This release is a pre-release and may not be stable for production use.
Celebi
Celebi is a data analysis management toolkit designed for high-energy physics research.
It provides a structured environment for organizing projects, tasks, algorithms, and data, enabling reproducible, traceable, and collaborative scientific workflows.
Celebi is particularly suited for complex analysis chains common in HEP, where dependency tracking, provenance, and re-execution are critical.
Key Features and Benefits
-
Structured Organization
Clear separation of projects, data, algorithms, and tasks with a well-defined hierarchy. -
Dependency Tracking
Automatic tracking of relationships between data, algorithms, and tasks, forming a directed acyclic graph (DAG). -
Impressions (Versioning)
Built-in impressions system to snapshot important results, configurations, and object states over time. -
Reproducibility
Complete capture of workflow structure, parameters, inputs, and execution environments. -
Adaptability
Modify algorithms or parameters and re-run only affected downstream tasks. -
Collaboration
Share projects and workflows consistently across users and environments.
Core Concepts
- Project – A self-contained analysis workspace.
- Data – Raw or derived datasets registered and managed by Celebi.
- Algorithm – A reusable, self-contained piece of code or script.
- Task – A concrete execution instance of an algorithm with specific inputs and parameters.
- Runner – An execution backend (local, batch system, remote, etc.).
- Impression – A recorded snapshot of key outputs or analysis states.
Installation
git clone https://github.com/CelebiProjects/Celebi.git
cd Celebi
pip install .
Getting Started
celebi init
celebi
Documentation
- Online Docs: http://celebi.readthedocs.io/en/latest/
- Ask DeepWiki: https://deepwiki.com/CelebiProjects/Celebi
License
Apache License, Version 2.0
Author
Mingrui Zhao
- 2013–2017 — Center of High Energy Physics, Tsinghua University
- 2017–2025 — Department of Nuclear Physics, China Institute of Atomic Energy
- 2020–2025 — Niels Bohr Institute, University of Copenhagen
- 2025–now — Peking University
Metadata
Release files for CelebiChrono 1.0.0b2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| celebichrono-1.0.0b2.tar.gz | 237.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| celebichrono-1.0.0b2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 535.1 kB
Release files / celebichrono-1.0.0b2.tar.gz
| Download URL | celebichrono-1.0.0b2.tar.gz |
|---|---|
| Size | 237.7 kB |
| Tags | Source |
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No |
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twine/7.0.0 CPython/3.13.12
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Release files / celebichrono-1.0.0b2-py3-none-any.whl
| Download URL | celebichrono-1.0.0b2-py3-none-any.whl |
|---|---|
| Size | 297.4 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.12
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