code: def test_classification_data_operations():
      (
          train_input,
          predict_input,
          y_test,
      ) = get_small_classification_dataset()
  
      operation_names = OperationTypesRepository(
          "data_operation"
      ).suitable_operation(task_type=TaskTypesEnum.classification)
  
      for data_operation in operation_names:
          node_data_operation = PipelineNode(data_operation)
          node_final = PipelineNode(
              "logit", nodes_from=[node_data_operation]
          )
          pipeline = Pipeline(node_final)
  
          # Fit and predict for pipeline
          pipeline.fit_from_scratch(train_input)
          predicted_output = pipeline.predict(predict_input)
          predicted = predicted_output.predict
  
          assert len(predicted) == len(y_test)
  
imports: import os
  import numpy
  import pytest
  from examples.simple.classification.classification_with_tuning import get_classification_dataset
  from examples.simple.regression.regression_with_tuning import get_regression_dataset
  from examples.simple.time_series_forecasting.gapfilling import generate_synthetic_data
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.data.supplementary_data import SupplementaryData
  from fedot.core.operations.evaluation.operation_implementations.data_operations.sklearn_imbalanced_class import ResampleImplementation
  from fedot.core.operations.evaluation.operation_implementations.data_operations.sklearn_transformations import ImputationImplementation
  from fedot.core.operations.evaluation.operation_implementations.data_operations.ts_transformations import CutImplementation, LaggedTransformationImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.operation_types_repository import OperationTypesRepository
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
  from fedot.preprocessing.data_types import TYPE_TO_ID
  from test.unit.preprocessing.test_preprocessing_through_api import data_with_only_categorical_features
label_desc: Use image node_id 12 for calling a global function with example usage: test_classification_data_operations() without return types