24912462866

Committed 24 Apr 2026 09:21PM UTC coverage: 76.362% (-3.1%) from 79.464%

Build # 24912462866

Build Type

push

github

Committed by

web-flow

Commit Message

Merge pull request #73 from rafaelpadilla/eduardo/refactor_data_operations

Refactor of data operations, trainers and models.

Coverage Stats

244 of 339 branches covered (71.98%)

Branch coverage included in aggregate %.

1317 of 1706 new or added lines in 50 files covered. (77.2%)

28 existing lines in 5 files now uncovered.

2124 of 2762 relevant lines covered (76.9%)

0.77 hits per line

Source File
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88.24

/toolkit/ThreeWToolkit/core/base_transform.py

from pydantic import BaseModel
from abc import ABC, abstractmethod

from .base_dataset import BaseDataset
from .dataset_outputs import DatasetOutputs
from .base_instantiable import Instantiable


class BaseTransformConfig(BaseModel, Instantiable):
    """Base configuration for general transformation steps."""

    _target: type["BaseTransform"]


class BaseTransform(ABC):
    """Base class for general transformation steps."""

    def __init__(self, config: BaseTransformConfig):
        self.config = config

    @abstractmethod
    def fit(self, dataset: BaseDataset) -> None:
        """Fit the transformation step to the dataset if needed.

        Args:
            dataset: Dataset to fit on.
        """
        pass

    def transform_event(self, data: DatasetOutputs) -> DatasetOutputs:
        """Transform a single event using the fitted transformation step.

        Args:
            data: Single event's dataset outputs to transform.

        Returns:
            Transformed dataset outputs.
        """
        raise NotImplementedError(
            "Subclasses must implement the transform_event method."
        )

    def transform(self, dataset: BaseDataset) -> BaseDataset:
        raise NotImplementedError("Subclasses must implement the transform method.")

1	from pydantic import BaseModel	1✔
2	from abc import ABC, abstractmethod	1✔
3
4	from .base_dataset import BaseDataset	1✔
5	from .dataset_outputs import DatasetOutputs	1✔
6	from .base_instantiable import Instantiable	1✔
7
8
9	class BaseTransformConfig(BaseModel, Instantiable):	1✔
10	"""Base configuration for general transformation steps."""
11
12	_target: type["BaseTransform"]	1✔
13
14
15	class BaseTransform(ABC):	1✔
16	"""Base class for general transformation steps."""
17
18	def __init__(self, config: BaseTransformConfig):	1✔
19	self.config = config	1✔
20
21	@abstractmethod	1✔
22	def fit(self, dataset: BaseDataset) -> None:	1✔
23	"""Fit the transformation step to the dataset if needed.
24
25	Args:
26	dataset: Dataset to fit on.
27	"""
NEW 28	pass	×
29
30	def transform_event(self, data: DatasetOutputs) -> DatasetOutputs:	1✔
31	"""Transform a single event using the fitted transformation step.
32
33	Args:
34	data: Single event's dataset outputs to transform.
35
36	Returns:
37	Transformed dataset outputs.
38	"""
39	raise NotImplementedError(	1✔
40	"Subclasses must implement the transform_event method."
41	)
42
43	def transform(self, dataset: BaseDataset) -> BaseDataset:	1✔
NEW 44	raise NotImplementedError("Subclasses must implement the transform method.")	×

rafaelpadilla / 3W / 24912462866

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