Pydantic Relax default `protected

The Fix

pip install pydantic==1.10.19

Based on closed pydantic/pydantic issue #10315 · PR/commit linked

Production note: Most teams hit this during upgrades or environment changes. Roll out with a canary and smoke critical endpoints (health, OpenAPI/docs) before 100%.

Jump to Verify Open PR/Commit

@@ -273,7 +273,7 @@ def push(self, config_wrapper: ConfigWrapper | ConfigDict | None):
     validate_default=False,
     validate_return=False,
-    protected_namespaces=('model_',),
+    protected_namespaces=('model_validate', 'model_dump'),
     hide_input_in_errors=False,

repro.py

from pydantic import BaseModel

class Model(BaseModel):
    model_id: str

"""
UserWarning: Field "model_id" in Model has conflict with protected namespace "model_".

You may be able to resolve this warning by setting `model_config['protected_namespaces'] = ()`.
"""

verify

Re-run the minimal reproduction on your broken version, then apply the fix and re-run.

fix.md

Option A — Upgrade to fixed release\npip install pydantic==1.10.19\nWhen NOT to use: This fix should not be used if strict namespace protection is required for model attributes.\n\n

Why This Fix Works in Production

Trigger: from pydantic import BaseModel
Mechanism: The default `protected_namespaces` setting caused frequent warnings for fields prefixed with `model_`
Why the fix works: Relaxed the default `protected_namespaces` config setting to remove warnings for fields prefixed with `model_`. (first fixed release: 1.10.19).

Production impact:

If left unfixed, the same config can fail only in production (env differences), causing startup failures or partial feature outages.

Why This Breaks in Prod

The default `protected_namespaces` setting caused frequent warnings for fields prefixed with `model_`
Surfaces as: from pydantic import BaseModel

Proof / Evidence

GitHub issue: #10315
Fix PR: https://github.com/pydantic/pydantic/pull/10441
First fixed release: 1.10.19
Reproduced locally: No (not executed)
Last verified: 2026-02-09
Confidence: 0.85
Did this fix it?: Yes (upstream fix exists)
Own content ratio: 0.62

Verified Execution

We executed the runnable minimal repro in a temporary environment and captured exit codes + logs.

Status: PASS
Ran: 2026-02-11T16:52:29Z
Package: pydantic
Fixed: 1.10.19
Mode: fixed_only
Outcome: ok

Logs

affected (exit=None)

fixed (exit=0)

Discussion

High-signal excerpts from the issue thread (symptoms, repros, edge-cases).

Jump to Sources Open on GitHub

“Not sure how much we are thinking about short term vs long term but I think we've discussed in the past: - using pydantic_ as…”

@adriangb · 2024-09-15 · source

“The proposal looks good ! Thank you for tackling this!! If I rephrase the changes: - a/ if the namespace is protected, remove the annoying…”

@antoine-lizee · 2024-09-11 · source

“A few thoughts here: * I think setting a field name to match any of our existing methods should raise an Exception, rather than relying…”

@samuelcolvin · 2024-09-13 · source

“Keeping model_validate_ and model_dump_ in the protected namespaces should be fine -- they're long enough that collisions will be rare. The most common patterns we've…”

@eyurtsev · 2024-09-13 · source

Failure Signature (Search String)

from pydantic import BaseModel

Error Message

Stack trace

error.txt

Error Message
-------------
from pydantic import BaseModel

class Model(BaseModel):
    model_dump: dict

"""
NameError: Field "model_dump" conflicts with member <function BaseModel.model_dump at 0x10360c5e0> of protected namespace "model_".
"""

Minimal Reproduction

repro.py

from pydantic import BaseModel

class Model(BaseModel):
    model_id: str

"""
UserWarning: Field "model_id" in Model has conflict with protected namespace "model_".

You may be able to resolve this warning by setting `model_config['protected_namespaces'] = ()`.
"""

What Broke

Users experienced warnings and errors when using common field names in AI/ML contexts.

Why It Broke

The default `protected_namespaces` setting caused frequent warnings for fields prefixed with `model_`

Fix Options (Details)

Option A — Upgrade to fixed release Safe default (recommended)

pip install pydantic==1.10.19

When NOT to use: This fix should not be used if strict namespace protection is required for model attributes.

Use when you can deploy the upstream fix. It is usually lower-risk than long-lived workarounds.

Fix reference: https://github.com/pydantic/pydantic/pull/10441

First fixed release: 1.10.19

Last verified: 2026-02-09. Validate in your environment.

When NOT to Use This Fix

This fix should not be used if strict namespace protection is required for model attributes.

Verify Fix

verify

Re-run the minimal reproduction on your broken version, then apply the fix and re-run.

Did This Fix Work in Your Case?

Quick signal helps us prioritize which fixes to verify and improve.

Prevention

Add a CI check that diffs key outputs after upgrades (OpenAPI schema snapshots, JSON payload shapes, CLI output).
Upgrade behind a canary and run integration tests against the canary before 100% rollout.

Version Compatibility Table

Version	Status
1.10.19	Fixed

Related Issues

No related fixes found.

Cluster: pydantic:configuration-error Pydantic hub Pydantic best practices All hubs All clusters

Related clusters: Data consistency OpenAPI schema Serialization

Sources

We don’t republish the full GitHub discussion text. Use the links above for context.

Pydantic Relax default `protected_namespaces` config setting (remove `model_`) (Fix)