SQL Explorer Project Introduction
SQL Explorer is a powerful tool designed to streamline data flow and make it more accessible. Developed for use with Django, it can be integrated into an existing Django website or used as an independent business intelligence application. Known for its simplicity, stability, and user-friendly design, SQL Explorer connects to any SQL database supported by Django, including databases created from user-uploaded CSVs, JSON, or SQLite files.
Key Features
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Multi-Database Support: Admins can configure multiple connections, or users can provide their own, allowing flexibility in data sources.
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User-Friendly Uploads: Users can upload JSON or CSV files and start querying them immediately.
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AI-Powered SQL Assistant: Connect an OpenAI or similar provider's API key, and let an AI assistant help write and debug queries. It adds relevant context and schema information automatically.
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Querying Made Simple: Enjoy quick access to schema details with features like autocomplete, reducing error and confusion.
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Snapshot Capabilities: Regularly scheduled query snapshots capture data changes over time.
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Logging and History: Keep track of previous queries, making it easy to revisit past analyses.
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In-Browser Analysis: Generate statistics, create pivot tables, and scatter plots directly in the browser, minimizing the need for external tools like Excel for simple tasks.
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Parameterized Queries: Create a user-friendly interface for those unfamiliar with SQL syntax.
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Playground and Email Features: Test ad-hoc queries quickly or email query results directly.
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JSON API: Convert saved queries into a straightforward JSON API effortlessly.
SQL Explorer is MIT licensed, encouraging collaboration and improvement through community pull requests.
Getting Started
To explore SQL Explorer, follow these simple steps:
- Run
docker compose up. - Navigate to 127.0.0.1:8000/explorer/ in your web browser.
- Log in using admin/admin credentials.
- Start exploring and making queries!
This setup includes a Vite dev server for front-end changes with hot reloading, enhancing the development experience.
Visual Guide
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Create and View Queries: Effortlessly write queries and use the schema helper.
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SQL AI Assistant: Utilize the AI assistant for smarter querying.
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Query Management: Access a comprehensive list of all your queries.
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Results and Analysis: View your query results with statistical summaries.
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In-Browser Pivots: Perform pivots without leaving the browser.
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Log Reviews: Check logs for a detailed view of query activities.
Conclusion
SQL Explorer is a versatile and powerful tool designed to offer ease and efficiency in data management and analysis. With its supportive features and intuitive interface, it bridges the gap between data complexity and user accessibility, making it an invaluable asset for any data-centric project.