event-model
Data model used by the bluesky ecosystem.
Decision gist · record as of 2026-08-14
Yes. If you work with bluesky data or need to emit data in bluesky-compatible format, this is a required dependency. Low install friction, active maintenance, permissive license, no known vulnerabilities, and supports current Python versions. Even as a transitive dependency it is stable and lightweight.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Low friction installation with three lightweight runtime dependencies (jsonschema, numpy, typing_extensions).
- Active maintenance with a release 72 days ago and recent commits; supports Python 3.10 through 3.13.
License · maintenance · safety
permissive license (permissive) — BSD 3-Clause License permits commercial and private use with attribution and liability disclaimers; no restrictions on derivative works or redistribution.
last release 2026-06-03 (72 days) · last repo commit 2026-08-03 · 24 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 89,877 downloads/mo, #13,630 on PyPI
Alternatives
Verify before relying
pip install event-model
import event_model
# Validate a Start document
start_doc = {"uid": "...", "time": 0.0}
event_model.compose_run(metadata={"proposal": "..."})- Whether the package provides runtime document composition helpers beyond schema validation.
- What transformations between document formats are supported beyond validation.
- Whether numpy is used for data handling or only as a transitive dependency.
What it is and what it does
event-model is the formal data schema and validation toolkit for the bluesky scientific data ecosystem. It defines how experimental metadata, measurements, and device state are organized into structured documents (Start, Event, EventDescriptor, Stop, etc.) that flow through data collection and analysis pipelines. The package provides Python tools to compose, validate, and transform these documents according to the bluesky specification.
The model is designed around the principle that rich metadata recorded alongside measured data enables better research and reproducibility. Documents capture sample information, experimental intent, detector calibrations, device configurations, and the actual measured data in a standardized format. This package is the foundation for any tool or workflow that needs to work with bluesky-collected data or emit data in bluesky-compatible format.
Use it for
- Validate experiment documents produced by bluesky beamline control systems before storage or analysis.
- Compose properly-structured Start, Event, and Stop documents when building custom data acquisition workflows.
- Transform or migrate experiment data between different storage backends while maintaining schema compliance.
- Build analysis pipelines that consume bluesky-formatted streaming data with guaranteed document structure.
- Integrate external data sources into bluesky workflows by wrapping them in compliant document schemas.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
If you work with bluesky data or need to emit data in bluesky-compatible format, this is a required dependency. Low install friction, active maintenance, permissive license, no known vulnerabilities, and supports current Python versions. Even as a transitive dependency it is stable and lightweight.
Install
event-model on PyPI
Before you install
Low friction installation with three lightweight runtime dependencies (jsonschema, numpy, typing_extensions). Active maintenance with a release 72 days ago and recent commits; supports Python 3.10 through 3.13.
Requires Python 3.10 or later.
License in practice
BSD 3-Clause License permits commercial and private use with attribution and liability disclaimers; no restrictions on derivative works or redistribution.
Quickstart
pip install event-model
import event_model
# Validate a Start document
start_doc = {"uid": "...", "time": 0.0}
event_model.compose_run(metadata={"proposal": "..."})Verify before relying
- Whether the package provides runtime document composition helpers beyond schema validation.
- What transformations between document formats are supported beyond validation.
- Whether numpy is used for data handling or only as a transitive dependency.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesjsonschemanumpytyping_extensions |
| Maintenance | Actively maintained 72 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 89,877 / month, #13,630 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 3 - AlphaLicense :: OSI Approved :: BSD LicenseProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13 |
Evidence: event_model-1.24.0-py3-none-any.whl
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See also bluesky · schema-salad · xmlschema · asdf-transform-schemas · ophyd-async · ophyd · sigstore-models · pandas-schema · coffea · asdf-coordinates-schemas