code: def _execute():
      # To start, take a look at "examples/environment_params.json" - This is the file we're giving our Environment below
      # In this file, we can define a bunch of default Environment parameters that we don't want to always explicitly provide
  
      # It works really well for things that won't be changing often, like the following:
      # - `results_path`, which we probably never want to change, so all our results go to one place;
      # - `target_column`, which will probably be a constant for your data
      # - `metrics`, if you're not using any fancy metrics, and you already know what you want
      # - `file_blacklist`, if you're angry at me for adding that one result file that's always useless
      # Other parameters, whose default values you may want to change
  
      env = Environment(
          train_dataset=get_breast_cancer_data(),  # If your dataset is a str path, you can even add it to environment_params
          environment_params_path="./environment_params.json",  # Use this file for parameters not explicitly given
          cv_params=dict(
              n_splits=5, shuffle=True, random_state=32
          ),  # Here we decide to override our default values
      )
  
      print(env.results_path)
      print(env.target_column)
      print(env.metrics)
      print(env.cv_type)
      print(env.runs)
      print(
          env.file_blacklist
      )  # This includes some other values too, but you can ignore them
      # All of the above are from `environment_params_path`
      print(
          env.cv_params
      )  # This is the value we provided above, rather than our `environment_params_path` default
  
      experiment = CVExperiment(
          model_initializer=KNeighborsClassifier, model_init_params={}
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: _execute() without return types