arthur-client
Arthur Python API Client Library
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.12 or later.
- Low install friction with a pure-Python wheel distribution.
- Actively maintained as of the latest release date.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions, making it suitable for most production deployments without legal friction.
last release 2026-08-14 (0 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 96,465 downloads/mo, #13,209 on PyPI
Alternatives
Verify before relying
pip install arthur-client
from arthur_client import ArthurClient
client = ArthurClient()
# Configure and connect your model to Arthur platform- 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)
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 on it.
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
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.
Requires Python 3.12 or later.
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 platformVerify 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 packagesauthlibclickpydanticpython-dateutilrequestssimple-settingstyping-extensionsurllib3 |
| 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 |
| Classifiers | 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 |
Evidence: arthur_client-1.4.2333-py3-none-any.whl
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