pydantic-collections

What it is and what it does

pydantic-collections wraps a list of pydantic models in a `BaseCollectionModel` class that applies validation, serialization, and type checking to the entire collection. It acts as a container that enforces that all items conform to a specified pydantic model schema, supporting both strict and lenient assignment modes. The class inherits from pydantic's `BaseModel`, so collections can be nested as fields in other models and serialized to JSON or dictionaries using pydantic's standard methods.

The package is designed for workflows where you need to load, validate, and serialize batches of structured data—such as API responses containing arrays of objects, CSV imports, or database result sets. It reduces boilerplate by letting you define a collection type once and reuse it across your codebase. However, the repository is archived and abandoned, with no active maintenance since mid-2026, which may pose a risk if you rely on future compatibility with newer pydantic versions or need bug fixes.

Use it for:

• Validate and type-check a list of API response objects before processing them in your application.
• Wrap CSV or JSON imports in a collection model to ensure all records conform to a schema before persisting.
• Nest a collection of models as a field in a parent pydantic model for hierarchical data validation.
• Serialize a batch of model instances to JSON with automatic datetime and custom type handling.
• Enforce strict type safety when appending items to a collection to catch invalid assignments early.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Provides a `BaseCollectionModel` class that wraps collections of pydantic models with validation, serialization, and type safety.

Yes, if you are using pydantic v1.x or early v2.x and need a lightweight, low-friction way to validate and serialize collections of models. No, if you require active maintenance or plan to upgrade pydantic significantly in the near future—the package is archived and abandoned, with no recent updates. Consider whether pydantic's native list validation (e.g., `list[MyModel]`) or a simple wrapper function meets your needs instead.

Install

pydantic-collections on PyPI

pip install pydantic-collections

uv add pydantic-collections

poetry add pydantic-collections

Installing pydantic-collections

Before you install

Low install friction with only two runtime dependencies (pydantic and typing-extensions). However, the repository is archived and marked abandoned as of the fact sheet date, with no commits since 2026-08-05 and the last release over 2 years old.

License in practice

Licensed under Apache 2, a permissive open-source license that allows commercial and private use with minimal restrictions.

Quickstart

pip install pydantic-collections

from pydantic import BaseModel
from pydantic_collections import BaseCollectionModel

class User(BaseModel):
    id: int
    name: str

class UserCollection(BaseCollectionModel[User]):
    pass

users = UserCollection([{'id': 1, 'name': 'Alice'}])
print(users.model_dump_json())

Requires pydantic>=1.8.2,<3.0 and Python>=3.7; behavior differs between pydantic v1.x and v2.x (dict() vs model_dump(), json() vs model_dump_json()).

Verify before relying

• Whether the package works reliably with pydantic 2.x given the archived status and age of last release.
• Whether strict assignment validation (the default) is the right choice for most use cases or if it causes friction.
• Current community adoption and whether alternatives have emerged since abandonment.

Package facts

Evidence: pydantic_collections-0.6.0-py3-none-any.whl

Keywords: python, pydantic, validation, parsing, serialization, models

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