Metadata-Version: 2.1
Name: s5cmd
Version: 0.3.3
Summary: This project provides the infrastructure to build s5cmd Python wheels.
Author-Email: Jean-Christophe Fillion-Robin <jchris.fillionr@kitware.com>
License: Copyright 2024 Jean-Christophe Fillion-Robin
         
         Permission is hereby granted, free of charge, to any person obtaining a copy of
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         the Software without restriction, including without limitation the rights to
         use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
         of the Software, and to permit persons to whom the Software is furnished to do
         so, subject to the following conditions:
         
         The above copyright notice and this permission notice shall be included in all
         copies or substantial portions of the Software.
         
         THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering
Classifier: Typing :: Typed
Project-URL: Homepage, https://github.com/jcfr/s5cmd-python-distributions
Project-URL: Bug Tracker, https://github.com/jcfr/s5cmd-python-distributions/issues
Project-URL: Discussions, https://github.com/jcfr/s5cmd-python-distributions/discussions
Project-URL: Changelog, https://github.com/jcfr/s5cmd-python-distributions/releases
Requires-Python: >=3.8
Provides-Extra: test
Requires-Dist: importlib_metadata>=2.0; python_version < "3.10" and extra == "test"
Requires-Dist: pytest>=6; extra == "test"
Requires-Dist: pytest-cov>=3; extra == "test"
Provides-Extra: dev
Requires-Dist: pytest>=6; extra == "dev"
Requires-Dist: pytest-cov>=3; extra == "dev"
Provides-Extra: docs
Requires-Dist: sphinx>=7.0; extra == "docs"
Requires-Dist: myst_parser>=0.13; extra == "docs"
Requires-Dist: sphinx_copybutton; extra == "docs"
Requires-Dist: sphinx_autodoc_typehints; extra == "docs"
Requires-Dist: furo>=2023.08.17; extra == "docs"
Description-Content-Type: text/markdown

# s5cmd Python Distributions

[![Actions Status][actions-badge]][actions-link]

[![PyPI version][pypi-version]][pypi-link]
[![PyPI platforms][pypi-platforms]][pypi-link]

<!-- SPHINX-START -->

## Overview

`s5cmd` is a very fast S3 and local filesystem execution tool. It comes with
support for a multitude of operations including tab completion and wildcard
support for files, which can be very handy for your object storage workflow
while working with large number of files.

This project provides the infrastructure for building the `s5cmd` Python wheels.
For more information about `s5cmd`, please refer to
https://github.com/peak/s5cmd.

The Python wheels provided here contain the official `s5cmd` executable, which
is sourced from the [GitHub releases](https://github.com/peak/s5cmd/releases).
Once the wheel is installed, a convenient launcher executable is automatically
placed in the PATH. This launcher is created during installation by pip,
leveraging the `[project.scripts]` configuration defined in the `pyproject.toml`
file.

## Platforms

The following platforms are supported by the binary wheels:

| OS            | Arch                                                                         |
| ------------- | ---------------------------------------------------------------------------- |
| Windows       | 64-bit<br>32-bit<br>ARM64                                                    |
| Linux Intel   | manylinux 64-bit<br>musllinux 64-bit<br>manylinux 32-bit<br>musllinux 32-bit |
| Linux ARM     | manylinux AArch64<br>musllinux AArch64                                       |
| Linux PowerPC | manylinux ppc64le<br>musllinux ppc64le                                       |
| macOS 10.10+  | Intel                                                                        |
| macOS 11+     | Apple Silicon                                                                |

## License

This project is maintained by Jean-Christophe Fillion-Robin from Kitware Inc. It
is covered by the OSI-approved MIT License.

`s5cmd` is distributed under the OSI-approved MIT License. For further details
regarding `s5cmd`, please visit https://github.com/peak/s5cmd.

<!-- prettier-ignore-start -->
[actions-badge]:            https://github.com/jcfr/s5cmd-python-distributions/workflows/CI/badge.svg
[actions-link]:             https://github.com/jcfr/s5cmd-python-distributions/actions
[pypi-link]:                https://pypi.org/project/s5cmd/
[pypi-platforms]:           https://img.shields.io/pypi/pyversions/s5cmd
[pypi-version]:             https://img.shields.io/pypi/v/s5cmd

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## Acknowledgments

This software is supported by the Imaging Data Commons (IDC) project, which has
been funded in whole or in part with Federal funds from the NCI, NIH, under task
order no. HHSN26110071 under contract no. HHSN261201500003l.

NCI Imaging Data Commons (IDC) (https://imaging.datacommons.cancer.gov/) is a
cloud-based environment containing publicly available cancer imaging data
co-located with analysis and exploration tools and resources. IDC is a node
within the broader NCI Cancer Research Data Commons (CRDC) infrastructure that
provides secure access to a large, comprehensive, and expanding collection of
cancer research data.

Learn more about IDC from this publication:

> Fedorov, A., Longabaugh, W. J. R., Pot, D., Clunie, D. A., Pieper, S. D.,
> Gibbs, D. L., Bridge, C., Herrmann, M. D., Homeyer, A., Lewis, R., Aerts, H.
> J. W., Krishnaswamy, D., Thiriveedhi, V. K., Ciausu, C., Schacherer, D. P.,
> Bontempi, D., Pihl, T., Wagner, U., Farahani, K., Kim, E. & Kikinis, R.
> _National Cancer Institute Imaging Data Commons: Toward Transparency,
> Reproducibility, and Scalability in Imaging Artificial Intelligence_.
> RadioGraphics (2023). https://doi.org/10.1148/rg.230180
