How to use Neptune with Bokeh#
Bokeh is a Python library for creating interactive visualizations for modern web browsers. With Neptune, you can log and display Bokeh charts as interactive HTML.
Before you start#
To follow the guide without any setup, run the Colab example.
- Sign up at neptune.ai/register.
- Create a project for storing your metadata.
Have Bokeh and Neptune installed:
neptune-client already installed
Important: To smoothly upgrade to the
1.0 version of the Neptune client library, first uninstall the
neptune-client library and then install
Bokeh logging example#
Import Neptune and start a run:
If you haven't set up your credentials, you can log anonymously:
Create a sample figure:
import numpy as np from bokeh.plotting import figure N = 500 x = np.linspace(0, 10, N) y = np.linspace(0, 10, N) xx, yy = np.meshgrid(x, y) d = np.sin(xx) * np.cos(yy) p = figure(tooltips=[("x", "$x"), ("y", "$y"), ("value", "@image")]) p.x_range.range_padding = p.y_range.range_padding = 0 # Pass a vector of image data as the 'image' argument p.image( image=[d], x=0, y=0, dw=10, dh=10, palette="Spectral11", level="image" ) p.grid.grid_line_width = 0.5
Upload the interactive figure:
To stop the connection to Neptune and sync all data, call the
To open the run, click the Neptune link that appears in the console output.
The resulting figure is logged as an HTML object.
You can view it in the All metadata section.