damccorm opened a new issue, #21428:
URL: https://github.com/apache/beam/issues/21428

   We have discovered a potential bug whereas when you execute a pipeline that 
contains
   a DataframeTransform with the "runtime_type_check" option set to True, a 
cryptic
   error is raised by Apache Beam typecheckng.
   
   Simple example to reproduce the bug:
       
   ```
   
   from apache_beam.options.pipeline_options import PipelineOptions
   from apache_beam import Pipeline,
   Create, Row
   from apache_beam.dataframe.transforms import DataframeTransform
   pipeline = Pipeline(options=PipelineOptions(runtime_type_check=True))
   pipeline
   | Create([Row(val1=1)]) | DataframeTransform(lambda df: df)
   pipeline.run()
   ```
   
   This raises a apache_beam.typehints.decorators.TypeCheckError:
   ```
   
   File ".....lib/python3.8/site-packages/apache_beam/typehints/typehints.py", 
line 416, in check_constraint
    
     raise SimpleTypeHintError
   apache_beam.typehints.decorators.TypeCheckError: According to type-hint
   expected output should be of type <class 
'apache_beam.typehints.schemas.BeamSchema_118086df_671f_4643_a929_ba65de48e7e8'>.
   Instead, received 'BeamSchema_118086df_671f_4643_a929_ba65de48e7e8(val1=1)', 
an instance of type <class
   
'apache_beam.typehints.schemas.BeamSchema_118086df_671f_4643_a929_ba65de48e7e8'>.
 [while running 'DataframeTransform/Unbatch
   'placeholder_DataFrame_140623617251840'/ParDo(_UnbatchNoIndex)'] 
   ```
   
    
   
   Imported from Jira 
[BEAM-13905](https://issues.apache.org/jira/browse/BEAM-13905). Original Jira 
may contain additional context.
   Reported by: benwah.


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