code: def test_merge_property_example():
      prop1 = Property(
          name="a",
          dtype=Object(
              properties=[
                  Property(
                      name="a", dtype=DataType.string, required=False
                  )
              ]
          ),
      )
      prop1_dict = prop1.to_dict()
      prop2 = Property(
          name="a",
          dtype=Object(
              properties=[
                  Property(name="a", dtype=DataType.string),
                  Property(name="b", dtype=DataType.double),
              ]
          ),
      )
      prop2_dict = prop2.to_dict()
      updated_prop = prop1._merge(prop2)
      assert updated_prop == Property(
          name="a",
          dtype=Object(
              properties=[
                  Property(
                      name="a", dtype=DataType.string, required=False
                  ),
                  Property(
                      name="b", dtype=DataType.double, required=False
                  ),
              ]
          ),
      )
      assert prop1.to_dict() == prop1_dict
      assert prop2.to_dict() == prop2_dict
  
imports: import datetime
  import json
  import math
  import re
  import numpy
  import pandas
  import pyspark
  import pyspark.sql.types
  import pytest
  from scipy.sparse import csc_matrix, csr_matrix
  from mlflow.exceptions import MlflowException
  from mlflow.models.utils import _enforce_tensor_spec
  from mlflow.pyfunc import _parse_spark_datatype
  from mlflow.types import DataType
  from mlflow.types.schema import Array, ColSpec, Object, ParamSchema, ParamSpec, Property, Schema, TensorSpec
  from mlflow.types.utils import _get_tensor_shape, _infer_colspec_type, _infer_param_schema, _infer_schema, _validate_input_dictionary_contains_only_strings_and_lists_of_strings
label_desc: Use image node_id 43 for calling a global function with example usage: test_merge_property_example() without return types