lazarillo commented on issue #32781:
URL: https://github.com/apache/beam/issues/32781#issuecomment-2422409550

   I will think more on my biggest pain points going cross-language, and 
provide a specific example when I remember / experience it.
   
   But for now, I'll give one pain point:  I am _really_ bad at Java.  I am a 
machine learning / data engineer.  If I could, I'd work with modern languages 
like Go or Rust.  But I need to use a language that is well supported for my 
career.  So that means either Java, Python, or Scala. (Less so Scala these 
days, but it was quite big when Spark initially started.)  I chose Python 
because it's easiest to work with, but also because I _vehemently_ believe that 
code should be easy to read, and that object oriented is a choice that is _only 
sometimes_ the right choice.  So Python seemed better than Java.  Lastly, the 
JVM was far more useful before Docker came onto the scene.  So even that perk 
lost its luster.
   
   I very much rely upon discovered code when documentation is insufficient.  I 
can read just about any Python code, no matter how complex, and understand what 
it is doing and how I can interact with it (and whether I should or not).  But 
with Java (or Go), I am too ignorant of the language: I need good docs in order 
to know what to do and how to interact with the SDK.
   
   I think the Apache Beam docs are _great_.  But Beam is such a complex beast 
that often I learn what I really need to know by going straight to the source 
code (which is linked to throughout the documentation, which is awesome).
   
   Because of all this, I try to stay with the pure Python code as much as 
possible.  It allows me more confidence to create my pipeline.  Even a "simple" 
pipeline is quite complex, I've found in my experience.
   
   
   


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