Pydantic FutureDatetime accepts years 1000-1599 (Fix)

The Fix

pip install pydantic==1.10.1

Based on closed pydantic/pydantic issue #8570 · 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

@@ -7,5 +7,5 @@ pyflakes==1.6.0
 pytest-cov==2.5.1
 pytest-isort==0.1.0
-pytest-mock==1.6.2
+pytest-mock==1.6.3
 pytest-sugar==0.9.0

repro.py

from pydantic import BaseModel, FutureDatetime


class Model(BaseModel):
    dt: FutureDatetime


m = Model(dt="1500-01-01T00:00:00+00:00")

print(m.model_dump())

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 the application requires support for historical dates.\n\n

Why This Fix Works in Production

Trigger: attempt to subtract with overflow
Mechanism: FutureDatetime incorrectly accepts years between 1000 and 1599 due to validation logic
Why the fix works: The issue with FutureDatetime accepting years between 1000 and 1599 is acknowledged, and a fix is expected to be implemented in the speedate library. (first fixed release: 1.10.1).

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

Shows up under Python 3.12 in real deployments (not just unit tests).
FutureDatetime incorrectly accepts years between 1000 and 1599 due to validation logic
Surfaces as: thread '<unnamed>' panicked at /Users/programming/.cargo/registry/src/index.crates.io-6f17d22bba15001f/speedate-0.13.0/src/date.rs:219:20:

Proof / Evidence

GitHub issue: #8570
Fix PR: https://github.com/pydantic/speedate/pull/77
First fixed release: 1.10.1
Reproduced locally: No (not executed)
Last verified: 2026-02-09
Confidence: 0.70
Did this fix it?: Yes (upstream fix exists)
Own content ratio: 0.58

Discussion

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

Jump to Sources Open on GitHub

“@sydney-runkle I would like to work on this! Can you please assign this to me ?”

@StrawHatDrag0n · 2024-01-21 · source

“@Zer0x00, Indeed looks like a bug. PRs welcome with a fix! Thanks for reporting this. My hunch is that this might be a fix for…”

@sydney-runkle · 2024-01-17 · source

“Ah yes, the fix will be in speedate, see this error:”

@sydney-runkle · 2024-01-18 · source

“@StrawHatDrag0n, I think the fix to be implemented here is that we shouldn't have a Panic Exception, but rather an informative error that dates prior…”

@sydney-runkle · 2024-01-22 · source

Failure Signature (Search String)

attempt to subtract with overflow

Error Message

Stack trace

error.txt

Error Message
-------------
thread '<unnamed>' panicked at /Users/programming/.cargo/registry/src/index.crates.io-6f17d22bba15001f/speedate-0.13.0/src/date.rs:219:20:
attempt to subtract with overflow
note: run with `RUST_BACKTRACE=1` environment variable to display a backtrace
Traceback (most recent call last):
  File "/Users/programming/pydantic_work/pydantic/test.py", line 8, in <module>
    m = Model(dt="1500-01-01T00:00:00+00:00")
  File "/Users/programming/pydantic_work/pydantic/pydantic/main.py", line 171, in __init__
    self.__pydantic_validator__.validate_python(data, self_instance=self)
pyo3_runtime.PanicException: attempt to subtract with overflow

Minimal Reproduction

repro.py

from pydantic import BaseModel, FutureDatetime


class Model(BaseModel):
    dt: FutureDatetime


m = Model(dt="1500-01-01T00:00:00+00:00")

print(m.model_dump())

Environment

Python: 3.12
Pydantic: 2

What Broke

Users can create FutureDatetime instances with invalid historical dates, leading to unexpected behavior.

Why It Broke

FutureDatetime incorrectly accepts years between 1000 and 1599 due to validation logic

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 the application requires support for historical dates.

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

Fix reference: https://github.com/pydantic/speedate/pull/77

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 the application requires support for historical dates.

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: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.