new_contents: import sys
  sys.path.insert(1, "../../")
  import h2o, tests
  from h2o import H2OAssembly
  from h2o.transforms.preprocessing import *
  from h2o import H2OFrame
  
  def assembly_demo():
    fr = h2o.import_file(h2o.locate("smalldata/iris/iris_wheader.csv"))                                                                # import data
    assembly = H2OAssembly(steps=[("col_select",      H2OColSelect(["sepal_len", "petal_len", "class"])),                              # col selection
                                  ("cos_sep_len",     H2OColOp(fun=H2OFrame.cos, col="sepal_len", inplace=True)),                      # math operation
                                  ("str_cnt_species", H2OColOp(fun=H2OFrame.countmatches, col="class", inplace=False, pattern="s"))])  # string operation
  
    result = assembly.fit(fr)  # fit the assembly
    result.show()              # show the result of the fit
    # print assembly.to_pojo(pojo_name="GeneratedH2OMungingPojo_001")   # export to pojo
    #
    #
  
  
  
    # java api usage:
    #
    #   String rawRow = framework.nextTuple();
    #   H2OMungingPOJO munger = new GeneratedH2OMungingPojo_001();
    #   EasyPredictModelWrapper model = new EasyPredictModelWrapper(new GeneratedH2OGbmPojo_001());
    #
    #   RowData row = new RowData();
    #   row.fill(rawRow);
    #   row = munger.transform(row);
    #   BinomialModelPrediction pred = model.predictBinomial(row);
    #   // Use prediction!
  
  
  if __name__ == "__main__":
    tests.run_test(sys.argv, assembly_demo)
subject: add pyunit assembly demo