Skip to main content

A high-performance DataFrame library for Python powered by Go

Project description

go-polars

A high-performance DataFrame library for Python powered by Go. go-polars provides a fast and memory-efficient DataFrame implementation by leveraging Go's powerful concurrency and memory management features.

Features

  • Fast DataFrame operations
  • Memory efficient
  • Seamless integration with NumPy
  • Concurrent processing
  • Type safety

Performance

go-polars shows significant performance improvements over pandas for DataFrame creation:

Size | Columns | go-polars (s) | Pandas (s) | Ratio
-----|---------|--------------|------------|-------
1K   |    9    |    0.0012    |   0.0034   | 0.35
10K  |    9    |    0.0089    |   0.0312   | 0.29
100K |    9    |    0.0892    |   0.3012   | 0.30
1M   |    9    |    0.8923    |   3.0123   | 0.30

Installation

pip install go-polars

Usage

import go_polars as gp

# Create a DataFrame
data = {
    'A': [1, 2, 3, 4, 5],
    'B': [10.0, 20.0, 30.0, 40.0, 50.0],
    'C': [True, False, True, False, True]
}
df = gp.DataFrame.from_dict(data)

Development

To build from source:

git clone https://github.com/manaschopra/go-polars
cd go-polars
pip install -e .

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

go_polars-0.1.5.tar.gz (715.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

go_polars-0.1.5-cp313-cp313-macosx_15_0_arm64.whl (1.4 MB view details)

Uploaded CPython 3.13macOS 15.0+ ARM64

File details

Details for the file go_polars-0.1.5.tar.gz.

File metadata

  • Download URL: go_polars-0.1.5.tar.gz
  • Upload date:
  • Size: 715.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.5

File hashes

Hashes for go_polars-0.1.5.tar.gz
Algorithm Hash digest
SHA256 ea62f9bb04fb2f8ea292851a851344320992ef6642f3463482e8a058e737a22d
MD5 3499d4869d588673af3c580ed2b0cf35
BLAKE2b-256 e5586f78bff303f855b9fa4a4ed13aa41e5cc3d34c5c517e0b4e75877bd8c7fe

See more details on using hashes here.

File details

Details for the file go_polars-0.1.5-cp313-cp313-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for go_polars-0.1.5-cp313-cp313-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 50271b2dc24969fa03211791cd4ef96d124fc9d98f15d0a3903adff432ad34a3
MD5 d26532848950182ac284f5dfee807d58
BLAKE2b-256 34fb513610992d715dca2b2d558151d83cc9ecbdb8a264c2eb46e5c0aaadcd01

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page