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rucio-clients

Rucio client package

rucio-clients v41.1.1 118.7K downloads/30d#12,105 on PyPI307
Permissive license Apache-2.0 Active released

What it is and what it does

Rucio-clients is the client-side package for Rucio, a data management framework originally built for the ATLAS high-energy physics experiment but now used across multiple LHC experiments and scientific communities. It provides both command-line tools and Python APIs to interact with a Rucio server, allowing users to organize data into scopes and datasets, manage replicas across distributed storage systems, and retrieve files using customizable policies.

The package depends on common HTTP and utility libraries (requests, urllib3, click, tabulate, rich) to handle communication, formatting, and user interaction. It is designed for system administrators and data scientists who need to work with large volumes of scientific data spread across heterogeneous storage backends—such as tape archives, cloud storage, and on-premise data centers—as a single federated entity. The framework handles distributed data recovery and adaptive replication automatically according to configured policies.

Use it for:

  • Query and retrieve data files stored across multiple ATLAS or LHC experiment data centers from a single interface.
  • Replicate datasets to new storage locations with automatic policy-driven placement and recovery.
  • Organize petabyte-scale scientific datasets into scopes and datasets for collaborative research teams.
  • Automate bulk data transfers and lifecycle management across globally distributed storage systems.
  • Monitor and manage data availability and redundancy across heterogeneous storage technologies.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Rucio-clients provides command-line and programmatic access to Rucio, a distributed scientific data management framework that organizes, replicates, and retrieves large volumes of data across globally distributed storage systems.

Yes, if you work with a Rucio-managed data infrastructure (ATLAS, LHC experiments, or other institutions running Rucio servers). The package is production-stable, actively maintained, has no known vulnerabilities, and provides the only official way to interact with Rucio from Python. Not relevant for general-purpose data management outside a Rucio deployment.

Install

rucio-clients on PyPI

pip

pip install rucio-clients

uv

uv add rucio-clients

poetry

poetry add rucio-clients

Installing rucio-clients

Before you install

Low friction install with a pure-Python wheel and stable maintenance. Last release was 15 days ago, repository is active with recent commits, and the package has been in production since 2016. Supports current Python versions (3.9+).

License in practice

Apache-2.0 permissive license allows use in most commercial and open-source projects without significant restrictions.

Quickstart

pip install rucio-clients

from rucio.client.client import Client
client = Client()
replicas = client.list_replicas(dids=[{'scope': 'scope', 'name': 'file.txt'}])

Requires Python 3.9 or later; Rucio server infrastructure must be accessible for the client to connect to.

Verify before relying

  • Whether the package works offline or requires continuous server connectivity.
  • Performance characteristics when managing very large numbers of files or replicas.
  • Specific authentication mechanisms supported beyond what the client library provides.

Package facts

License Apache-2.0 (permissive)
Python support supports the current Python release (>=3.9)
Install friction low — pure-Python wheel
Runtime dependencies 9 — click, requests, urllib3, dogpile-cache, packaging, tabulate, jsonschema, rich, typing_extensions
Maintenance actively maintained — 15 days since the last release
Last repo commit
First released
Downloads 118,735/month — #12,105 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: rucio_clients-41.1.1-py3-none-any.whl

Development Status :: 5 - Production/StableIntended Audience :: Information TechnologyIntended Audience :: System AdministratorsNatural Language :: EnglishOperating System :: POSIX :: LinuxProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.9

Tags

distributed data managementscientific data accessfederated storage clientdata replication and recoverylarge-scale data organizationmulti-site data managementATLAS data managementLHC data framework
scientific-datadistributed-storagehigh-energy-physics

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