Pydantic SCIM

0.0.8 · active · verified Fri Apr 17

Pydantic-SCIM provides Pydantic models that strictly adhere to the SCIM (System for Cross-domain Identity Management) specification. It allows developers to define, validate, and serialize SCIM resources like Users and Groups, simplifying integration with SCIM-compliant identity providers. The library currently supports Pydantic v1.x.

Common errors

```
TypeError: 'TypeAliasType' object is not subscriptable
```
cause Attempting to use pydantic-scim with Pydantic v2. This error specifically arises because Pydantic v2 changed how type aliases are handled.

fix Downgrade Pydantic to version 1.x: `pip uninstall pydantic && pip install 'pydantic<2.0.0'`.
```
pydantic.error_wrappers.ValidationError: 1 validation error for User\nschemas\n  field required (type=value_error.missing)
```
cause A required SCIM field (in this case, `schemas`) was omitted when instantiating a SCIM model, or an invalid value was provided.

fix Ensure all mandatory SCIM attributes are provided and correctly typed. For `User`, the `schemas` field is always required and should include `"urn:ietf:params:scim:schemas:core:2.0:User"`.
```
AttributeError: 'User' object has no attribute 'model_dump_json'
```
cause Attempting to use a Pydantic v2 method (`model_dump_json`) on a model defined with Pydantic v1.

fix For Pydantic v1 models, use `user.json()` to serialize to JSON, or `user.dict()` to get a dictionary representation.

Warnings

breaking pydantic-scim is only compatible with Pydantic v1.x. Installing it with Pydantic v2.x will lead to import errors, validation failures, or unexpected behavior.
Fix: Ensure Pydantic v1.x is installed: `pip install 'pydantic<2.0.0'` or uninstall Pydantic v2 (`pip uninstall pydantic`) before installing Pydantic v1 and pydantic-scim.
gotcha SCIM schemas are very strict. Missing required fields (e.g., `schemas`, `userName` for User) or providing incorrect data types will result in Pydantic `ValidationError`.
Fix: Always consult the SCIM specification (RFC 7643) for required fields and data types, or refer to the `pydantic-scim` source for model definitions. Ensure all mandatory fields are present.
gotcha SCIM attribute names are case-sensitive and must match the specification exactly (e.g., `userName`, `givenName`, `familyName`). Python's convention often uses `snake_case`, but SCIM uses `camelCase`.
Fix: Use the exact `camelCase` attribute names as defined in the SCIM specification when initializing models (e.g., `userName`, not `user_name`). pydantic-scim models reflect the SCIM spec directly.

Install

pip install pydantic-scim Install stable version

Imports

User
```
from pydantic_scim import User
```
Group
```
from pydantic_scim import Group
```
ListResponse
```
from pydantic_scim import ListResponse
```

Quickstart

Demonstrates how to instantiate a SCIM User object and serialize it to JSON, following the required SCIM schema fields. Note the use of `user.json()` for Pydantic v1 serialization.

from pydantic_scim import User

# Create a SCIM User object adhering to the SCIM Core Schema
user = User(
    schemas=["urn:ietf:params:scim:schemas:core:2.0:User"],
    userName="bjensen",
    name={
        "givenName": "Barbara",
        "familyName": "Jensen"
    },
    emails=[
        {
            "value": "bjensen@example.com",
            "type": "work",
            "primary": True
        }
    ],
    active=True,
    externalId="employee-id-123"
)

# Serialize the user object to JSON (using Pydantic v1 .json() method)
print(user.json(indent=2))

view raw JSON →