HPAT unable to handle non-existent dataframe index name. #132

Activity

1. akharche commented on Sep 5, 2019

   

   akharche

   on Sep 5, 2019

   Last edited by akharche

   Contributor

   More actions

   Thank you for the example. I guess this issue is not connected to non-existent dataframe index (I mean the additional column "Index").
   Now Hpat is limited in handling DataFrames created such way df2 = pd.DataFrame([100,200,300,400,200,100]), Hpat expects column name like df2 = pd.DataFrame([100,200,300,400,200,100], columns=['A']) or a dictionary like in your examples.
   It is mentioned in Hpat docs.

   We will add ability to handle such cases.
2. triskadecaepyon commented on Sep 6, 2019

   

   triskadecaepyon

   on Sep 6, 2019

   Author

   More actions

   So an additional thought then since we are adding this ability:

   Is there a way we can elegantly handle unsupported features in the future? As in throw a warning, don't continue, leave as Python Object code?
3. fschlimb commented on Sep 6, 2019

   

   fschlimb

   on Sep 6, 2019

   Contributor

   More actions

   It is of course possible to just not compile anything and leave the entire function uncompiled.
   It's less straight forward to partially fall back to object mode. It is conceptually possible for certain functions, e.g. those which are trivially data parallel. There is no default fallback for others, like reductions, joins etc. The situation is different if we separated distribution from compilation: going to object-mode in (a hypothetical) non-distributed mode should always be possible.