neptune

library1.14.0.post2pypypi✓ verified 82d ago

Neptune is an MLOps platform for experiment tracking and model management, focusing on machine learning metadata. The `neptune-client` Python library provides the interface to log, store, display, and compare MLOps artifacts and metadata directly from your code. It is currently at version 1.14.0.post2, with active development including an upcoming 2.x branch, and releases frequent updates.

ai-ml observability devops

pip install neptune

github ↗package ↗homepage ↗docs ↗

INSTALL

IMPORT

SIG · NEPTUNE

neptune

ai-mlpythonv1.14.0.post2

Install

15.6s avg

Import

10637ms

Disk

255MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v1.14.0.post2 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.920 runs

installs and imports cleanly · install 0.0s · import 11.058s · 246MB

glibc

py 3.10–3.920 runs

installs and imports cleanly · install 15.6s · import 10.215s · 240MB

255MB installed

● package 255MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

Run

✓ from neptune import Run

✗ import neptune; run = neptune.init_run(...)

This quickstart initializes a Neptune run, logs basic parameters and metrics, tracks a placeholder for a model checkpoint, and then stops the run. Ensure you have your `NEPTUNE_API_TOKEN` and `NEPTUNE_PROJECT` (e.g., 'your_workspace/your_project') set as environment variables or passed directly to `init_run`.

import neptune import os import random # Initialize a new Neptune run # Replace 'YOUR_WORKSPACE/YOUR_PROJECT_NAME' with your actual project name, e.g., 'common/quickstart-python' # Set NEPTUNE_API_TOKEN and NEPTUNE_PROJECT as environment variables for production use. run = neptune.init_run( project=os.environ.get("NEPTUNE_PROJECT", "common/quickstart-python"), api_token=os.environ.get("NEPTUNE_API_TOKEN", "YOUR_NEPTUNE_API_TOKEN"), # Replace with your token if not using env var name="Minimal Example", tags=["quickstart", "example"] ) # Log some parameters params = {"learning_rate": 0.001, "optimizer": "Adam"} run["parameters"] = params # Log some metrics for i in range(10): run["train/loss"].append(random.uniform(0.1, 0.9)) run["train/accuracy"].append(random.uniform(0.5, 0.99)) # Log a model checkpoint placeholder (e.g., a path or a link) run["model_checkpoints/best_model"].track_files("s3://my-bucket/models/best_model.pth") # Stop the run run.stop() print(f"Neptune run URL: {run.get_url()}")

neptune --version

Debug

Known issues

breakingPython 3.7 is no longer supported. Ensure your environment uses Python 3.8 or newer.

fix

Upgrade your Python environment to 3.8 or a later compatible version (e.g., 3.9, 3.10, 3.11).

affects: >=1.12.0

deprecatedThe `model` and `model_version` endpoints within the Neptune API are deprecated. Users should migrate to the new `Model` and `ModelVersion` objects.

fix

Refer to Neptune's official documentation for updated methods to manage models and model versions using the `neptune.init_model()` and `neptune.init_model_version()` functions.

affects: >=1.12.0

gotchaThe `neptune.init()` function is deprecated. Using it will lead to warnings and potentially errors in future versions.

fix

Replace all instances of `neptune.init()` with `neptune.init_run()` for initializing experiment runs.

affects: >=1.0.0

gotchaWhen uploading HTML objects with `run['path'].upload()` or using `File.as_html()`, the default behavior is to embed the entire Plotly.js library (approx. 3MB) within the HTML. For Neptune SaaS users, this can significantly increase object size.

fix

For smaller HTML objects, especially with Neptune SaaS, pass `include_plotlyjs='cdn'` to the `upload()` or `as_html()` method, which loads Plotly.js from a CDN.

affects: >=1.13.0

gotchaYou must set the `NEPTUNE_API_TOKEN` and `NEPTUNE_PROJECT` environment variables or pass them directly to `neptune.init_run()` to connect to your Neptune project. Forgetting to do so is a common cause of connection errors.

fix

Define `NEPTUNE_API_TOKEN` and `NEPTUNE_PROJECT` in your environment or explicitly pass `api_token` and `project` arguments to `neptune.init_run()`.

affects: all

Upgrade

Version history

1.14.0.post2latest on PyPI · released Mar 17, 2026

Audit

Dependencies

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Agent activity

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OpenAI (training)

Resources

githubhttps://github.com/neptune-ai/neptune-client ↗

packagehttps://pypi.org/project/neptune/ ↗

homepagehttps://neptune.ai/ ↗

docshttps://docs.neptune.ai/ ↗