d3py vs Bokeh

Side-by-side — pricing, strengths, tradeoffs, and fit.

d3py

Python plotting library based on D3.js for interactive visualizations.

Bokeh

Interactive Web Plotting for Python.

At a glance

Open SourceFree Tier
◌ Declining·From $0
Open SourceFree Tier
● Established·From $0

Overview

One-liner

Python plotting library based on D3.js for interactive visualizations.

One-liner

Interactive Web Plotting for Python.

Maturity

Declining

Maturity

Established

Open source

✓ Yes

Open source

✓ Yes

Pricing

Free tier

✓ Available

Open source — free to use

Free tier

✓ Available

Open source — free to use

Starts at

$0

Starts at

$0

Model

Flat rate

Model

Flat rate

Enterprise

✕ None

Enterprise

✕ None

Best for

✓ Best for

Python developers who need to create advanced, interactive visualizations for web applications without leaving the Python ecosystem.
Data analysts looking to leverage D3.js's capabilities directly from Python.

✓ Best for

Projects requiring high-performance interactivity over large datasets
Web applications that need to visualize streaming data
Developers who want to create interactive plots and charts for web apps without a backend service

Not ideal for

✕ Not for

Projects requiring real-time data streaming and visualization as d3py focuses on static or batch processing of data.
Teams that require a fully managed backend service for their visualizations, as it is primarily a local library.

✕ Not for

Teams needing real-time streaming (Bokeh is more suited for batch processing)
Projects with strict performance constraints where JavaScript libraries might be lighter-weight options

Strengths

↑ Strengths

Integration with D3.js for advanced visualizations
Seamless Python data manipulation and visualization
Interactive charts and graphs directly from Python

↑ Strengths

Interactive plots and charts for web applications
High-performance interactivity over large datasets
Supports streaming data visualization
Customizable visualizations with extensive styling options

Weaknesses

↓ Weaknesses

Limited active development and small community
Performance overhead due to Python-D3.js bridge

↓ Weaknesses

Limited third-party integration support
Performance issues with very large datasets
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