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Sql Admin Panel

#admin#database#data#developer#enterprise

Build a SQL dashboard and admin panel with schema browsing, searchable data grids, safe queries, row editing, and result history.

Preview
Code
/index
Workspace is ready
Tech Stack
reflexpython
Key Features
Schema explorer with typed columns and qualified-name insertion
SQL editor with read-only statement validation and keyboard execution
Sortable paginated result grid with explicit null values
Saved queries with unique-name validation and exact SQL restoration
Timestamped query history with duration and row-count feedback
Before-and-after review for one allowlisted local record edit
Requirements
A safe local workspace for exploring relational data
Read-only SQL execution with clear validation feedback
Review-before-commit edits to allowlisted sample fields
Saved queries and timestamped run history

About This Template

SQL Admin Panel is a Reflex template for analysts and developers who want a clear SQL dashboard and admin dashboard for inspecting relational data without starting from a live database connection. The seeded Local sample opens with a saved customer-revenue join, a schema explorer, an editable SQL surface, and an internally consistent result grid. Running valid read-only SQL updates the returned rows, elapsed time, row count, and timestamped history together, while unsupported input leaves the current result intact and explains what to change. Saved queries restore their exact SQL, schema items can insert qualified names, and sortable paginated results make nulls and values explicit. A selected customer also demonstrates one narrowly allowlisted status edit with a before-and-after review and local confirmation. This constrained workflow shows useful admin behavior without implying that arbitrary SQL is safe for production. Teams can later replace the local data boundary with an appropriately secured database adapter. The SQL dashboard is designed as a database administration interface users can inspect immediately, then connect to an approved PostgreSQL, MySQL, SQLite, or MSSQL database when live access is appropriate.

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