Not currently On Sat, May 10, 2025, 12:48 AM Reuven Lax <re...@google.com> wrote:
> Does this work with nested fields? Can you specify Input_field="a.b.c"? > > On Fri, May 9, 2025 at 7:18 PM Joey Tran <joey.t...@schrodinger.com> > wrote: > >> Sure! >> >> Given a DoFn that has... >> >> def process(self, sentence): >> yield from sentence.split() >> >> >> You could use it with SchemadParDo as: >> >> (p | beam.Create([pvalue.Row(element="hello world", id="id")]) >> | SchemadParDo(SchemadParDo(SplitSentenceDoFn(), input_field="element", >> output_field="word")) >> >> And it'd produce Row(word="hello", id="id") and Row(word=""world", >> id="id") >> >> On Fri, May 9, 2025, 9:57 PM Reuven Lax via dev <dev@beam.apache.org> >> wrote: >> >>> Can you explain a bit how SchemadParDo works? >>> >>> On Fri, May 9, 2025 at 4:49 PM Joey Tran <joey.t...@schrodinger.com> >>> wrote: >>> >>>> I've written a `SchemadParDo(input_field: str, output_field, >>>> dofn:DoFn)` transform for more easily writing a Schemad transform given a >>>> DoFn. >>>> >>>> Is this something worth upstreaming into the Beam Python SDK? I wrote >>>> it to make it easier to convert our current set of dofn's into >>>> schemad dofns for use with the YAML SDK. Just wanted to gauge interest >>>> before setting up the dev env again >>>> >>>
