pydantic-scim
Pydantic types for SCIM
Decision gist · record as of 2026-08-14
Yes, if you need SCIM schema validation and your environment supports Python 3.8 or later with a compatible pydantic version. The low install friction and lack of vulnerabilities make it safe to add. However, the dormant status and unclear license mean you should verify license compatibility upfront and test pydantic version compatibility before relying on it in production.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.8 or later.
- SCIM schema knowledge is assumed; the package provides type definitions but not protocol documentation.
- Low install friction with a single dependency on pydantic.
License · maintenance · safety
(unclear) — License status is unclear; no SPDX identifier or raw license text is available. Verify the actual license terms before using in a project with specific licensing requirements.
last release 2023-10-26 (1023 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 185,315 downloads/mo, #10,012 on PyPI
Alternatives
Verify before relying
pip install pydantic-scim
from pydantic_scim import User
user = User(userName="john.doe", displayName="John Doe")- Which SCIM specification version(s) the models conform to
- Whether the models cover the full SCIM schema or a subset
- Current compatibility with recent pydantic versions (v2.x)
What it is and what it does
pydantic-scim wraps SCIM protocol data structures as Pydantic models, generated from official SCIM schema files and refined by hand. It lets you validate and work with identity management objects—users, groups, and related entities—using Pydantic's validation and serialization machinery.
The package is a thin schema layer: it depends only on pydantic and provides type definitions for SCIM entities. It is dormant, with no activity since its latest release, so it will not receive updates for new pydantic releases or SCIM specification changes. Use it when you need to parse or validate SCIM data in a Python application and your pydantic version is compatible with the package's expectations.
Use it for
- Validate incoming SCIM API requests in an identity provider or directory service
- Serialize Python objects to SCIM-compliant JSON for outbound identity sync
- Parse SCIM responses from a third-party identity management system
- Build a SCIM-compatible REST endpoint with type-safe request/response models
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need SCIM schema validation and your environment supports Python 3.8 or later with a compatible pydantic version.
The low install friction and lack of vulnerabilities make it safe to add. However, the dormant status and unclear license mean you should verify license compatibility upfront and test pydantic version compatibility before relying on it in production.
Install
pydantic-scim on PyPI
Before you install
Low install friction with a single dependency on pydantic. The package is dormant—no activity recorded since its latest release—which means bug fixes or compatibility updates are unlikely.
Requires Python 3.8 or later. SCIM schema knowledge is assumed; the package provides type definitions but not protocol documentation.
License in practice
License status is unclear; no SPDX identifier or raw license text is available. Verify the actual license terms before using in a project with specific licensing requirements.
Quickstart
pip install pydantic-scim
from pydantic_scim import User
user = User(userName="john.doe", displayName="John Doe")Verify before relying
- Which SCIM specification version(s) the models conform to
- Whether the models cover the full SCIM schema or a subset
- Current compatibility with recent pydantic versions (v2.x)
Package facts
| License | Not declared unclear |
| Python support | Supports the current Python release >=3.8.0 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagepydantic |
| Maintenance | Dormant 1,023 days since the last release |
| First released | |
| Downloads | 185,315 / month, #10,012 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Programming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.8 |
Evidence: pydantic_scim-0.0.8-py3-none-any.whl
Tags
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 › “pydantic scim models”
- pydantic-scimProvides Pydantic data models for SCIM (System for Cross-domain…
- scim2-modelsProvides Pydantic models for SCIM2 (System for Cross-domain Identity…
- django-scim2Implements the SCIM 2.0 provider specification as a Django app,…
Give your agent the search over MCP, or paste the wish link into any chat.
More Internet packages
Botocore provides low-level, data-driven access to Amazon Web Services APIs, serving as the foundation for the AWS CLI and boto3 libraries.
Install it if you need programmatic access to AWS services.
Provides an async client for AWS services using botocore and aiohttp, allowing you to call AWS APIs asynchronously within asyncio-based applications.
Install it if you need to call AWS services from async Python code; it is the standard way to do so.
Pydantic validates Python data structures against type hints, coercing and checking input at runtime to ensure it matches a declared schema.
Provides a platform-independent file locking mechanism to coordinate access to files across processes and threads.
FastAPI is a Python web framework for building REST APIs using type hints, with automatic request validation, serialization, and interactive API documentation.
Provides common Protocol Buffer message definitions used across Google Cloud APIs, enabling Python clients to interact with Google services.
See also scim2-models · django-scim2 · sigstore-models · safety-schemas · scim2-server · pydantic-xml · pydantic-numpy · datamodel-code-generator · py-ocsf-models · jsonschema-pydantic-converter