$npx skillfedfor your agent

neptune

Neptune Client

SkipPyPI Python ModulesReleased Mar 2026144.6K downloads / moApache-2.0Pure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — neptune-1.14.0.post2-py3-none-any.whl
v1.14.0.post2 · released 2026-03-17 · Python <4.0,>=3.8 · 19 runtime deps: GitPython, Pillow, PyJWT, boto3, bravado, click, future, oauthlib

No. The repository is archived and the package is abandoned. While it remains at production/stable status and has no known vulnerabilities, the fact sheet explicitly directs users to neptune-client-scale for new work. Installing this package locks you into a legacy client with no active maintenance or security updates.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires Python 3.8 or later; requires credentials and network access to a Neptune app instance.
  • Low install friction with a pure-wheel distribution.
  • However, the repository is archived and marked as abandoned; the package is no longer actively maintained, though it remains at production/stable status.

License · maintenance · safety

Apache-2.0 (permissive) — Licensed under Apache-2.0 (permissive), allowing broad use, modification, and distribution with minimal restrictions.

last release 2026-03-17 (150 days) · last repo commit 2026-03-17 · 623 stars · archived

0 known vulnerabilities (OSV.dev, 2026-08-14) · 144,595 downloads/mo, #11,147 on PyPI

Verify before relying

pip install neptune

import neptune
run = neptune.init_run()
  • Whether Neptune 2.x is still compatible with current Neptune app infrastructure or if migration to neptune-client-scale is required for ongoing use.
  • Support status and security patch availability given the archived repository status.
Same gist for agents: .md · .json

What it is and what it does

Neptune is a client library for the Neptune MLOps platform, designed to integrate with machine learning workflows to track experiments, log metrics and artifacts, and manage model metadata. It provides integration points for logging training runs, model parameters, and results to a centralized Neptune app instance, enabling teams to organize and compare ML work across projects.

The package depends on a broad set of utilities including requests, pandas, boto3, and websocket-client for cloud storage integration, OAuth authentication, and real-time communication. It supports Python 3.8 through 3.14 on multiple operating systems. The fact sheet indicates this is the legacy client for Neptune app version 2.x; the project repository is now archived, and users are directed toward neptune-client-scale for new work.

Use it for

  • Log and track ML experiment metrics, hyperparameters, and model performance during training runs.
  • Store and retrieve model artifacts and training outputs in a centralized Neptune workspace.
  • Compare multiple experiment runs side-by-side to identify the best model configurations.
  • Integrate experiment tracking into existing ML pipelines and CI/CD workflows.
  • Manage team collaboration on ML projects with shared experiment history and metadata.

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

Skip

No.

The repository is archived and the package is abandoned. While it remains at production/stable status and has no known vulnerabilities, the fact sheet explicitly directs users to neptune-client-scale for new work. Installing this package locks you into a legacy client with no active maintenance or security updates.

Install

neptune on PyPI

Before you install

Low install friction with a pure-wheel distribution. However, the repository is archived and marked as abandoned; the package is no longer actively maintained, though it remains at production/stable status.

Requires Python 3.8 or later; requires credentials and network access to a Neptune app instance.

License in practice

Licensed under Apache-2.0 (permissive), allowing broad use, modification, and distribution with minimal restrictions.

Quickstart

pip install neptune

import neptune
run = neptune.init_run()

Verify before relying

  • Whether Neptune 2.x is still compatible with current Neptune app infrastructure or if migration to neptune-client-scale is required for ongoing use.
  • Support status and security patch availability given the archived repository status.

Package facts

LicenseApache-2.0 permissive
Python supportSupports the current Python release <4.0,>=3.8
Install frictionLow. Pure-Python wheel
Runtime dependencies
19 packages
GitPythonPillowPyJWTboto3bravadoclickfutureoauthlibpackagingpandaspsutilrequestsrequests-oauthlibsetuptoolssixswagger-spec-validatortyping-extensionsurllib3websocket-client
MaintenanceAbandoned 150 days since the last release
Last repo commit repository archived
First released
Downloads144,595 / month, #11,147 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Development Status :: 5 - Production/StableEnvironment :: ConsoleIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseNatural Language :: EnglishOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIXOperating System :: UnixProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Programming Language :: Python :: Implementation :: CPythonTopic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Software Development :: Libraries :: Python Modules

Evidence: neptune-1.14.0.post2-py3-none-any.whl

Tags

Capabilities
ML experiment trackingmachine learning metadata storemodel registry pythonexperiment logging MLOpsML model tracking client
Topics
mlopsexperiment-trackinglegacy
PyPI keywords
MLOpsML Experiment TrackingML Model RegistryML Model StoreML Metadata Store

Let your AI agent find packages like this

Example. Real query, live index.

You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.

wish › “ML experiment tracking”

  • neptuneNeptune is a Python client for experiment tracking and ML metadata…
  • tracemlTraceML tracks metrics, parameters, artifacts, and data references…
  • sagemaker-experimentsTracks machine learning experiments, trials, and trial components in…

Give your agent the search over MCP, or paste the wish link into any chat.

More Python Modules packages

idna Worth it
PyPI · Python Modules · released Jun 2026

Converts domain names between Unicode and ASCII-compatible encoding (Punycode) according to IDNA 2008 and Unicode Technical Standard 46, with security validation and broader script coverage than the standard library.

Install it if you work with internationalized domain names, need to validate domains, or use HTTP clients that depend on it transitively.

BSD-3-Clausepure Python · 3.9+
1.8Bdownloads / mo
setuptools Worth it
PyPI · Python Modules · released Aug 2026

Setuptools is a Python build backend and package management tool that handles building, distributing, and installing Python packages, including support for C/C++ extension modules.

MITpure Python · 3.10+
1.6Bdownloads / mo
PyYAML Worth it
PyPI · Python Modules · released Sep 2025

PyYAML parses and emits YAML 1.1 data format, enabling serialization and deserialization of configuration files and Python objects to and from human-readable YAML text.

MITcompiled wheel · 3.8+
1.2Bdownloads / mo
pydantic Worth it
PyPI · Python Modules · released May 2026

Pydantic validates Python data structures against type hints, coercing and checking input at runtime to ensure it matches a declared schema.

MITpure Python · 3.9+
1.1Bdownloads / mo
annotated-types Worth it
PyPI · Python Modules · released Jul 2026

Provides reusable metadata objects for use with PEP-593 `typing.Annotated` to express common constraints like bounds, collection sizes, and predicates on types.

Install it if you use or build libraries that need to express type constraints in a standardized, inspectable way—or if you want to annotate your own types with…

MITpure Python · 3.10+
871.3Mdownloads / mo
typing-inspection Worth it
PyPI · Python Modules · released Aug 2026

Provides runtime tools to inspect and introspect Python type annotations, enabling programmatic examination of type hints at execution time.

MITpure Python · 3.10+
783.0Mdownloads / mo

See also arthur-client · neptune-api · neptune-scale · neptune-fetcher · neptune-query · dvclive · dvc-studio-client · azureml-mlflow · wandb · comet-ml