Metadata-Version: 2.2
Name: sqlshell
Version: 0.1.0
Summary: A powerful SQL shell with GUI interface for data analysis
Home-page: https://github.com/yourusername/sqlshell
Author: SQLShell Team
License: MIT
Project-URL: Homepage, https://github.com/yourusername/sqlshell
Keywords: sql,data analysis,gui,duckdb
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas>=2.0.0
Requires-Dist: numpy>=1.24.0
Requires-Dist: PyQt6>=6.4.0
Requires-Dist: duckdb>=0.9.0
Requires-Dist: openpyxl>=3.1.0
Requires-Dist: pyarrow>=14.0.1
Requires-Dist: fastparquet>=2023.10.1
Requires-Dist: xlrd>=2.0.1
Dynamic: home-page
Dynamic: requires-python

# SQLShell

A powerful SQL shell with GUI interface for data analysis. SQLShell provides an intuitive interface for working with various data formats (CSV, Excel, Parquet) using SQL queries powered by DuckDB.

## Features

- Load and analyze data from CSV, Excel (.xlsx, .xls), and Parquet files
- Interactive GUI with syntax highlighting
- Real-time query results
- Table preview functionality
- Built-in test data generation
- Support for multiple concurrent table views

## Installation

You can install SQLShell using pip:

```bash
pip install sqlshell
```

For development installation:

```bash
git clone https://github.com/yourusername/sqlshell.git
cd sqlshell
pip install -e .
```

## Usage

After installation, you can start SQLShell from anywhere in your terminal by running:

```bash
sqls
```

This will open the GUI interface where you can:
1. Load data files using the "Load Files" button
2. Write SQL queries in the query editor
3. Execute queries using the "Execute" button or Ctrl+Enter
4. View results in the table view below
5. Load sample test data using the "Test" button

## Requirements

- Python 3.8 or higher
- PyQt6
- DuckDB
- Pandas
- Other dependencies will be automatically installed

## License

This project is licensed under the MIT License - see the LICENSE file for details. 
