Package Health Score

78 / 100

security
No known security issues
popularity
Small
maintenance
Healthy
community
Active

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Popularity

Small

GitHub Stars: 183
Forks: 95
Contributors: 70

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package bluesky, we found that it has been starred 183 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Oct 8, 2024
Direct Vulnerabilities: 0
C
0
H
0
M
0
L
Indirect Vulnerabilities: 0
C
0
H
0
M
0
L
License Risk: 0
H
0
M
0
L

All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

BSD-3-Clause

Security Policy

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Maintenance

Healthy

Commit Frequency

Open Issues: 187
Open PR: 51
Last Release: 3 months ago
Last Commit: 6 days ago

Further analysis of the maintenance status of bluesky based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Healthy.

We found that bluesky demonstrates a positive version release cadence with at least one new version released in the past 3 months.

As a healthy sign for on-going project maintenance, we found that the GitHub repository had at least 1 pull request or issue interacted with by the community.

Community

Active

Readme: Yes
Contributing.md: Yes
Code of Conduct: No
Contributors: 70
Funding: No

With more than 10 contributors for the bluesky repository, this is possibly a sign for a growing and inviting community.

We found a way for you to contribute to the project! Looks like bluesky is missing a Code of Conduct.

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Package

Python Versions Compatibility: >=3.8

Age: 8 years
Latest Release: 3 months ago
Dependencies: 6 Direct
Versions: 54
Maintainers: 0
Wheels: OS Independent

Not sure how to use bluesky?

To help you get started, we've collected the most common ways that bluesky is being used within popular public projects.

TUDelft-CNS-ATM / bluesky / bluesky / ui / qtgl / radarwidget.py View on Github

def actnodedataChanged(self, nodeid, nodedata, changed_elems):
        ''' Update buffers when a different node is selected, or when
            the data of the current node is updated. '''
        self.makeCurrent()

        # Shape data change
        if 'SHAPE' in changed_elems:
            if nodedata.polys:
                contours, fills, colors = zip(*nodedata.polys.values())
                # Create contour buffer with color
                buf = np.concatenate(contours)
                update_buffer(self.allpolysbuf, buf)
                buf = np.concatenate(colors)
                update_buffer(self.allpolysclrbuf, buf)
                self.allpolys.set_vertex_count(len(buf) // 2)

                # Create fill buffer
                buf = np.concatenate(fills)
                update_buffer(self.allpfillbuf, buf)
                self.allpfill.set_vertex_count(len(buf) // 2)
            else:
                self.allpolys.set_vertex_count(0)
                self.allpfill.set_vertex_count(0)

        # Trail data change
        if 'TRAILS' in changed_elems:
            if len(nodedata.traillat0):
                update_buffer(self.trailbuf, np.array(

View more ways to use bluesky

Bluesky — An Experiment Specification & Orchestration Engine

Source
PyPI	`pip install bluesky`
Documentation
Releases

Bluesky is a library for experiment control and collection of scientific data and metadata. It emphasizes the following virtues:

Live, Streaming Data: Available for inline visualization and processing.
Rich Metadata: Captured and organized to facilitate reproducibility and searchability.
Experiment Generality: Seamlessly reuse a procedure on completely different hardware.
Interruption Recovery: Experiments are "rewindable," recovering cleanly from interruptions.
Automated Suspend/Resume: Experiments can be run unattended, automatically suspending and resuming if needed.
Pluggable I/O: Export data (live) into any desired format or database.
Customizability: Integrate custom experimental procedures and commands, and get the I/O and interruption features for free.
Integration with Scientific Python: Interface naturally with numpy and Python scientific stack.

Bluesky Documentation.

The Bluesky Project enables experimental science at the lab-bench or facility scale. It is a collection of Python libraries that are co-developed but independently useful and may be adopted a la carte.

Bluesky Project Documentation.

See https://bluesky.github.io/bluesky for more detailed documentation.

bluesky dependencies

cycler historydict msgpack msgpack-numpy opentelemetry-api toolz

FAQs

What is bluesky?

Experiment specification & orchestration. Visit Snyk Advisor to see a full health score report for bluesky, including popularity, security, maintenance & community analysis.

Is bluesky popular?

The python package bluesky receives a total of 8,428 weekly downloads. As such, bluesky popularity was classified as small. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is bluesky well maintained?

We found that bluesky demonstrated a healthy version release cadence and project activity. It has a community of 70 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is bluesky safe to use?

The python package bluesky was scanned for known vulnerabilities and missing license, and no issues were found. Thus the package was deemed as safe to use. See the full health analysis review.

Last updated on 24 December-2024, at 07:52 (UTC).

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bluesky

Experiment specification & orchestration. For more information about how to use this package see README

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Bluesky — An Experiment Specification & Orchestration Engine

bluesky dependencies

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Commit Frequency

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Not sure how to use bluesky?

Bluesky — An Experiment Specification & Orchestration Engine

bluesky dependencies

FAQs

What is bluesky?

Is bluesky popular?

Is bluesky well maintained?

Is bluesky safe to use?

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Source Code

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