pydantic-compat
Compatibility layer for pydantic v1/v2
Decision gist · record as of 2026-08-14
Yes, if you are a library author needing to support both pydantic v1 and v2 in the same codebase. The low install friction and active maintenance make it a practical choice. However, be aware that this is a name adapter, not a full semantic bridge—you will still need to test against both pydantic versions and handle any deeper API differences yourself. Not necessary if you can pin pydantic to a single version.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low install friction with only two runtime dependencies (importlib-metadata and pydantic).
- Actively maintained as of 2026-08-03, though the last release was in 2023-10-24.
License · maintenance · safety
BSD 3-Clause License (permissive) — BSD 3-Clause License (permissive) allows use in most commercial and open-source projects without significant restrictions.
last release 2023-10-24 (1025 days) · last repo commit 2026-08-03 · 13 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 80,268 downloads/mo, #14,301 on PyPI
Alternatives
Verify before relying
from pydantic import BaseModel
from pydantic_compat import PydanticCompatMixin, field_validator
class MyModel(PydanticCompatMixin, BaseModel):
x: int
@field_validator('x', mode='after')
def check_x(cls, v):
return v
obj = MyModel(x=42)
data = obj.model_dump() # works in both v1 and v2- Whether the package's API coverage is sufficient for your specific pydantic usage patterns beyond the documented examples
- How well custom type handling works across both pydantic versions when using this adapter
What it is and what it does
pydantic-compat is a compatibility layer that lets you write pydantic models using either v1 or v2 API names while supporting both pydantic versions in a single codebase. It works by providing a mixin class and adapter functions that translate between the two APIs—for example, mapping `obj.dict()` to `obj.model_dump()` or vice versa depending on which pydantic version is installed. This eliminates the need for version-specific conditionals and boilerplate throughout your library code.
The package is not a full semantic bridge: it translates names and provides basic compatibility for common operations like validation, serialization, and schema access, but does not attempt to hide deeper behavioral differences between v1 and v2. You still need to test your code against both pydantic versions and understand what's changing under the hood. It's designed for library authors who want to support a range of pydantic versions without forcing users to pin a specific version.
Use it for
- Library author supporting both pydantic v1 and v2 without version pinning or deprecation warnings
- Migrating a codebase from pydantic v1 to v2 incrementally while maintaining compatibility
- Defining models that work seamlessly when users have either pydantic version installed
- Reducing conditional version-checking code in model definitions and validation logic
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are a library author needing to support both pydantic v1 and v2 in the same codebase.
The low install friction and active maintenance make it a practical choice. However, be aware that this is a name adapter, not a full semantic bridge—you will still need to test against both pydantic versions and handle any deeper API differences yourself. Not necessary if you can pin pydantic to a single version.
Install
pydantic-compat on PyPI
Before you install
Low install friction with only two runtime dependencies (importlib-metadata and pydantic). Actively maintained as of 2026-08-03, though the last release was in 2023-10-24.
License in practice
BSD 3-Clause License (permissive) allows use in most commercial and open-source projects without significant restrictions.
Quickstart
from pydantic import BaseModel
from pydantic_compat import PydanticCompatMixin, field_validator
class MyModel(PydanticCompatMixin, BaseModel):
x: int
@field_validator('x', mode='after')
def check_x(cls, v):
return v
obj = MyModel(x=42)
data = obj.model_dump() # works in both v1 and v2Verify before relying
- Whether the package's API coverage is sufficient for your specific pydantic usage patterns beyond the documented examples
- How well custom type handling works across both pydantic versions when using this adapter
Package facts
| License | BSD 3-Clause License permissive |
| Python support | Supports the current Python release >=3.7 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesimportlib-metadatapydantic |
| Maintenance | Actively maintained 1,025 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 80,268 / month, #14,301 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 3 - AlphaFramework :: PydanticLicense :: OSI Approved :: BSD LicenseNatural Language :: EnglishProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Typing :: Typed |
Evidence: pydantic_compat-0.1.2-py3-none-any.whl
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See also bump-pydantic · prime-pydantic-config · pydantic-function-models · django-pydantic-field · pylint-pydantic · pydantic-to-typescript2 · pydantic-extra-types · drf-pydantic · pydantic_yaml · json-schema-to-pydantic