A modern, locally-hosted data analysis platform that allows you to load, query, and visualize structured data files with ease. Built with React, FastAPI, and DuckDB for a Snowflake-like experience.

• Smart File Analysis: Automatically detects file type, delimiter, and data types
• Flexible Data Loading: Support for CSV, TSV, TXT, and JSON files
• Header Detection: Auto-detects headers with option to customize
• Column Management: Rename columns or let the tool generate names
• SQL Query Interface: Write and execute SQL queries with Monaco editor
• Visual Filters: Point-and-click filtering without writing SQL
• Data Visualization: Create bar charts, line charts, and pie charts
• Export Functionality: Export query results to CSV or JSON
• Modern UI: Clean, responsive Material-UI interface

• FastAPI: Modern Python web framework
• DuckDB: High-performance analytical database
• Pandas: Data manipulation and analysis
• Chardet: Character encoding detection

• React: UI library
• Material-UI: Component library
• Recharts: Data visualization
• Axios: HTTP client
• Vite: Build tool

bethany-project/
├── backend/
│   ├── app/
│   │   ├── __init__.py
│   │   ├── main.py              # FastAPI application
│   │   ├── models.py            # Pydantic models
│   │   ├── file_analyzer.py     # File analysis logic
│   │   └── database.py          # DuckDB integration
│   └── requirements.txt
├── frontend/
│   ├── src/
│   │   ├── components/
│   │   │   ├── FileUpload.jsx
│   │   │   ├── DataPreview.jsx
│   │   │   ├── QueryInterface.jsx
│   │   │   ├── FilterInterface.jsx
│   │   │   └── DataVisualization.jsx
│   │   ├── services/
│   │   │   └── api.js
│   │   ├── App.jsx
│   │   └── main.jsx
│   ├── index.html
│   ├── vite.config.js
│   └── package.json
└── README.md

• Python 3.8+
• Node.js 16+
• npm or yarn

1. Navigate to the backend directory:

cd backend

2. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Run the FastAPI server:

uvicorn app.main:app --reload --host 0.0.0.0 --port 8000

The API will be available at http://localhost:8000

1. Navigate to the frontend directory:

cd frontend

2. Install dependencies:

npm install

3. Start the development server:

npm run dev

The application will be available at http://localhost:3000

• Drag and drop a file or click to browse
• Supported formats: CSV, TSV, TXT, JSON
• The tool will automatically analyze the file

The tool will display:

• File type and delimiter
• Number of rows and columns
• Detected column names and data types
• Preview of first 10 rows

• Toggle "File has header row" if needed
• Rename columns if no header or ignoring header
• Click "Load Data" to proceed

SQL Query Interface:

• Write SQL queries in the editor
• Press Cmd/Ctrl + Enter to execute
• View results in a table
• Export results to CSV or JSON

Visual Filters:

• Add multiple filter conditions
• Choose column, operator, and value
• Apply filters to see results
• Export filtered data

Data Visualization:

• Select chart type (bar, line, pie)
• Choose X-axis column
• Select aggregation (count, sum, avg, min, max)
• Choose Y-axis for numeric aggregations
• Generate interactive charts

Upload and analyze a file

Load analyzed data into DuckDB

Execute SQL query

Apply visual filters

Export data in CSV or JSON format

Delete session and cleanup resources

-- Get all data
SELECT * FROM data_table LIMIT 100

-- Filter by condition
SELECT * FROM data_table WHERE column_1 > 50

-- Aggregation
SELECT column_1, COUNT(*) as count
FROM data_table
GROUP BY column_1
ORDER BY count DESC

-- Join (if multiple tables loaded)
SELECT a.*, b.*
FROM data_table a
JOIN other_table b ON a.id = b.id

1. Equals: column = 'value'
2. Contains: Find rows where column contains text
3. Greater Than: Numeric comparisons
4. Is Null: Find missing values

The backend uses FastAPI with automatic API documentation:

• Swagger UI: http://localhost:8000/docs
• ReDoc: http://localhost:8000/redoc

The frontend uses Vite for fast development:

• Hot module replacement (HMR)
• Fast refresh for React components

cd backend
pip install -r requirements.txt
uvicorn app.main:app --host 0.0.0.0 --port 8000

cd frontend
npm run build
npm run preview

Import errors:

# Make sure virtual environment is activated
source venv/bin/activate
pip install -r requirements.txt

Port already in use:

# Change the port
uvicorn app.main:app --reload --port 8001

Dependencies not installed:

rm -rf node_modules package-lock.json
npm install

CORS errors:

• Make sure backend is running on port 8000
• Check vite.config.js proxy settings

• Multiple file support
• Save queries and filters
• More chart types (scatter, area, etc.)
• Export to Excel
• Database connection support
• Query history
• Data profiling and statistics
• Column type conversion
• Advanced joins across datasets

MIT License

Contributions are welcome! Please feel free to submit a Pull Request.