https://github.com/explorerhq/sql-explorer

SQL reporting that Just Works. Fast, simple, and confusion-free. Write and share queries in a delightful SQL editor, with AI assistance.
https://github.com/explorerhq/sql-explorer

ai analytics django-application reporting sql

Last synced: 12 days ago
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SQL reporting that Just Works. Fast, simple, and confusion-free. Write and share queries in a delightful SQL editor, with AI assistance.

• Host: GitHub
• URL: https://github.com/explorerhq/sql-explorer
• Owner: explorerhq
• License: other
• Created: 2013-12-22T20:58:37.000Z (almost 11 years ago)
• Default Branch: master
• Last Pushed: 2024-10-20T23:21:50.000Z (23 days ago)
• Last Synced: 2024-10-29T09:49:59.471Z (15 days ago)
• Topics: ai, analytics, django-application, reporting, sql
• Language: Python
• Homepage: https://www.sqlexplorer.io
• Size: 2.93 MB
• Stars: 2,761
• Watchers: 65
• Forks: 366
• Open Issues: 37
• Metadata Files:
  • Readme: README.rst
  • Changelog: HISTORY.rst
  • License: LICENSE
  • Authors: AUTHORS

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README

        
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   :target: https://django-sql-explorer.readthedocs.io/en/latest/?badge=latest

   :alt: Documentation Status

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    :alt: License

SQL Explorer

============

* `Official Website `_

* `Live Demo `_

* `Documentation `_

Video Tour

----------

.. |inline-image| image:: https://sql-explorer.s3.amazonaws.com/video-thumbnail.png

   :target: https://sql-explorer.s3.amazonaws.com/Sql+Explorer+5.mp4

   :height: 10em

|inline-image|

Quick Start

-----------

Included is a complete test project that you can use to kick the tires.

1. Run ``docker compose up``

2. Navigate to 127.0.0.1:8000/explorer/

3. log in with admin/admin

4. Begin exploring!

This will also run a Vite dev server with hot reloading for front-end changes.

About

-----

SQL Explorer aims to make the flow of data between people fast,

simple, and confusion-free. It is a Django-based application that you

can add to an existing Django site, or use as a standalone business

intelligence tool. It will happily connect to any SQL database that

`Django supports `_

as well as user-uploaded CSV, JSON, or SQLite databases.

Quickly write and share SQL queries in a simple, usable SQL editor,

view the results in the browser, and keep the information flowing.

Add an OpenAI (or other provider) API key and get an LLM-powered

SQL assistant that can help write and debug queries. The assistant

will automatically add relevant context and schema into the underlying

LLM prompt.

SQL Explorer values simplicity, intuitive use, unobtrusiveness,

stability, and the principle of least surprise. The project is MIT

licensed, and pull requests are welcome.

Some key features include:

- Support for multiple connections, admin configured or user-provided.

- Users can upload and immediately query JSON or CSV files.

- AI-powered SQL assistant

- Quick access to schema information to make querying easier

  (including autocomplete)

- Ability to snapshot queries on a regular schedule, capturing changing data

- Query history and logs

- Quick in-browser statistics, pivot tables, and scatter-plots (saving

  a trip to Excel for simple analyses)

- Parameterized queries that automatically generate a friendly UI for

  users who don't know SQL

- A playground area for quickly running ad-hoc queries

- Send query results via email

- Saved queries can be exposed as a quick-n-dirty JSON API if desired

- ...and more!

Screenshots

-----------

**Writing a query and viewing the schema helper**

.. image:: https://sql-explorer.s3.amazonaws.com/5.0-query-with-schema.png

------------------

**Using the SQL AI Assistant**

.. image:: https://sql-explorer.s3.amazonaws.com/5.0-assistant.png

------------------

**Viewing all queries**

.. image:: https://sql-explorer.s3.amazonaws.com/5.0-query-list.png

------------------

**Query results w/ stats summary**

.. image:: https://sql-explorer.s3.amazonaws.com/5.0-query-results.png

------------------

**Pivot in browser**

.. image:: https://sql-explorer.s3.amazonaws.com/5.0-pivot.png

------------------

**View logs**

.. image:: https://sql-explorer.s3.amazonaws.com/5.0-querylogs.png