After many of my own attempts, research, digging through source code, and speaking with folks in various channels in the community, I'm starting to wonder if *anyone* has *ever* successfully gotten Avro to work with Python Functions.
(I don't just mean ingesting a byte array with fastavro but actually using the built-in schema support that Pulsar Python functions are intended to support - hence the purpose of combining built-in Avro internals with multi-language support.) This capability is a core part of the community offering to support Python, and as we've standardized on Avro internals, I'm concerned we may have a gap in our ability to support this combination of technologies, which can impact adoption in organizations that have a heavy investment in both Python and Java (such as for different teams) when Avro has already been standardized on. I've brought this question up in various places/groups for almost 3 years now, and I'm starting to wonder if *nobody* has actually done it. I've seen examples of using Python producers and consumers with Avro, but the interaction is different because those interfaces allow the Schema to be explicitly specified. It's not clear from the source code how (or if) this can be done currently with the Python Functions API. If there's a feature gap here, then we need to decide if it's a priority to address. This is becoming increasingly important as the Python userbase is growing significantly, but I'd like to hear thoughts from others, especially since Lari recently asked if we should be considering wider changes to the Function API internals. Devin G. Bost
