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Polars

Lightning-fast DataFrame library in Rust with lazy evaluation for efficient data preprocessing before model training.

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Data Utilities MIT Medium setup 30,000 stars

Overview

Plain English

Lightning-fast DataFrame library in Rust with lazy evaluation for efficient data preprocessing before model training.

Technical

Lightning-fast DataFrame library in Rust with lazy evaluation for efficient data preprocessing before model training.

Technical scorecard

License MIT
Commercial use Yes
OpenAI-compatible API No
REST API No
Fine-tuning support No
Quantization support No
Docker available No
GUI / no-code available No
Telemetry None
Offline after setup Yes

Data & Privacy

Does it send data online?

After setup, this listing is marked as usable offline. Confirm network behavior against the upstream project before regulated deployment.

Does it store history?

Not verified in this directory yet. Review the upstream docs for persistence, logs, and workspace storage.

License checks?

Commercial use is marked as allowed or likely allowed by the listed license.

Telemetry?

None

Last verified: May 16, 2026. Maintainer verification should be treated as directory guidance, not legal advice.

Setup & Installation

Medium

A developer can usually get this running with standard docs.

Prerequisites

Rust, Bare Metal 

# Start with the official project documentation
# https://github.com/pola-rs/polars

Hardware Requirements

RAM8 GB minimum / 16 GB recommended
Hardware tagsCPU Only
Model formatsNot specified
Primary languageRust

Works Well With

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