# QuantConnect/Lean

Lean Algorithmic Trading Engine by QuantConnect (Python, C#)

Repository: https://github.com/QuantConnect/Lean
Canonical: https://ross.abutalabs.com/products/lean
Homepage: https://lean.io
Language: C#
License: Apache-2.0
License Family: permissive
Topics: c-sharp, algorithmic-trading-engine, quantconnect, lean-engine, finance, algorithm, options, trading-algorithms, trading-platform, trading-strategies, trading-bot, python, stock-indicators, forex, trading
Last push: 2026-08-26T23:02:36+00:00

## Health v2 (maintenance only)
Score: 67/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 8, longevity 100
- inputs: {"age_days": 4296, "days_push": 7, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 21363, forks 5195 (observed 2026-08-28T04:11:31.617619+00:00)

## What it is
LEAN is an open-source, event-driven algorithmic trading engine by QuantConnect supporting backtesting, optimization, and live trading across equities, options, futures, forex, and crypto. It is written in C# with Python support, features a modular pluggable architecture, 100+ technical indicators, and brokerage/data-provider integrations.

## Use cases
- backtest a trading strategy on historical market data
- deploy a live trading bot to Interactive Brokers or Binance
- build a quantitative trading algorithm in Python or C#
- optimize strategy parameters before going live
- simulate slippage, fees, and margin for a portfolio
- test options and futures strategies with corporate action handling

## When to choose
- you need a professional-grade backtesting and live-trading engine with many brokerage integrations
- you want to write strategies in Python or C# with a large indicator library
- you need multi-asset-class support including options, futures, forex, and crypto

## When to avoid
- you only need simple charting or market data analysis without order execution
- you want a lightweight script rather than a full engine with Docker/CLI tooling
- you need a no-code trading platform

## Facets
- artifact type: framework
- maturity: stable
- function: trading, simulation, sdk, cli, data-science
- domain: fintech
- platform: cross-platform, python, dotnet, cli
- tags: backtesting, live-trading, quant, technical-indicators, brokerage-integration, event-driven, options, forex, crypto, algorithmic-trading, quantitative-finance, automation, docker

## Member repositories
- QuantConnect/Lean (main) score 67

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:31.617619+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T16:58:08.016521+00:00, confidence not recorded.
  - readme: https://github.com/QuantConnect/Lean (fetched 2026-08-28T04:11:31.617619+00:00, sha 74c4d256c208)
  - homepage: https://lean.io (fetched 2026-08-29T07:57:01.508917+00:00, sha b1a049b71022)
  - site_page: https://www.lean.io/docs/v2/lean-cli (fetched 2026-08-29T07:57:01.518524+00:00, sha d2788fe843ba)
  - site_page: https://www.lean.io/docs/v2/lean-cli/key-concepts/getting-started (fetched 2026-08-29T07:57:01.520612+00:00, sha eefe03b27f4a)
  - site_page: https://www.lean.io/docs (fetched 2026-08-29T07:57:01.522502+00:00, sha 73d80ea63b46)
  - site_page: https://www.lean.io/about (fetched 2026-08-29T07:57:01.524579+00:00, sha 2273e219ddc8)
  - site_page: https://www.lean.io/pricing (fetched 2026-08-29T07:57:01.526739+00:00, sha 2273e219ddc8)
- Data as of 2026-08-30T08:39:29.467469+00:00.