Transform Raw SQL queries into visualizations using DuckDB and Iced. Available for Rust, Python, and WebAssembly.
[dependencies]
sql2viz = { version = "0.2.0", features = ["gui"] }pip install sql2viznpm install @nkwork9999/sql2viz-wasmuse sql2viz::vizcreate;
fn main() {
let query = "SELECT 'A' as x, 10 as y UNION ALL SELECT 'B', 20";
vizcreate(query.to_string()).unwrap();
}use sql2viz::vizcreate;
fn main() {
let queries = "
-- Connect to existing database
ATTACH 'mydata.db' AS mydb;
-- Query 1: Sales summary by category
SELECT category, SUM(amount) as total_sales
FROM mydb.sales
GROUP BY category
ORDER BY total_sales DESC;
-- Query 2: Load CSV file
SELECT * FROM 'test.csv' LIMIT 100;
";
vizcreate(queries.to_string()).unwrap();
}use sql2viz::{VizBuilder, ChartType};
fn main() -> Result<(), Box<dyn std::error::Error>> {
VizBuilder::new()
.add_query("SELECT month, sales FROM data")
.with_chart(ChartType::Line, "month", "sales")
.launch()?;
Ok(())
}Method 1: Direct SQL
from sql2viz import vizcreate
# Simple query
vizcreate("SELECT * FROM 'data.csv'")
# Multiple queries
vizcreate("""
SELECT category, COUNT(*) as count
FROM products
GROUP BY category;
SELECT month, revenue
FROM sales
ORDER BY month;
""")Method 2: DuckDB Integration
import duckdb
# Simple usage
duckdb.sql("SELECT * FROM 'sales.csv'").viz()
# With chart configuration
duckdb.sql("SELECT month, revenue FROM sales").viz(
chart_type="Line",
x_column="month",
y_column="revenue"
)Method 3: Using VizBuilder
from sql2viz import VizBuilder
builder = VizBuilder()
builder.add_query("SELECT month, sales FROM data")
builder.with_chart("Bar", "month", "sales")
builder.launch()Available chart types: "Bar", "Line", "Area", "Scatter"
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8" />
<title>SQL2VIZ Example</title>
</head>
<body>
<canvas id="chart" width="800" height="600"></canvas>
<script type="module">
import init, {
WasmVizBuilder,
} from "https://unpkg.com/@nkwork9999/sql2viz-wasm@0.2.0/sql2viz.js";
async function run() {
await init();
const canvas = document.getElementById("chart");
const builder = new WasmVizBuilder();
builder.setTitle("Sales Data");
builder.setChartType("bar");
const data = {
column_names: ["Month", "Sales"],
rows: [
["January", "150"],
["February", "230"],
["March", "180"],
],
};
builder.renderChart(canvas, data);
}
run();
</script>
</body>
</html>Chart types: "bar", "line", "pie", "scatter"
- SQL query execution with DuckDB
- Interactive charts (Bar, Line, Area, Scatter, Pie)
- Table view with alternating row colors
- Multiple query tabs
- Column selection for chart axes
- CSV, Parquet, JSON file support
gui: Enable GUI visualization with Icedpython: Python bindings via PyO3wasm: WebAssembly support
# GUI only
sql2viz = { version = "0.2.0", features = ["gui"] }
# Python bindings
sql2viz = { version = "0.2.0", features = ["python"] }
# WASM
sql2viz = { version = "0.2.0", features = ["wasm"] }| Platform | Rust | Python | WASM |
|---|---|---|---|
| Windows | ✅ | ✅ | ✅ |
| macOS | ✅ | ✅ | ✅ |
| Linux | ✅ | ✅ | ✅ |
| Web | ❌ | ❌ | ✅ |
- Rust Crate: https://crates.io/crates/sql2viz
- Python Package: https://pypi.org/project/sql2viz/
- WASM Package: https://www.npmjs.com/package/@nkwork9999/sql2viz-wasm
- GitHub Repository: https://github.com/nkwork9999/sql2viz
- Documentation: https://docs.rs/sql2viz
- MIT License (LICENSE-MIT or http://opensource.org/licenses/MIT)