View kfp on Snyk Open Source Advisor

Package Health Score

85 / 100

security
Security review needed
popularity
Key ecosystem project
maintenance
Sustainable
community
Active

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Popularity

Key ecosystem project

GitHub Stars: 3.43K
Forks: 1.54K
Contributors: 380

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package kfp, we found that it has been starred 3,431 times.

Security

Security review needed

Security and license risk for latest version

Release Date: Feb 14, 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
9
M
0
L

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

License

Apache-2.0

Security Policy

Yes

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Maintenance

Sustainable

Commit Frequency

Open Issues: 383
Open PR: 229
Last Release: 2 months ago
Last Commit: 8 days ago

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

We found that kfp 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: 380
Funding: No

A good and healthy external contribution signal for kfp project, which invites more than one hundred open source maintainers to collaborate on the repository.

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

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Package

Python Versions Compatibility: >=3.7.0,<3.13.0

Age: 5 years
Latest Release: 2 months ago
Dependencies: N/A
Versions: 132
Maintainers: 2
Wheels: No

Not sure how to use kfp?

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

kubeflow / pipelines / test / sample-test / check_notebook_results.py View on Github

try:
            with open(DEFAULT_CONFIG, 'r') as f:
                raw_args = yaml.safe_load(f)
        except yaml.YAMLError as yamlerr:
            raise RuntimeError('Illegal default config:{}'.format(yamlerr))
        except OSError as ose:
            raise FileExistsError('Default config not found:{}'.format(ose))
        else:
            test_timeout = raw_args['test_timeout']

        if self._run_pipeline:
            experiment = self._experiment_name
            ###### Initialization ######
            host = 'ml-pipeline.%s.svc.cluster.local:8888' % self._namespace
            client = Client(host=host)

            ###### Get experiments ######
            experiment_id = client.get_experiment(experiment_name=experiment).id

            ###### Get runs ######
            list_runs_response = client.list_runs(page_size=RUN_LIST_PAGE_SIZE,
                                                  experiment_id=experiment_id)

            ###### Check all runs ######
            for run in list_runs_response.runs:
                run_id = run.id
                response = client.wait_for_run_completion(run_id, test_timeout)
                succ = (response.run.status.lower()=='succeeded')
                utils.add_junit_test(test_cases, 'job completion',
                                     succ, 'waiting for job completion failure')

View more ways to use kfp

Kubeflow Pipelines is a platform for building and deploying portable, scalable machine learning workflows based on Docker containers within the Kubeflow project.

Use Kubeflow Pipelines to compose a multi-step workflow (pipeline) as a graph of containerized tasks using Python code and/or YAML. Then, run your pipeline with specified pipeline arguments, rerun your pipeline with new arguments or data, schedule your pipeline to run on a recurring basis, organize your runs into experiments, save machine learning artifacts to compliant artifact registries, and visualize it all through the Kubeflow Dashboard.

Installation

To install kfp, run:

pip install kfp

Getting started

The following is an example of a simple pipeline that uses the kfp v2 syntax:

from kfp import dsl
import kfp


@dsl.component
def add(a: float, b: float) -&gt; float:
    '''Calculates sum of two arguments'''
    return a + b


@dsl.pipeline(
    name='Addition pipeline',
    description='An example pipeline that performs addition calculations.')
def add_pipeline(
    a: float = 1.0,
    b: float = 7.0,
):
    first_add_task = add(a=a, b=4.0)
    second_add_task = add(a=first_add_task.output, b=b)


client = kfp.Client(host='')
client.create_run_from_pipeline_func(
    add_pipeline, arguments={
        'a': 7.0,
        'b': 8.0
    })

FAQs

What is kfp?

Kubeflow Pipelines SDK. Visit Snyk Advisor to see a full health score report for kfp, including popularity, security, maintenance & community analysis.

Is kfp popular?

The python package kfp receives a total of 1,480,284 weekly downloads. As such, kfp popularity was classified as a key ecosystem project. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is kfp well maintained?

We found indications that kfp maintenance is sustainable demonstrating some project activity. We saw a total of 380 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is kfp safe to use?

While scanning the latest version of kfp, we found that a security review is needed. A total of 0 vulnerabilities or license issues were detected. See the full security scan results.

Last updated on 19 April-2024, at 09:10 (UTC).

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Kubeflow Pipelines SDK For more information about how to use this package see README

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Package

Not sure how to use kfp?

Installation

Getting started

FAQs

What is kfp?

Is kfp popular?

Is kfp well maintained?

Is kfp safe to use?

Build a secure application checklist

Select a recommended open source package

Scan your app for vulnerabilities

Fix identified vulnerabilities

Monitor for new issues

Package Health Score

Explore Similar Packages

Direct Usage Popularity

Security and license risk for latest version

Commit Frequency

Embed Package Health Score Badge

Keep your project healthy

Check your requirements.txt

Snyk Vulnerability Scanner

Not sure how to use kfp?

Installation

Getting started

FAQs

What is kfp?

Is kfp popular?

Is kfp well maintained?

Is kfp safe to use?

Build a secure application checklist

Select a recommended open source package

Scan your app for vulnerabilities

Source Code

Open Source

Container

Config

Fix identified vulnerabilities

Monitor for new issues