--- id: bluesky version: "1.15.1" license: BSD 3-Clause License Copyright (c) 2015, Brookhaven National Laboratory All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided… (full text in the JSON record) license_treatment: permissive maintenance: active --- # bluesky — Experiment specification & orchestration. License: permissive · Maintenance: active · Downloads: 92.3K/mo ## What it is and what it does Bluesky is a Python library for specifying and running scientific experiments with automatic orchestration, live data streaming, and rich metadata capture. It abstracts experiment logic from hardware details, allowing the same procedure to run on different instruments without modification. The library emphasizes reproducibility, interruption recovery (experiments can be paused and resumed cleanly), and integration with the scientific Python stack (numpy, msgpack for serialization, tqdm for progress, toolz for functional utilities, and opentelemetry-api for observability). Typical use involves defining an experiment as a plan—a generator-based specification of detector readings, motor movements, and data collection steps—then submitting it to a RunEngine that handles execution, live data emission, metadata organization, and pluggable I/O backends. This design separates experiment intent from hardware control, enabling reuse across labs and facilities. The library targets scientific facilities and lab-bench automation where reproducibility, traceability, and unattended operation are priorities. Use it for: - Define a synchrotron beamline scan procedure once and reuse it across different beamlines with different hardware. - Stream detector data live during an experiment for real-time visualization and early stopping decisions. - Automatically suspend a long-running materials characterization experiment if a resource becomes unavailable, then resume from the checkpoint. - Capture and organize experimental metadata (sample ID, conditions, operator, timestamps) alongside raw data for reproducibility audits. - Export live experimental data to multiple formats or databases simultaneously via pluggable I/O handlers. - Integrate custom laboratory procedures and commands while inheriting interruption recovery and metadata management for free. ## Worth the install? AI-flagged interpretation of the facts above — verify before relying. Bluesky is an experiment control and scientific data collection library that orchestrates experimental procedures, captures rich metadata, and streams live data for inline processing and visualization. Yes, if you are building or automating scientific experiments at a facility or lab scale and need hardware-agnostic experiment specification, live data streaming, and reproducibility guarantees. The active maintenance, low install friction, permissive license, and integration with standard scientific Python packages make it a solid foundation. The Alpha status and lack of known vulnerabilities are not blockers, but verify that the library's maturity and feature set align with your facility's production requirements before committing to it as a core dependency. ## Install pip install bluesky uv add bluesky poetry add bluesky ## Installing bluesky Before you install: Low install friction with a pure Python wheel. Active maintenance with a recent commit on 2026-08-13 and a release 100 days ago. Ten runtime dependencies are all standard scientific Python packages (numpy, msgpack, tqdm, toolz, opentelemetry-api, and others), suggesting a stable, well-integrated ecosystem. License in practice: BSD 3-Clause License (permissive). You may use, modify, and distribute bluesky freely in commercial and private projects, provided you retain the copyright notice and disclaimer. No copyleft obligations. Quickstart: pip install bluesky from bluesky import RunEngine from bluesky.plans import scan RE = RunEngine({}) # Define and execute an experiment plan RE(scan([detector], motor, start, stop, num_points)) Requires Python 3.10 or later. Bluesky is designed for integration with hardware control systems and scientific instruments; standalone use requires appropriate detector and motor objects. Verify before relying: - Specific hardware platforms or control systems that bluesky officially supports or integrates with. - Whether the interruption recovery and suspend/resume features work with all experiment types or have limitations. - Performance characteristics or scalability limits for large-scale or high-frequency data collection. - Maturity of the Alpha status (Development Status :: 3) relative to production use in scientific facilities. ## Package facts - License: BSD 3-Clause License Copyright (c) 2015, Brookhaven National Laboratory All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided… (full text in the JSON record) (permissive) - Python support: supports_current - Install friction: low - Maintenance: active - Downloads: 92.3K/month (top 15,000 on PyPI) - Known vulnerabilities: none known ## Tags experiment control and orchestration, scientific data collection framework, lab automation and experiment management, streaming scientific data processing, reproducible experiment specification, hardware-agnostic experiment procedures, live data visualization and collection, experiment-orchestration, scientific-data-collection, lab-automation [View on SkillFed](https://skillfed.io/packages/bluesky) · [View on PyPI](https://pypi.org/project/bluesky/)