code: def test__create_treatment_flag():
      df = pd.DataFrame(
          {
              "feature": [1.3, 1.0, 1.8, -0.1],
              "group": ["treatment", "treatment", "control", "control"],
              "target": [1, 1, 1, 0],
          }
      )
  
      expected = pd.DataFrame(
          {
              "feature": [1.3, 1.0, 1.8, -0.1],
              "group": ["treatment", "treatment", "control", "control"],
              "target": [1, 1, 1, 0],
              TREATMENT_FEATURE: [1.0, 1.0, 0.0, 0.0],
          }
      )
  
      results = _create_treatment_flag(
          df,
          treatment_col="group",
          control_name="control",
          treatment_name="treatment",
      )
  
      assert_frame_equal(results, expected)
  
imports: from typing import Callable
  from unittest.mock import MagicMock, call, create_autospec, patch
  import numpy
  import pandas
  import pytest
  from pandas import DataFrame
  from pandas.testing import assert_frame_equal
  from fklearn.causal.cate_learning.meta_learners import TREATMENT_FEATURE, _append_treatment_feature, _create_treatment_flag, _filter_by_treatment, _fit_by_treatment, _get_learners, _get_model_fcn, _get_unique_treatments, _predict_by_treatment_flag, _simulate_t_learner_treatment_effect, _simulate_treatment_effect, causal_s_classification_learner, causal_t_classification_learner
  from fklearn.exceptions.exceptions import MissingControlError, MissingTreatmentError, MultipleTreatmentsError
  from fklearn.training.classification import logistic_classification_learner
  from fklearn.types import LearnerFnType
label_desc: Use image node_id 8 for calling a global function with example usage: test__create_treatment_flag() without return types