🧪 VizlyChart Live Demo

import vizlychart as vc

# Natural language to chart
chart = vc.ai.create(
    "scatter plot of sales vs price"
)

# Smart recommendations
data = {'x': [1,2,3], 'y': [2,4,6]}
rec = vc.recommend_chart(data, 'correlation')

print(f"Recommended: {rec.chart_type}")
print(f"Confidence: {rec.confidence:.0%}")

import vizlychart as vc

# List available backends
backends = vc.list_backends()
print(f"Available: {backends}")

# Switch backends seamlessly
vc.set_backend('matplotlib')  # Publication
chart = vc.LineChart()

vc.set_backend('plotly')      # Interactive
chart = vc.LineChart()        # Same API!

vc.set_backend('pure')        # GPU-ready
chart = vc.LineChart()

from vizlychart.gpu import AcceleratedRenderer
import numpy as np

# Create GPU renderer
renderer = AcceleratedRenderer(800, 600)

# Test with large dataset
x = np.random.randn(1000)
y = np.random.randn(1000)

# GPU-accelerated rendering
renderer.scatter_gpu(x, y, color='blue')

# Get performance stats
stats = renderer.get_performance_stats()

import vizlychart as vc

# Natural language styling
vc.style_chart(chart,
    "professional blue theme with bold fonts"
)

# Parse styling descriptions
style = vc.ai.parse_style(
    "elegant pastel colors with shadows"
)

print(f"Theme: {style.overall_theme}")
print(f"Colors: {style.color_scheme}")