What will you get with this integration?

​Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. This integration lets you log charts generated in matplotlib to Neptune for easy reference and collaboration.

Introduction

This guide will show you how to:

• Initialize Neptune and create a run,

• Log matplotlib charts to Neptune.

Step 0: Before you start

Make sure that:

• You have Python 3.6+ in your system,

• You are already registered user, so that you can log metadata to your private projects.

• You have your NEPTUNE_API_TOKEN set to the environment variable: check this docs page.

Install neptune-client and matplotlib

Depending on your operating system open a terminal or CMD and run this command. All required libraries are available via pip and conda:

pip install neptune-client matplotlib

conda install -c conda-forge neptune-client matplotlib

For more help see installing neptune-client.

This integration is tested with neptune-client==0.9.5 and matplotlib==3.2.2.

Install plotly (optional)

If you want to log static matplotlib figures to interactive plotly charts, you need to install plotly.

pip install plotly

conda install -c conda-forge plotly

This integration is tested with plotly==5.0.0.

Step 1: Import and initialize Neptune

import neptune.new as neptune
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run = neptune.init(api_token='<your_api_token>', project='<your_project_name>')

Executing this cell will give you a link looking like: https://app.neptune.ai/common/matplotlib-support/e/MAT-3352 with common/matplotlib-support replaced by your project, and MAT-3352 replaced by your run.

Click on the link to open the run in Neptune. For now, it is empty but keep the tab with the run open to see what happens next.

Step 2: Log Matplotlib figures to Neptune

Create a sample figure

import matplotlib.pyplot as plt
import numpy as np
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np.random.seed(42)
data = np.random.randn(2, 100)
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figure, ax = plt.subplots(2, 2, figsize=(5, 5))
ax[0, 0].hist(data[0])
ax[1, 0].scatter(data[0], data[1])
ax[0, 1].plot(data[0], data[1])

Log as a static image

run["static-img"].upload(neptune.types.File.as_image(figure))

Log as an interactive chart

If you have plotly installed, you can log your static matplotlib figures as interactive plotly charts.

run['interactive-img'].upload(neptune.types.File.as_html(figure))

Step 3: Stop logging

run.stop()

Step 4: Explore the charts in Neptune

The images can be found in the All metadata section:

Conclusion

You’ve learned how to:

• Initialize Neptune and create a run,

• Log matplotlib charts to Neptune.

What's next

Now that you know how to log charts to Neptune, you can learn:

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