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Rust data visualization framework - The modern Plotly alternative

Project description

SeraPlot — High-Performance Data Visualization & ML Framework

SeraPlot v2.4.0+ is a production-grade framework written in Rust, delivering blazing-fast interactive charts and built-in machine learning pipelines. Designed as a modern alternative to Plotly + scikit-learn, it combines visualization and ML preprocessing in a single Rust binary — no dependencies, no bloat.

📖 Documentation: https://feur25.github.io/seraplot/introduction.html


Why Choose SeraPlot?

100–8000× faster than Plotly & Matplotlib on chart generation
Minimal memory footprint — runs on edge devices, embedded systems, low-power servers
Production-ready — enterprise-grade stability, zero fluff, maximum efficiency
Multi-language — Python, JavaScript/WebAssembly, C/C++, C#
60+ chart types — 2D, 3D, maps, statistical plots, all GPU-accelerated
ML preprocessing & metrics — StandardScaler with Welford partial_fit (online learning), Pipeline with score/predict_proba/decision_function, OneHotEncoder/OrdinalEncoder with incremental category union
WebAssembly — npm package @seraplot/wasm for browser visualization & ML inference
Streaming data — online scalers and encoders for incremental model training


Installation

Python (PyPI — wheel for CPython 3.11+)

pip install seraplot

Alternative package managers:

conda install -c conda-forge seraplot
uv pip install seraplot

JavaScript/WebAssembly (npm)

npm install seraplot

Gallery — Chart Types

2D Charts

2D-1 2D-2 2D-3 2D-4
2D-5 2D-6 2D-7 2D-8

3D Charts

3D-1 3D-2 3D-3 3D-4
3D-5 3D-6 3D-7 3D-8

Benchmark — SeraPlot vs Plotly vs Matplotlib

Bench-1 Bench-2 Bench-3

SeraPlot outperforms Plotly and Matplotlib by 100–8000× on chart generation speed.

Project details


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