pyarrow
Python library for Apache Arrow
Install
pyarrow on PyPI
pip
pip install pyarrowuv
uv add pyarrowpoetry
poetry add pyarrowPackage facts
| License | Apache-2.0 (permissive) |
| Python support | supports the current Python release (>=3.10) |
| Install friction | medium — platform-specific wheel |
| Runtime dependencies | none |
| Maintenance | actively maintained — 3 days since the last release |
| Last repo commit | |
| First released | |
| Popularity | one of the 100 most-downloaded packages on PyPI (30-day window, as of 2026-08-13) |
| Known vulnerabilities | none known (OSV.dev, checked 2026-08-13) |
Evidence: pyarrow-25.0.1-cp310-cp310-macosx_12_0_arm64.whl; pyarrow-25.0.1-cp310-cp310-macosx_12_0_x86_64.whl; pyarrow-25.0.1-cp310-cp310-manylinux_2_28_aarch64.whl; pyarrow-25.0.1-cp310-cp310-manylinux_2_28_x86_64.whl; pyarrow-25.0.1-cp310-cp310-musllinux_1_2_aarch64.whl; pyarrow-25.0.1-cp310-cp310-musllinux_1_2_x86_64.whl; pyarrow-25.0.1-cp310-cp310-win_amd64.whl; pyarrow-25.0.1-cp311-cp311-macosx_12_0_arm64.whl; pyarrow-25.0.1-cp311-cp311-macosx_12_0_x86_64.whl; pyarrow-25.0.1-cp311-cp311-manylinux_2_28_aarch64.whl; pyarrow-25.0.1-cp311-cp311-manylinux_2_28_x86_64.whl; pyarrow-25.0.1-cp311-cp311-musllinux_1_2_aarch64.whl; pyarrow-25.0.1-cp311-cp311-musllinux_1_2_x86_64.whl; pyarrow-25.0.1-cp311-cp311-win_amd64.whl; pyarrow-25.0.1-cp312-cp312-macosx_12_0_arm64.whl; pyarrow-25.0.1-cp312-cp312-macosx_12_0_x86_64.whl; pyarrow-25.0.1-cp312-cp312-manylinux_2_28_aarch64.whl; pyarrow-25.0.1-cp312-cp312-manylinux_2_28_x86_64.whl; pyarrow-25.0.1-cp312-cp312-musllinux_1_2_aarch64.whl; pyarrow-25.0.1-cp312-cp312-musllinux_1_2_x86_64.whl
About pyarrow
from the package's own PyPI description — quoted content, verbatim
<!--- Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements. See the NOTICE file distributed with this work for additional information regarding copyright ownership. The ASF licenses this file to you under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. -->
Python library for Apache Arrow
pypi (image) conda-forge (image)
This library provides a Python API for functionality provided by the Arrow C++ libraries, along with tools for Arrow integration and interoperability...
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
pyarrow is a Python library providing access to Apache Arrow's C++ data structures and computation engine, enabling efficient columnar data processing and interoperability with pandas, NumPy, and other Python ecosystem tools.
Medium install friction due to compiled C++ dependencies across multiple platforms (macOS arm64/x86_64, Linux aarch64/x86_64, Windows). Pre-built wheels available for Python 3.10–3.12. Actively maintained with release 25.0.1 just 3 days old.
Apache-2.0 permissive license allows commercial and private use with minimal restrictions; you must include a copy of the license and notice file but face no copyleft obligations.
Usage
pip install pyarrow
import pyarrow as pa
table = pa.table({'col1': [1, 2, 3], 'col2': ['a', 'b', 'c']})
print(table)
Requires Python ≥3.10. On Windows, may require Visual C++ Redistributable for Visual Studio to be installed separately.
Verdict: pyarrow is a mature, actively maintained top-100 PyPI package with zero known vulnerabilities and permissive Apache-2.0 licensing. Medium install friction is typical for compiled libraries and well-mitigated by pre-built wheels across major platforms. Suitable for production data processing pipelines.
Needs verification
- Whether the Visual C++ Redistributable requirement on Windows affects most users or is an edge case
- Performance characteristics compared to alternative columnar formats for specific workloads
- Adoption metrics beyond GitHub stars to assess ecosystem integration
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