https://github.com/bluesky/tutorials

tutorial materials related to data acquisition, management, and analysis
https://github.com/bluesky/tutorials

bluesky python tutorial

Last synced: about 2 months ago
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tutorial materials related to data acquisition, management, and analysis

• Host: GitHub
• URL: https://github.com/bluesky/tutorials
• Owner: bluesky
• License: bsd-3-clause
• Created: 2015-10-09T17:20:56.000Z (about 9 years ago)
• Default Branch: main
• Last Pushed: 2023-04-25T15:56:26.000Z (over 1 year ago)
• Last Synced: 2023-04-25T17:03:07.422Z (over 1 year ago)
• Topics: bluesky, python, tutorial
• Language: Jupyter Notebook
• Homepage: https://mybinder.org/v2/gh/bluesky/tutorials/main?urlpath=lab
• Size: 4.48 MB
• Stars: 14
• Watchers: 11
• Forks: 27
• Open Issues: 24
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

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README

        
[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/bluesky/tutorials/main)

# Bluesky Tutorials

This is a collection of tutorials on data acquisition and analysis using Bluesky

and scientific Python generally. There are a couple ways to use it.

* Try it in the interactive sandbox in the cloud at

  https://mybinder.org/v2/gh/bluesky/tutorials/main (**recommended**).

* Browse the content non-interactively at https://blueskyproject.io/tutorials.

* Use Docker, running `docker run -p 8888:8888 nsls2/tutorials:latest`.

* Download this content and run it on your local machine. This is not

  recommended for novices. See {doc}`INSTALLATION`.

## Survey

Took our tutorial? Let us know how you thought of it so we can better improve

it!

[Survey](https://goo.gl/forms/WAWhkAIvEGVzIUdf2)

## References

* [Bluesky Software Documentation Landing Page](https://blueskyproject.io)

* [Bluesky Documentation](https://blueskyproject.io/bluesky)

* [Ophyd Documentation](https://blueskyproject.io/ophyd)

* [Databroker Documentation](https://blueskyproject.io/databroker)

* [Our Gitter Chat Channel](https://gitter.im/NSLS-II/DAMA) (come here for questions)

* [Python Help](https://www.oreilly.com/programming/free/files/python-for-scientists.pdf) : A collection of Python tutorials geared towards scientific data analysis.