Pydantic Error when parsing a string as an integer (Fix)

The Fix

pip install pydantic==1.10.1

Based on closed pydantic/pydantic issue #9165 · PR/commit linked

Jump to Verify Open PR/Commit

@@ -61,6 +61,7 @@
     'TimeError',
     'DurationError',
+    'HashableError',
     'UUIDError',
     'UUIDVersionError',

repro.py

import pydantic


class TestModel(pydantic.BaseModel):
    a: int
    b: int | None = None


TestModel(**{'b': '000001', 'a': '1'})

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==1.10.1\nWhen NOT to use: This fix should not be applied if integer parsing is not required.\n\n

Why This Fix Works in Production

Trigger: TestModel(**{'b': '000001', 'a': '1'})
Mechanism: Parsing a string as an integer fails due to validation error in Pydantic
Why the fix works: Fixes an issue where parsing a string as an integer would fail in Pydantic. (first fixed release: 1.10.1).

Production impact:

If left unfixed, this can cause silent data inconsistencies that propagate (bad cache entries, incorrect downstream decisions).

Why This Breaks in Prod

Shows up under Python 3.11 in real deployments (not just unit tests).
Parsing a string as an integer fails due to validation error in Pydantic
Surfaces as: Traceback (most recent call last):

Proof / Evidence

GitHub issue: #9165
Fix PR: https://github.com/pydantic/pydantic-core/pull/1266
First fixed release: 1.10.1
Reproduced locally: No (not executed)
Last verified: 2026-02-09
Confidence: 0.85
Did this fix it?: Yes (upstream fix exists)
Own content ratio: 0.55

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: 1.10.1
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

“Thanks for reporting @hlloreda, this is a really good catch. This is fixed in https://github.com/pydantic/pydantic-core/pull/1266.”

@samuelcolvin · 2024-04-06 · confirmation · source

“@hlloreda, Thanks for reporting this. We're looking into this issue and will work on a fix before we release 2.7!”

@sydney-runkle · 2024-04-04 · source

Failure Signature (Search String)

TestModel(**{'b': '000001', 'a': '1'})

Error Message

Stack trace

error.txt

Error Message
-------------
Traceback (most recent call last):
  File "/home/hugo/PycharmProjects/pythonProject3/main.py", line 9, in <module>
    TestModel(**{'b': '000001', 'a': '1'})
  File "/home/hugo/PycharmProjects/pythonProject3/venv/lib/python3.11/site-packages/pydantic/main.py", line 175, in __init__
    self.__pydantic_validator__.validate_python(data, self_instance=self)
pydantic_core._pydantic_core.ValidationError: 1 validation error for TestModel
b
  Input should be a valid integer, unable to parse string as an integer [type=int_parsing, input_value='000001', input_type=str]
    For further information visit https://errors.pydantic.dev/2.7/v/int_parsing

Minimal Reproduction

repro.py

import pydantic


class TestModel(pydantic.BaseModel):
    a: int
    b: int | None = None


TestModel(**{'b': '000001', 'a': '1'})

Environment

Python: 3.11
Pydantic: 2

What Broke

Users encounter validation errors when passing string representations of integers.

Why It Broke

Parsing a string as an integer fails due to validation error in Pydantic

Fix Options (Details)

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

pip install pydantic==1.10.1

When NOT to use: This fix should not be applied if integer parsing is not required.

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

Fix reference: https://github.com/pydantic/pydantic-core/pull/1266

First fixed release: 1.10.1

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

When NOT to Use This Fix

This fix should not be applied if integer parsing is not required.

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
1.10.1	Fixed

Related Issues

No related fixes found.

Cluster: pydantic:data-consistency Pydantic hub Pydantic best practices All hubs All clusters

Related clusters: Configuration error OpenAPI schema Serialization

Sources

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