dango

# Dango [](https://pypi.org/project/getdango/) [](https://pypi.org/project/getdango/) [](LICENSE) [](https://github.com/getdango/dango) **Open-source data platform for small teams.** Dango gives you a complete data stack — ingestion, warehouse, transformations, and dashboards — with the operational machinery a self-assembled stack doesn't have: sync queue management, lock recovery, empty-replace protection, schema drift detection, credential health checks, and backups. It combines [dlt](https://dlthub.com/) for data loading, [DuckDB](https://duckdb.org/) as the analytics database, [dbt](https://www.getdbt.com/) for SQL transformations, and [Metabase](https://www.metabase.com/) for dashboards. One `pip install`, one command to start. > **Upgrading from v0.1.x?** v1.0.0 is a complete rewrite. Back up your data and run `dango init` to create a new v1 project. See the [migration guide](https://docs.getdango.dev) for details. ## Quick Start **Prerequisites:** Python 3.10-3.13, [Docker](https://docs.docker.com/desktop/) (for Metabase and dbt docs) ```bash mkdir my-project && cd my-project pip install getdango dango init dango start ``` Open [http://localhost:8800](http://localhost:8800) to see your data platform. Or use the install script: ```bash curl -sSL https://getdango.dev/install.sh | bash ``` For detailed installation instructions, see the [documentation](https://docs.getdango.dev). ## Use Dango with your coding agent ```bash dango mcp setup ``` Connects Claude Code, Cursor, or Windsurf to your project over MCP — your agent can set up sources (credentials stay in your `.env`, never in the chat), sync, build and document dbt models, manage schedules, check PII findings and schema drift, diagnose failures, and run read-only queries with PII columns masked. Remote tools default to a dry run. See the [full guide](https://docs.getdango.dev/guides/mcp-claude-code/) for the complete tool reference and worked examples. ## Features - **35 data sources** — Stripe, Google Sheets, Google Analytics, Shopify, PostgreSQL, MySQL, CSV, REST APIs, and more - **Auto-generated dbt models** — staging models created automatically when you add a source - **Data catalog** — browse tables, columns, and profiling stats; view dbt lineage and test results - **Web dashboard** — monitor syncs, manage sources, and view platform health - **Metabase integration** — dashboards and SQL queries, auto-configured and ready to use - **Scripts** — schedule custom Python scripts alongside your syncs; runs on a schedule with access to your warehouse - **Cloud deployment** — deploy to DigitalOcean or any server with `dango deploy` - **Authentication** — admin login, user management, 2FA, API keys - **Schema drift detection** — get alerted when source schemas change - **PII scanning** — detect personally identifiable information across your tables - **Notebooks** — Marimo notebooks connected to your DuckDB warehouse - **Monitoring** — metric tracking with trend detection and drill-downs - **Scheduled syncs** — cron-based scheduling with queued execution, retry, and timeout handling - **Webhooks** — Slack notifications for sync results and alerts - **Local backup** — `dango backup` lists and restores local project backups - **File watcher** — auto-sync when CSV files change on disk ## Screenshots <img src="https://raw.githubusercontent.com/getdango/dango/main/docs/assets/screenshots/sources.png" alt="Dango Sources page showing connected data sources with sync status" width="800"> *Data Sources page — monitor syncs, row counts, and schedule status for all your data sources.* <img src="https://raw.githubusercontent.com/getdango/dango/main/docs/assets/screenshots/catalog.png" alt="Dango Data Catalog showing columns, lineage, and profiling" width="800"> *Data Catalog — browse tables, explore columns with profiling stats, view data lineage.* <img src="https://raw.githubusercontent.com/getdango/dango/main/docs/assets/screenshots/models.png" alt="Dango dbt Models page" width="800"> *dbt Models — view model status, run transformations, and track test results.* ## Architecture ``` Sources → dlt → DuckDB → dbt → Metabase (APIs, (load) (warehouse) (transform) (dashboards) CSVs, databases) ``` All data stays local in DuckDB. No external warehouse needed. ## Tech Stack | Component | Tool | Role | |-----------|------|------| | Ingestion | [dlt](https://dlthub.com/) | Load data from 35 sources | | Warehouse | [DuckDB](https://duckdb.org/) | Embedded analytics database | | Transformation | [dbt](https://www.getdbt.com/) | SQL modeling and testing | | Dashboards | [Metabase](https://www.metabase.com/) | BI and SQL queries | | Web UI | [FastAPI](https://fastapi.tiangolo.com/) | Monitoring and management | | Containers | [Docker](https://www.docker.com/) | Metabase and service orchestration | ## Documentation Full documentation at [docs.getdango.dev](https://docs.getdango.dev). ## Contributing See [CONTRIBUTING.md](CONTRIBUTING.md) for development setup and guidelines. ## License Apache 2.0 — see [LICENSE](LICENSE) for details. ## Known limitations Dango is honest about what it doesn't do yet. The short version — full detail at [docs.getdango.dev/reference/limitations](https://docs.getdango.dev/reference/limitations): - Single-writer concurrency until the Quack migration lands (DuckDB 2.0) - No streaming, CDC, or reverse ETL - 35 sources today, added on demand - BYOS deployments need to configure their own backup destination (warned at deploy time) ## Links - [PyPI](https://pypi.org/project/getdango/) - [Changelog](CHANGELOG.md) - [Issues](https://github.com/getdango/dango/issues)