awswrangler

Pandas on AWS.

awswrangler Permissive license Apache-2.0 Active ★ 4,116 v3.17.1 released 2026-08-03

Install

awswrangler on PyPI

pip

pip install awswrangler

uv

uv add awswrangler

poetry

poetry add awswrangler

Package facts

License	Apache-2.0 (permissive)
Python support	supports the current Python release (<4.0,>=3.10)
Install friction	low — pure-Python wheel
Runtime dependencies	8 — boto3, botocore, numpy, packaging, pandas, pyarrow, setuptools, typing-extensions
Maintenance	actively maintained — 10 days since the last release
Last repo commit	2026-08-13
First released	2019-02-28
Popularity	one of the top 1,000 most-downloaded packages on PyPI (30-day window, as of 2026-08-13)
Known vulnerabilities	none known (OSV.dev, checked 2026-08-13)

Evidence: awswrangler-3.17.1-py3-none-any.whl

Keywords: aws, pandas

Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14

About awswrangler

from the package's own PyPI description — quoted content, verbatim

AWS SDK for pandas (awswrangler)

Pandas on AWS

Easy integration with Athena, Glue, Redshift, Timestream, OpenSearch, Neptune, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).

AWS SDK for pandas (image) tracker (image)

> An AWS Professional Service open source initiative | aws-proserve-opensource@amazon.com

PyPi (image) Conda (image) Python Version (image) Code style: ruff (image) License (image)

[![Checked...

Read as markdown · JSON record · Source repository · Homepage · Docs

AI interpretation — verify before relying

AI-generated interpretation of the package facts above; every digit, version, license, or vulnerability id it cites is grounded in the facts already shown on this page

awswrangler integrates pandas DataFrames with AWS services including S3, Athena, Redshift, Glue, Timestream, and databases like PostgreSQL and MySQL, enabling seamless data reading and writing across the AWS ecosystem.

Low friction: pure Python wheel with 8 runtime dependencies (boto3, botocore, numpy, pandas, pyarrow, packaging, setuptools, typing-extensions). Active maintenance with release 10 days old and 4116 GitHub stars. Supports Python 3.10–3.14.

Apache-2.0 permissive license allows commercial and private use with minimal restrictions, requiring only license and copyright notice retention.

Usage

pip install awswrangler
import awswrangler as wr
import pandas as pd
df = pd.DataFrame({"id": [1, 2], "value": ["foo", "boo"]})
wr.s3.to_parquet(df=df, path="s3://bucket/dataset/", dataset=True)
df = wr.s3.read_parquet("s3://bucket/dataset/", dataset=True)

AWS credentials must be configured (via environment variables, IAM role, or AWS CLI config); some optional features (e.g., Redshift) require explicit extra installation.

Verdict: Well-maintained AWS SDK for pandas with active development, no known vulnerabilities, and permissive licensing. Low install friction and broad AWS service coverage make it suitable for data workflows on AWS. Optional modules must be installed explicitly from version 3.0 onward.

Needs verification

Whether optional extras (redshift, etc.) are documented in the fact sheet or require separate discovery
Performance characteristics at scale with Modin/Ray integration mentioned in description

pandas aws integrationread write s3 parquetathena sql queriesredshift data accessaws data lakeglue catalog pandastimestream write read