GH-53: refactor: Centralize relative dataframe-information-path and M…

[Urfoex]

…igrate from pydantic dataclasses to BaseModel

This commit refactors all data models from pydantic.dataclasses.dataclass to pydantic.BaseModel. This change provides a more idiomatic and powerful way to use Pydantic's features, such as model_config and model_dump/validate.

Key changes include:

• Replaced @dataclass(frozen=True) with BaseModel and model_config = ConfigDict(frozen=True).
• Simplified serialization/deserialization logic by replacing TypeAdapter with direct Model.model_dump_json() and Model.model_validate() calls.
• Centralized path relativization logic for DataFrameInformation into a new serialize/dataframe_information.py module. This removes the need for custom _serialize_model methods and path fields on ContainerInformation and PipelineInformation, cleaning up the model definitions.
• Renamed ROLE_TYPE_ADAPTER_MAPPING to ROLE_TO_COLUMN_STATISTICS_TYPE_MAPPING and now stores model types instead of TypeAdapter instances, simplifying validation logic.
• Removed obsolete type alias files (feature_sets.py, prediction_results.py).

[Copilot]

Pull Request Overview

This PR refactors all data models from pydantic.dataclasses.dataclass to pydantic.BaseModel to provide more idiomatic usage of Pydantic features. It also centralizes relative path handling for DataFrameInformation objects and simplifies serialization logic.

• Replace @dataclass(frozen=True) with BaseModel and model_config = ConfigDict(frozen=True) across all models
• Migrate from TypeAdapter to direct BaseModel.model_dump_json() and BaseModel.model_validate() calls
• Centralize DataFrameInformation path relativization logic into a dedicated serialize/dataframe_information.py module

Reviewed Changes

Copilot reviewed 42 out of 42 changed files in this pull request and generated 1 comment.

File	Description
Multiple test files	Updated test fixtures and expectations to work with new BaseModel approach
Multiple metadata model files	Converted from pydantic dataclass to BaseModel with frozen configuration
Multiple serialize modules	Replaced TypeAdapter usage with direct model methods and centralized path logic
Integration test files	Updated model instantiation and validation to use BaseModel patterns

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[gemini-code-assist]

Code Review

This pull request is a significant and well-executed refactoring. It successfully migrates all Pydantic data models from pydantic.dataclasses.dataclass to pydantic.BaseModel, aligning with modern Pydantic idioms. The centralization of path relativization logic is a great improvement, cleaning up the model definitions and improving separation of concerns. The code is consistent, and the tests have been thoroughly updated to reflect these substantial changes. Overall, this is an excellent enhancement to the codebase.

[srnnkls]

A small comment on best practices for BaseModel configuration. Otherwise lgtm.

[awaismirza92]

LGTM.

Minor ruff check error

(getml-io) awais@Admins-MacBook-Air:~/code17/projects/getML/github/getml-io% uv run ruff check --extend-ignore FIX .
src/getml_io/serialize/dataframe_or_view.py:172:10: COM812 [*] Trailing comma missing
|
170 | role,
171 | column_type,
172 | )
| ^ COM812
173 | )
174 | if column_statistics_type is None:
|
= help: Add trailing comma

Found 1 error.
[*] 1 fixable with the --fix option.

ruff format unformatted file

awais@Admins-MacBook-Air:~/code17/projects/getML/github/getml-io% uv run ruff format --check .
warning: The following rule may cause conflicts when used with the formatter: COM812. To avoid unexpected behavior, we recommend disabling this rule, either by removing it from the lint.select or lint.extend-select configuration, or adding it to the lint.ignore configuration.
Would reformat: src/getml_io/serialize/dataframe_or_view.py
1 file would be reformatted, 80 files already formatted