{"repo":"OpenByteInc/QuantDinger","free":true,"listed":false,"github":"https://github.com/OpenByteInc/QuantDinger","clone":"git clone https://github.com/OpenByteInc/QuantDinger.git","description":"AI quantitative trading platform for crypto, stocks, and forex with backtesting, live trading, market data, and multi-agent research.vibe-trading ,trading-agents,ai-trader,ai-trading","language":"Python","stars":10738,"topics":["agent","ai","alpaca","backtesting","binance","coinbase","crypto","exchange","finance","fintech","forex","mcp-server","python","quant","quantitative-finance","saas","stocks","strategy","trade","trading-toolkit"],"license":"Apache-2.0","category":"quant_trading_os","readme_excerpt":"
\n \n \"QuantDinger\n \n\n

QuantDinger

\n

Open-source AI Trading OS

\n

Turn trading ideas into Python strategies, backtests, paper trading, live execution, and monitoring — all in one self-hosted stack.

\n

QuantDinger is a product of Open Byte Inc.

\n

AI research → Strategy code → Backtest → Paper/Live execution → Monitoring

\n\n

\n English\n ·\n 简体中文\n ·\n API\n ·\n AI Agents & MCP\n

\n\n

\n Live App\n ·\n Website\n ·\n Video Demo\n ·\n Official Support Email\n

\n\n

\n \"Telegram\"\n \"Discord\"\n \"YouTube\"\n \"X\n

\n\n

\n \"Apache\n \"Python\n \"PostgreSQL\n \"Redis\n \"Docker\n \"Latest\n

\n\n

SUPPORTED BY

\n

\n \n \n \n \"Atlas\n \n \n     \n \n \n \n \"Amazon\n \n \n

\n
\n\n> QuantDinger can submit real orders when live trading is explicitly enabled.\n> Start with paper trading, use restricted API keys, and review the risk and\n> compliance requirements for your jurisdiction. This project does not provide\n> investment advice.\n\n## What QuantDinger is\n\nQuantDinger is an **open-source AI Trading OS** for independent traders, Python\nstrategy authors, and small teams. Its local-first, self-hosted design keeps\nmarket data, strategy code, broker credentials, and deployment under the\noperator's control.\n\nThe project combines:\n\n- multi-provider AI market research and analysis;\n- Python indicators and Strategy API V2 development;\n- server-side backtesting and experiment workflows;\n- paper and live execution across crypto exchanges and traditional brokers;\n- web, mobile H5, human API, Agent Gateway, and MCP access;\n- PostgreSQL-backed state, durable workers, audit logs, and optional monitoring.\n\nIt is not a black-box signal service. Strategy code, risk settings, credentials,\nand deployment remain under the operator's control.\n\n## What changed in v5\n\nThe v5 backend is organized around explicit runtime and operational boundaries:\n\n- the HTTP API no longer owns long-running trading or scheduler loops;\n- trading, scheduling, Celery jobs, and migrations run as separate processes;\n- Celery handles finite, retryable work while long-lived strategy runtimes stay\n in the trading worker;\n- cache Redis and durable job Redis use separate instances and eviction policies;\n- high-risk API contracts are represented in OpenAPI and protected by tests;\n- JSON logs, request IDs, Prometheus metrics, dashboards, and alert rules are\n available through an optional observability overlay;\n- the production overlay runs backend processes as a non-root user with a\n read-only root filesystem, dropped capabilities, and resource limits;\n- CI checks syntax, lint, tests, release gates, Compose files, dependencies,\n source security, secrets, API compatibility, version drift, and text encoding.\n\nThe source version is declared in [`VERSION`](VERSION). Git release tags use the\nsame semantic version with a leading `v`, for example `v5.0.1`.\n\n## Architecture\n\n

\n \"QuantDinger\n

\n\n

The editable source is available as architecture-v5.svg.

\n\nThe diagram above shows the complete product and process architecture. The\nruntime topology below focuses on container-to-container ownership and data flow.\n\n```mermaid\nflowchart TB\n C[\"Web / Mobile / API / MCP clients\"]\n FE[\"Nginx frontend services\"]\n API[\"Flask + Gunicorn API\"]\n PG[(\"PostgreSQL\")]\n CACHE[(\"Redis cache\")]\n JOBS[(\"Redis jobs\")]\n TW[\"Trading worker\"]\n SW[\"Scheduler worker\"]\n CW[\"Celery worker\"]\n BEAT[\"Celery beat\"]\n PROM[\"Prometheus\"]\n GRAF[\"Grafana\"]\n ALERT[\"Alertmanager\"]\n\n C --> FE --> API\n API --> PG\n API --> CACHE\n API -->|\"durable commands\"| PG\n TW -->|\"leases, orders, heartbeats\"| PG\n SW -->|\"schedules, monitoring, heartbeats\"| PG\n API -->|\"finite async jobs\"| JOBS\n BEAT --> JOBS --> CW\n CW --> PG\n API -. metrics .-> PROM\n PG -. exporter .-> PROM\n CACHE -. exporter .-> PROM\n JOBS -. exporter .-> PROM\n PROM --> GRAF\n PROM --> ALERT\n```\n\nOne backend image is reused by several containers with different commands:\n\n| Process | Responsibility |\n| --- | --- |\n| `migration` | Applies the database schema and exits before application services start. |\n| `backend` | Handles HTTP, authentication, validation, and durable command submission. |\n| `trading-worker` | Owns strategy runtimes, pending orders, broker sessions, and reconciliation. |\n| `scheduler-worker` | Runs portfolio, deployment, payment, and signal schedules. |\n| `celery-worker` | Executes finite AI, backtest, experiment, report, and maintenance jobs. |\n| `celery-beat` | Dispatches periodic Celery tasks. |\n\nSee [Backend process roles](docs/architecture/PROCESS_ROLES_AND_TASKS.md),\n[architecture](docs/architecture/ARCHITECTURE.md), and\n[concurrency model](docs/architecture/CONCURRENCY_MODEL.md) for the ownership rules.\n\n## Quick start\n\n### Option A: prebuilt images\n\nPrerequisites: Docker with Compose v2. Node.js and a local Python environment are\nnot required.\n\nLinux or macOS:\n\n```bash\ncurl -fsSL https://raw.githubusercontent.com/OpenByteInc/QuantDinger/main/install.sh | bash\n```\n\nWindows PowerShell:\n\n```powershell\nirm https://raw.githubusercontent.com/OpenByteInc/QuantDinger/main/install.ps1 | iex\n```\n\nThe installer asks for the initial administrator credentials, generates the\nrequired secrets, downloads the GHCR Compose stack, and starts it.\n\nOpen:\n\n- Web: \n- Mobile H5: \n- API health: \n\n### Docker administrator and settings notes\n\nDetailed guides: [English](docs/deployment/ADMIN_AND_SETTINGS_TROUBLESHOOTING_EN.md) |\n[中文](docs/deployment/ADMIN_AND_SETTINGS_TROUBLESHOOTING_CN.md)\n\nOn a fresh database, the backend creates the initial administrator from\n`ADMIN_USER`, `ADMIN_PASSWORD`, and optional `ADMIN_EMAIL`. Passwords are stored\nas hashes, never as plaintext. An existing PostgreSQL volume is not overwritten:\nthe backend only replaces the untouched legacy `quantdinger` / `123456`\nadministrator when a non-default administrator is explicitly configured. It\nnever overwrites an account whose password was already changed, and it refuses\nto promote an existing account that already uses the requested username.\n\nManual Docker deployments retain `quantdinger` / `123456` only for backward\ncompatibility when the administrator variables are left at their defaults. This\ncredential is not suitable for an internet-facing deployment; change it before\nfirst start or immediately after the first login. The one-command installer does\nnot accept `123456` as the chosen password.\n\nThe Settings UI writes runtime configuration to `/app/.env`. In the GHCR stack\nthis is the host `backend.env`; in a source deployment it is\n`backend_api_python/.env`. Current backend images automatically give runtime UID\n`10001` ownership and keep mode `600`. Do not use `chmod 755` or recursive `777`:\nthese files contain passwords and API keys, and `755` still does not grant write\naccess to UID `10001` when root owns the file.\n\nVerify write access with:\n\n```bash\ndocker 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