Chartify vs Plotly (Python)
A data-driven comparison of two Python interactive web charting libraries: popularity, development activity, licensing and installation. Updated .
ChartifyBokeh wrapper that makes it easy for data scientists to create charts.
Plotly (Python)Interactive web based visualization built on top of plotly.js
Key differences
- Plotly (Python) has 5.2× as many GitHub stars as Chartify (18.9K vs 3.7K).
- Plotly (Python) had more development activity over the last 12 months: 816 commits vs 0.
- Plotly (Python) is downloaded 24259× as often on PyPI (14.3M vs 588 per week).
- Chartify is licensed under Apache-2.0; Plotly (Python) under MIT.
- Plotly (Python) is the older project: its repository was created in 2013, Chartify's in 2018.
- Chartify has had no commits since Oct 16, 2024.
By the numbers
- Chartify
- Plotly (Python)
Show data as a table
| Metric | Chartify | Plotly (Python) |
|---|---|---|
| GitHub stars | 3,656 | 18,868 |
| PyPI downloads / week | 588 | 14,264,549 |
| Commits, last 12 months | 0 | 816 |
| Contributors | 19 | 311 |
| Forks | 337 | 2,884 |
Development activity
Commits per month to each default branch, last 12 complete months.
- Chartify
- Plotly (Python)
Show data as a table
| Month | Chartify | Plotly (Python) |
|---|---|---|
| Nov 2025 | 0 | 51 |
| Dec 2025 | 0 | 33 |
| Jan 2026 | 0 | 25 |
| Feb 2026 | 0 | 44 |
| Mar 2026 | 0 | 94 |
| Apr 2026 | 0 | 67 |
| May 2026 | 0 | 49 |
| Jun 2026 | 0 | 36 |
| Jul 2026 | 0 | 98 |
| Aug 2026 | 0 | 80 |
| Sep 2026 | 0 | 98 |
| Oct 2026 | 0 | 141 |
Side by side
| Attribute | Chartify | Plotly (Python) |
|---|---|---|
| Description | Bokeh wrapper that makes it easy for data scientists to create charts. | Interactive web based visualization built on top of plotly.js |
| Category | Python interactive web charting libraries | Python interactive web charting libraries |
| License | Apache-2.0 | MIT |
| Language | Python | Python |
| Status | Inactive | Active |
| Latest release | 5.0.1 () | v7.1.0 () |
| Last commit | ||
| Repository created | ||
| Open issues | 44 | 647 |
| Install | pip install chartify | pip install plotly |
Which should you choose?
Popularity and activity are only part of the story. Consider which ecosystem you work in, the chart types and interactions you need, how much data you render, and whether the license fits your project. Both tool pages list alternatives if neither is quite right.
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Chartify
Bokeh wrapper that makes it easy for data scientists to create charts.
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Plotly (Python)
Interactive web based visualization built on top of plotly.js