{"data":{"slug":"brokermr810-quantdinger","name":"QuantDinger","tagline":"AI quantitative trading platform for finance instruments with backtesting and live trading capabilities","github_url":"https://github.com/brokermr810/QuantDinger","owner":"brokermr810","repo":"QuantDinger","owner_avatar_url":"https://avatars.githubusercontent.com/u/220133043?v=4","primary_language":"Python","stars":10841,"forks":2290,"topics":["agent","ai","alpaca","backtesting","binance","coinbase","crypto","exchange","finance","fintech","forex","mcp-server","python","quant","quantitative-finance","saas","stocks","strategy","trade","trading-toolkit"],"archived":false,"github_pushed_at":"2026-08-19T09:13:35+00:00","maintenance_label":"Very active","stars_delta_30d":1055,"url":"https://www.graphcanon.com/tools/brokermr810-quantdinger","markdown_url":"https://www.graphcanon.com/tools/brokermr810-quantdinger.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/brokermr810-quantdinger","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=brokermr810-quantdinger","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","homepage_url":"https://ai.quantdinger.com","license":"Apache-2.0","open_issues":52,"watchers":69,"ai_summary":"QuantDinger is an AI-powered quantitative trading platform designed for automated trading in crypto, stocks, and forex markets. It features support for multiple financial exchanges including Binance and Coinbase, along with robust backtesting tools and the capability to deploy custom trading agents.","readme_excerpt":"### 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 compose exec -u 10001:10001 -T backend \\\n  sh -c 'test -w /app/.env && echo writable=yes || echo writable=no'\n```\n\nThe hardened production override intentionally mounts `/app/.env` read-only.\nWhen using `docker-compose.production.yml`, manage configuration on the host and\nrecreate the services instead of saving it from the Settings UI. See the\n[English guide](docs/deployment/ADMIN_AND_SETTINGS_TROUBLESHOOTING_EN.md) or\n[中文指南](docs/deployment/ADMIN_AND_SETTINGS_TROUBLESHOOTING_CN.md) for\nlegacy-image recovery and rootless/NFS notes.\n\n---\n\n## Production deployment\n\nValidate secrets before starting a production stack:\n\n```bash\npython backend_api_python/scripts/check_production_config.py \\\n  --env-file .env \\\n  --env-file backend_api_python/.env\n```\n\nStart the hardened runtime with optional observability:\n\n```bash\ndocker compose \\\n  -f docker-compose.yml \\\n  -f docker-compose.production.yml \\\n  -f docker-compose.observability.yml \\\n  up -d --build\n```\n\nOmit `docker-compose.observability.yml` when the host is resource-constrained or\nmonitoring is provided externally.\n\nProduction rules:\n\n- expose only a TLS reverse proxy on ports 80/443;\n- keep PostgreSQL, both Redis instances, Prometheus, Grafana, and Alertmanager\n  off the public internet;\n- do not deploy with example passwords or empty encryption keys;\n- back up PostgreSQL and the durable `redis-jobs` volume;\n- keep cache Redis disposable and never use it as the Celery broker;\n- review worker health and application readiness after every deployment.\n\nThe full checklist is in [Production hardening](docs/deployment/PRODUCTION_HARDENING.md).\n\n---\n\n## License and commercial terms\n\n- Backend source code is licensed under [Apache License 2.0](LICENSE).\n- QuantDinger is a product of **Open Byte Inc**. The name, logo, product\n  identity, and commercial licensing are managed separately from the code license.\n- Web frontend source is published in\n  [QuantDinger Frontend](https://github.com/OpenByteInc/QuantDinger-Vue) under\n  its own source-available license.\n- Mobile H5 and native client source is published in\n  [QuantDinger Mobile](https://github.com/OpenByteInc/QuantDinger-Mobile) under\n  its own source-available license.\n- Trademark, branding, attribution, and watermark use is governed by\n  [TRADEMARKS.md](TRADEMARKS.md). Apache 2.0 does not grant trademark rights.\n\nFor commercial licensing, frontend source access, branding authorization, or\ndeploymen","github_created_at":"2025-12-28T18:39:26+00:00","created_at":"2026-07-07T17:39:34.818313+00:00","updated_at":"2026-08-19T12:01:16.598806+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"}],"tags":[{"slug":"agent","name":"agent"},{"slug":"ai","name":"ai"},{"slug":"alpaca","name":"alpaca"},{"slug":"backtesting","name":"backtesting"},{"slug":"binance","name":"binance"},{"slug":"coinbase","name":"coinbase"},{"slug":"crypto","name":"crypto"},{"slug":"exchange","name":"exchange"}],"trust":{"provenance":{"is_fork":false,"github_id":1124295269,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-19T12:01:15.647Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":30,"days_since_push":0,"last_release_at":"2026-08-18T12:41:27Z","stars_delta_30d":1055,"open_issues_delta_30d":15},"security_summary":{"status":"no_manifest","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:14:47.193Z","medium_count":0,"scan_profile":"mcp_manifest","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-19T12:01:16.198Z"},"deploy":{"source":"dockerfile:docker-compose.yml","self_host":true,"observed_at":"2026-08-19T12:01:16.198Z","managed_saas":false},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-08-19T12:01:16.198Z"},"has_docker":{"value":true,"source":"dockerfile:docker-compose.yml","observed_at":"2026-08-19T12:01:16.198Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-19T12:01:16.198Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When you need a specialized platform that supports developing and deploying custom trading algorithms across major exchanges such as Binance and Coinbase.","If your strategy involves backtesting trading ideas before deployment into live markets, ensuring robustness of your trading model."],"when_not_to_use":["Not recommended if your operations require more than just Python support; QuantDinger is specifically built around Python services and does not leverage Node.js on the local environment.","If you prefer open-source licenses for all components, note that while the backend is Apache-licensed, the frontend UI has specific commercial licensing terms which may restrict use."],"source":"enrich:decision_facts","observed_at":"2026-07-11T16:06:52.612Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"QuantDinger is an AI-powered quantitative trading platform suitable for traders looking to deploy custom trading agents across multiple financial exchanges."}]}}