s5cmd
This project provides the infrastructure to build s5cmd Python wheels.
Decision gist · record as of 2026-08-14
Yes, if you need a fast, portable S3 command-line tool and your platform is among the supported architectures. The MIT license, active maintenance, zero Python dependencies, and broad platform coverage make it a low-friction choice for S3 workflows. Medium install friction is mainly a matter of ensuring the correct binary wheel is available for your OS and CPU architecture—a non-issue on common platforms (x86_64 Linux, Windows, macOS Intel/Apple Silicon).AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- The correct binary wheel must be available for your platform (Windows, Linux, or macOS) and architecture (x86_64, ARM64, ppc64le, or 32-bit); installation will fail if no matching wheel exists.
- Medium install friction due to platform-specific binary wheels.
- The package is actively maintained with recent releases and has no runtime dependencies, simplifying installation once the correct wheel is selected for your platform.
License · maintenance · safety
permissive license (permissive) — MIT license (permissive) allows unrestricted use, modification, and distribution. No restrictions on commercial or proprietary use.
last release 2025-09-09 (339 days) · last repo commit 2026-08-10 · 5 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,088,949 downloads/mo, #4,381 on PyPI
Alternatives
Verify before relying
pip install s5cmd
s5cmd --help- Whether the bundled s5cmd version and its capabilities are documented or versioned separately from the wheel distribution version.
- Performance characteristics and scalability limits for very large file operations or concurrent transfers.
- Integration with AWS credentials and authentication methods beyond standard environment variables.
What it is and what it does
s5cmd is a Python wheel distribution that bundles the official s5cmd executable—a high-performance command-line tool for interacting with S3 object storage and local filesystems. When installed via pip, it automatically places the s5cmd launcher in your PATH, making it immediately available as a system command. The tool is designed for workflows involving large numbers of files, offering wildcard pattern matching, tab completion, and a range of S3 operations (upload, download, copy, delete, and more) with a focus on speed and efficiency.
This package is essentially a distribution wrapper: it contains no Python code of its own and has zero runtime dependencies. It supports a broad range of platforms—Windows (32-bit, 64-bit, ARM64), Linux (Intel, ARM, PowerPC architectures, both glibc and musl libc variants), and macOS (Intel and Apple Silicon). Once installed, you interact with s5cmd as a standalone CLI tool rather than through Python imports, making it suitable for shell scripts, CI/CD pipelines, and interactive terminal use.
Use it for
- Bulk upload or download of hundreds or thousands of files to/from S3 with wildcard patterns instead of listing each file individually.
- Parallel S3 operations in CI/CD pipelines where speed and minimal dependencies are critical.
- Interactive S3 management from the command line with tab completion and pattern matching for exploratory or ad-hoc file operations.
- Cross-platform S3 workflows that need a single, pre-built executable without compiling or managing language-specific dependencies.
- Scripting large-scale data transfers between S3 and local storage in research or cloud-native environments.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need a fast, portable S3 command-line tool and your platform is among the supported architectures.
The MIT license, active maintenance, zero Python dependencies, and broad platform coverage make it a low-friction choice for S3 workflows. Medium install friction is mainly a matter of ensuring the correct binary wheel is available for your OS and CPU architecture—a non-issue on common platforms (x86_64 Linux, Windows, macOS Intel/Apple Silicon).
Install
s5cmd on PyPI
Before you install
Medium install friction due to platform-specific binary wheels. The package is actively maintained with recent releases and has no runtime dependencies, simplifying installation once the correct wheel is selected for your platform.
The correct binary wheel must be available for your platform (Windows, Linux, or macOS) and architecture (x86_64, ARM64, ppc64le, or 32-bit); installation will fail if no matching wheel exists.
License in practice
MIT license (permissive) allows unrestricted use, modification, and distribution. No restrictions on commercial or proprietary use.
Quickstart
pip install s5cmd
s5cmd --helpVerify before relying
- Whether the bundled s5cmd version and its capabilities are documented or versioned separately from the wheel distribution version.
- Performance characteristics and scalability limits for very large file operations or concurrent transfers.
- Integration with AWS credentials and authentication methods beyond standard environment variables.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 339 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 1,088,949 / month, #4,381 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 1 - PlanningIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Scientific/EngineeringTyping :: Typed |
Evidence: s5cmd-0.3.3-py3-none-macosx_11_0_arm64.whl; s5cmd-0.3.3-py3-none-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl; s5cmd-0.3.3-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl; s5cmd-0.3.3-py3-none-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl; s5cmd-0.3.3-py3-none-musllinux_1_2_aarch64.whl; s5cmd-0.3.3-py3-none-musllinux_1_2_ppc64le.whl; s5cmd-0.3.3-py3-none-musllinux_1_2_x86_64.whl; s5cmd-0.3.3-py3-none-win32.whl; s5cmd-0.3.3-py3-none-win_amd64.whl; s5cmd-0.3.3-py3-none-win_arm64.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “s3 command line tool”
- s5cmdProvides a Python wheel distribution that installs the s5cmd…
- s3cmds3cmd is a command-line tool for uploading, downloading, and managing…
- parquet-toolsCommand-line tool to read, inspect, and export Parquet files from…
Give your agent the search over MCP, or paste the wish link into any chat.
More Scientific/Engineering packages
NumPy provides an N-dimensional array object and a comprehensive suite of mathematical, linear algebra, Fourier transform, and random number functions for scientific computing in Python.
pandas provides fast, flexible data structures (Series and DataFrame) for loading, cleaning, transforming, and analyzing labeled or relational data in Python.
scipy provides numerical algorithms for mathematics, science, and engineering—including optimization, integration, linear algebra, Fourier transforms, signal and image processing, and ODE solvers—built on numpy arrays.
scikit-learn provides a comprehensive Python library for supervised and unsupervised machine learning, including classification, regression, clustering, dimensionality reduction, and model evaluation tools built on NumPy and SciPy.
Install it if you need to train, evaluate, or deploy supervised or unsupervised learning models.
dill extends Python's pickle module to serialize and deserialize a much wider range of Python objects, including functions, lambdas, classes, and interpreter sessions, to byte streams for storage or network transmission.
Multiprocess is an enhanced fork of Python's standard multiprocessing library that uses dill for better serialization, allowing you to spawn processes with a threading-like API and share complex objects between them.
Install it if you use multiprocessing and encounter pickle serialization limits with lambdas or complex objects.
See also s3fs · ninja · fs-s3fs · cibuildwheel · fsspec-xrootd · patchelf · installer · ensureconda · s3transfer · cmeel