content: #  Copyright (c) ZenML GmbH 2020. All Rights Reserved.
  #
  #  Licensed under the Apache License, Version 2.0 (the "License");
  #  you may not use this file except in compliance with the License.
  #  You may obtain a copy of the License at:
  #
  #       https://www.apache.org/licenses/LICENSE-2.0
  #
  #  Unless required by applicable law or agreed to in writing, software
  #  distributed under the License is distributed on an "AS IS" BASIS,
  #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
  #  or implied. See the License for the specific language governing
  #  permissions and limitations under the License.
  from steps import importer, predictor, trainer, vectorizer
  
  from zenml import pipeline
  from zenml.config import DockerSettings
  from zenml.integrations.constants import PANDAS, SCIPY, SKLEARN
  
  docker_settings = DockerSettings(
      required_integrations=[SKLEARN, PANDAS, SCIPY]
  )
  
  
  @pipeline(enable_cache=True, settings={"docker": docker_settings})
  def scipy_example_pipeline():
      X_train, X_test, y_train, y_test = importer()
      vec_transformer, X_train_vec, X_test_vec = vectorizer(X_train, X_test)
      model = trainer(X_train_vec, y_train)
      predictor(vec_transformer, model, X_test)
  