预配置的数据平台:摄取、转换、仪表盘和笔记本。基于 dlt、dbt、DuckDB、Metabase 和 Marimo。免费且开源。
AI 翻译
Pre-configured data platform: ingestion, transformation, dashboards, and notebooks. Built on dlt, dbt, DuckDB, Metabase, and Marimo. Free and open source.
数据Python · HTMLGitHub @getdango在线运营者未确认
试用过了吗? 点一下就好,无需登录。
个人 GitHub 账号下公开仓库的所有者可以登录并验证所有权,自行管理介绍,无需管理员批准。
登录并生成验证文件,在 30 分钟内将其提交到此仓库的默认分支。其他分支或分叉仓库中的文件无效。然后在下方检查文件,即可无需管理员批准直接管理项目。请保留文件以维持管理权限。
如需登录,将前往登录页面。登录后请回到此处,再次点击所选的验证按钮。
在项目文件夹中运行 /nomorevibe verify,即可验证所有权并自行管理介绍。
一分钟完成验证您的完整数据平台——dlt、dbt、DuckDB 和 Metabase,自托管且免费。
AI 翻译
Your complete data platform — dlt, dbt, DuckDB, and Metabase, self-hosted and free
取自仓库 README
正在加载完整 README。 以下为已保存的摘录。
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 for data loading, DuckDB as the analytics database, dbt for SQL transformations, and Metabase for dashboards. One pip install, one command to start.查看完整 README ↗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 for data loading, DuckDB as the analytics database, dbt for SQL transformations, and Metabase for dashboards. One install, one command to start.
Upgrading from v0.1.x? v1.0.0 is a complete rewrite. Back up your data and run
dango initto create a new v1 project. See the migration guide for details.
Prerequisites: Python 3.10-3.13, Docker (for Metabase and dbt docs)
macOS / Linux:
curl -sSL https://getdango.dev/install.sh | bash
Windows (PowerShell):
irm https://getdango.dev/install.ps1 | iex
Prefer pip?
mkdir my-project && cd my-project
pip install getdango
dango init
dango start
Open http://localhost:8800 to see your data platform.
For detailed installation instructions, see the documentation.
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 for the complete tool reference
and worked examples.
dango deploydango backup lists and restores local project backupsData Sources page — monitor syncs, row counts, and schedule status for all your data sources.
Data Catalog — browse tables, explore columns with profiling stats, view data lineage.
dbt Models — view model status, run transformations, and track test results.
Sources → dlt → DuckDB → dbt → Metabase
(APIs, (load) (warehouse) (transform) (dashboards)
CSVs,
databases)
All data stays local in DuckDB. No external warehouse needed.
| Component | Tool | Role |
|---|---|---|
| Ingestion | dlt | Load data from 35 sources |
| Warehouse | DuckDB | Embedded analytics database |
| Transformation | dbt | SQL modeling and testing |
| Dashboards | Metabase | BI and SQL queries |
| Web UI | FastAPI | Monitoring and management |
| Containers | Docker | Metabase and service orchestration |
Full documentation at docs.getdango.dev.
See CONTRIBUTING.md for development setup and guidelines.
Apache 2.0 — see LICENSE for details.
Dango is honest about what it doesn't do yet. The short version — full detail at docs.getdango.dev/reference/limitations: