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-0.1.13.tar.gz (715.7 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-0.1.13-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-0.1.13.tar.gz.

File metadata

  • Download URL: go_polars-0.1.13.tar.gz
  • Upload date:
  • Size: 715.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.5

File hashes

Hashes for go_polars-0.1.13.tar.gz
Algorithm Hash digest
SHA256 1af67000e82e4c814fa075da6b4f40e9c4e15c185d845ee3ecc6d83e8b4a9dc5
MD5 41aaa62fbaa650c64b65cad8d731ed25
BLAKE2b-256 c0b5473a7e5afaefff9ac76f87a6b53998ee8febfaaf1d1db345044eafa3b54f

See more details on using hashes here.

File details

Details for the file go_polars-0.1.13-cp313-cp313-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for go_polars-0.1.13-cp313-cp313-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 e0cf5967f920b2a7b329f0b44a54758683b6555d268f00beb32030a2cbebaf5f
MD5 75d1bfaa13b2c43a5af8cc0040c4ff1e
BLAKE2b-256 835be913de2d4ec1ae5cc80b6376090190f4548c40cddef605b860367ba96264

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