for t in range(100):
    plot(
        x=x,
        y=np.cos(x + t / 10)
    )
    time.sleep(0.01)

Visualize in realtime directly from your Python scripts — no notebooks, servers, or
browsers required.

Visualizations are displayed in a dedicated
tab right within the IDE.

Scripton includes built-in plotting toolkits that expose the capabilities of Plotly
and
Observable
Plot directly to Python.

No installation is necessary — these libraries are automatically
available when executing in Scripton.

from scripton.lyra import plot
import numpy as np

# Evenly spaced values between 0 and 2π
x = np.linspace(0, 2 * np.pi)

# Plot sin(x)
plot({'x': x, 'y': np.sin(x)})

For more details, check out the Scripton plotting documentation for Lyra
(toolkit for Plotly) and Orion
(toolkit for Observable Plot).

Scripton’s architecture combines high-performance interprocess communication for low
latency and high throughput on the backend, while leveraging GPU-accelerated rendering to
deliver real-time visualizations.

Visualizing matrices (2D NumPy arrays, PyTorch tensors, …) is as simple as this —

import numpy as np
from scripton import show

x = np.arange(100)
toeplitz = np.abs(x[:, None] - x)

# Show a colormapped version of the matrix
show(toeplitz)

Learn more about visualizing
matrices.

The built-in Scripton canvas library
provides a fast and powerful 2D raster graphics API.

from scripton.canvas import Canvas

canvas = Canvas(width=290, height=200)

for i in range(10):
    canvas.draw_circle(
        x=100 + 5 * i,
        y=100,
        radius=10 + 10 * i,
        fill='#3D79FF2