inspect architectures/finrl-meta
● finrl-meta — external
FinRL-Meta
The AI4Finance market-environment and data layer for financial reinforcement learning, with gym-style trading environments across equities, crypto, FX and futures plus 15 data-source processors.
added 2026-08-17 · MIT · external
$ git clone https://github.com/AI4Finance-Foundation/FinRL-Meta $ cd FinRL-Meta $ pip install -r requirements.txt $ python main.py --mode=train
requires python >= 3.6
you also need: API keys or accounts for most data sources (Yahoo Finance, CCXT and Binance work without one)
finrl-meta ├─ market environments ├─ data processors └─ benchmarks
FinRL-Meta supplies the environment and data half of the reinforcement-learning trading loop. The repository ships eight gym-style environment families — crypto trading, execution optimizing, futures trading, FX trading, market impact, portfolio allocation, portfolio optimization and stock trading — and 15 data-source processors (akshare, alpaca, alphavantage, baostock, binance, ccxt, fx, iexcloud, joinquant, quandl, quantconnect, ricequant, tushare, wrds, yahoofinance). It is deliberately agnostic about the learning library: the README’s plug-and-play section names ElegantRL, Stable-Baselines3 and RLlib, and the stock-trading folder carries matching paper-trading environments for each. The work was published in the NeurIPS 2022 Datasets and Benchmarks Track (proceedings).
Development continues — the newest commit, on 2026-04-02, merged impact-aware market environments —
but the packaging lags the code: PyPI’s newest finrl-meta release is 0.3.6 from 2023-02-07 while
setup.py declares 0.3.7, so pip install finrl-meta fetches a roughly three-year-old snapshot and
the git checkout is the real install path. The README now steers production users to a separate
FinRL-Trading repository and positions FinRL-Meta as the research environment and benchmark layer.
Two things to know before relying on it. Most of the listed data sources — Alpaca, JoinQuant, RiceQuant, Tushare, WRDS, IEXCloud, QuantConnect — need accounts or API keys; only Yahoo Finance, CCXT and Binance are usable key-free. And while the code is MIT (LICENSE reads “Copyright (c) 2024 AI4Finance Foundation Inc.”), the README adds a trademark notice outside that text: FinRL® is a registered trademark and the license grants no rights to the FinRL name or logo. The README’s citation block also attributes a 2024 follow-up paper to the journal “Machine Learning - Nature”, an attribution arXiv:2304.13174 does not carry — treat it as unverified.
trading [●●●··] moderate ai [●●●●·] advanced programming [●●●··] moderate setup [●●●●·] advanced
athenara:~$