Package Health Score

87 / 100

security
No known security issues
popularity
Popular
maintenance
Healthy
community
Active

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Popularity

Popular

GitHub Stars: 3.7K
Forks: 1.08K
Contributors: 260

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package kserve, we found that it has been starred 3,703 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Oct 16, 2024
Direct Vulnerabilities: 0
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0
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0
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0
L
Indirect Vulnerabilities: 0
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0
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License Risk: 0
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0
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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

Apache-2.0

Security Policy

Yes

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Maintenance

Healthy

Commit Frequency

Open Issues: 377
Open PR: 71
Last Release: 2 months ago
Last Commit: 12 days ago

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

We found that kserve 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: 260
Funding: No

A good and healthy external contribution signal for kserve 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 kserve is missing a Code of Conduct.

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Package

Python Versions Compatibility: <3.13,>=3.9

Age: 3 years
Latest Release: 2 months ago
Dependencies: 0 Direct
Versions: 31
Maintainers: 0
Wheels: OS Independent

Readme

KServe Python SDK

Python SDK for KServe Server and Client.

Installation

KServe Python SDK can be installed by pip or poetry.

pip install

pip install kserve

To install Kserve with storage support

pip install kserve[storage]

Poetry

Install via Poetry.

make dev_install

To install Kserve with storage support

poetry install -E storage

poetry install --extras "storage"

KServe Python Server

KServe's python server libraries implement a standardized library that is extended by model serving frameworks such as Scikit Learn, XGBoost and PyTorch. It encapsulates data plane API definitions and storage retrieval for models.

It provides many functionalities, including among others:

Registering a model and starting the server
Prediction Handler
Pre/Post Processing Handler
Liveness Handler
Readiness Handlers

It supports the following storage providers:

Google Cloud Storage with a prefix: "gs://"
- By default, it uses GOOGLE_APPLICATION_CREDENTIALS environment variable for user authentication.
- If GOOGLE_APPLICATION_CREDENTIALS is not provided, anonymous client will be used to download the artifacts.
S3 Compatible Object Storage with a prefix "s3://"
- By default, it uses S3_ENDPOINT, AWS_ACCESS_KEY_ID, and AWS_SECRET_ACCESS_KEY environment variables for user authentication.
Azure Blob Storage with the format: "https://{$STORAGE_ACCOUNT_NAME}.blob.core.windows.net/{$CONTAINER}/{$PATH}"
- By default, it uses anonymous client to download the artifacts.
- For e.g. https://kfserving.blob.core.windows.net/triton/simple_string/
Local filesystem either without any prefix or with a prefix "file://". For example:
- Absolute path: /absolute/path or file:///absolute/path
- Relative path: relative/path or file://relative/path
- For local filesystem, we recommended to use relative path without any prefix.
Persistent Volume Claim (PVC) with the format "pvc://{$pvcname}/[path]".
- The pvcname is the name of the PVC that contains the model.
- The [path] is the relative path to the model on the PVC.
- For e.g. pvc://mypvcname/model/path/on/pvc
Generic URI, over either HTTP, prefixed with http:// or HTTPS, prefixed with https://. For example:
- https://.com/model.joblib
- http://.com/model.joblib

Metrics

For latency metrics, send a request to /metrics. Prometheus latency histograms are emitted for each of the steps (pre/postprocessing, explain, predict). Additionally, the latencies of each step are logged per request.

Metric Name	Description	Type
request_preprocess_seconds	pre-processing request latency	Histogram
request_explain_seconds	explain request latency	Histogram
request_predict_seconds	prediction request latency	Histogram
request_postprocess_seconds	pre-processing request latency	Histogram

KServe Client

Getting Started

KServe's python client interacts with KServe control plane APIs for executing operations on a remote KServe cluster, such as creating, patching and deleting of a InferenceService instance. See the Sample for Python SDK Client to get started.

Documentation for Client API

Please review KServe Client API docs.

Documentation For Models

FAQs

What is kserve?

KServe Python SDK. Visit Snyk Advisor to see a full health score report for kserve, including popularity, security, maintenance & community analysis.

Is kserve popular?

The python package kserve receives a total of 12,605 weekly downloads. As such, kserve popularity was classified as a popular. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is kserve well maintained?

We found that kserve demonstrated a healthy version release cadence and project activity. It has a community of 260 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is kserve safe to use?

The python package kserve 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 20 December-2024, at 17:03 (UTC).

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