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.

Bokeh figure in Neptune

See in Neptune Example script

Before you start#

Tip

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:

pipconda

pip install -U bokeh neptune

conda install -c conda-forge bokeh neptune

Upgrading with 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 neptune.

pip uninstall neptune-client

pip install neptune

Bokeh logging example#

Import Neptune and start a run:

import neptune

run = neptune.init_run()  # (1)!

If you haven't set up your credentials, you can log anonymously:

neptune.init_run(
    api_token=neptune.ANONYMOUS_API_TOKEN,
    project="common/bokeh-support",
)

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:
```
run["interactive_img"].upload(p)
```
To stop the connection to Neptune and sync all data, call the stop() method:
```
run.stop()
```
To open the run, click the Neptune link that appears in the console output.

Example link: https://app.neptune.ai/common/bokeh-support/e/BOK-9/metadata

Result

The resulting figure is logged as an HTML object.

You can view it in the All metadata section.