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arthur-client

Arthur Python API Client Library

arthur-client v1.4.2333 96.5K downloads/30d#13,209 on PyPI
Permissive license MIT Active released

What it is and what it does

Arthur-client is a Python SDK that connects your machine learning models to Arthur's centralized monitoring platform. It abstracts the HTTP API calls needed to send model metadata, predictions, and performance metrics to Arthur's infrastructure, enabling teams to track model accuracy, explainability, and fairness across production deployments without being locked into a specific ML framework or infrastructure provider.

The package depends on standard HTTP and configuration libraries (requests, urllib3, authlib, pydantic, click) to handle authentication, data validation, and CLI interactions. It's designed for data scientists and ML engineers who want to integrate monitoring into their model pipelines with minimal setup overhead—typically just instantiating a client and calling methods to register models and log predictions.

Use it for:

  • Integrate a scikit-learn or neural network model into Arthur's monitoring dashboard to track real-time prediction accuracy and data drift.
  • Send model fairness metrics to Arthur for compliance auditing and bias detection across demographic groups.
  • Set up automated alerts when model performance degrades below defined thresholds in production.
  • Log prediction explanations and feature importance alongside predictions for model interpretability.
  • Centralize monitoring for multiple models deployed across different services or cloud providers.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Python SDK for integrating machine learning models with Arthur, a centralized platform for monitoring production models across accuracy, explainability, and fairness.

Yes, if you are already using or planning to adopt Arthur for model monitoring. The SDK is actively maintained, has low install friction, uses a permissive MIT license, and carries no known vulnerabilities. Install only if your team has committed to Arthur's platform; it is a client library for a specific service, not a general-purpose monitoring tool.

Install

arthur-client on PyPI

pip

pip install arthur-client

uv

uv add arthur-client

poetry

poetry add arthur-client

Installing arthur-client

Before you install

Low install friction with a pure-Python wheel distribution. Actively maintained as of the latest release date. Supports current Python versions (3.12, 3.13) with no compiled dependencies.

License in practice

MIT license permits commercial and private use with minimal restrictions, making it suitable for most production deployments without legal friction.

Quickstart

pip install arthur-client

from arthur_client import ArthurClient

client = ArthurClient()
# Configure and connect your model to Arthur platform

Requires Python 3.12 or later.

Verify before relying

  • Specific authentication mechanisms and credential handling beyond authlib dependency
  • Whether the SDK supports all Arthur platform features or a subset of the API
  • Performance characteristics when monitoring high-volume model predictions
  • Integration patterns with common ML frameworks (scikit-learn, TensorFlow, PyTorch)

Package facts

License MIT (permissive)
Python support supports the current Python release (>=3.12)
Install friction low — pure-Python wheel
Runtime dependencies 8 — authlib, click, pydantic, python-dateutil, requests, simple-settings, typing-extensions, urllib3
Maintenance actively maintained — 0 days since the last release
First released
Downloads 96,465/month — #13,209 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: arthur_client-1.4.2333-py3-none-any.whl

Keywords: ArthurAI, api, arthur, client, ml, model, monitoring, sdk

Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Software Development :: Libraries :: Application Frameworks

Tags

ml model monitoring sdkproduction model observabilityarthur platform integrationmodel performance trackingai model governanceml ops monitoring clientmodel fairness tracking
ml-monitoringmodel-observabilityarthur-platform

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