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UID:pretalx-pydata-london-2026-BPJEKV@pretalx.com
DTSTART;TZID=GMT:20260606T102000
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DESCRIPTION:Adopting a streaming architecture as a Python developer often m
 eans abandoning the tools and abstractions you know: DataFrames\, batch pr
 ocessing\, familiar data workflows\, in favour of an entirely different me
 ntal model. After ten years of tackling this problem across multiple compa
 nies\, I've learned it doesn't have to be that way.\n\nIn this talk\, I'll
  show how to treat Kafka not as a stream of individual messages but as a s
 ource of micro-batches\, and how to deserialize those messages\, whether J
 SON or Protobuf\, into Arrow-backed DataFrames. The result: your processin
 g code looks the same whether the data comes from a Parquet file or a Kafk
 a topic.\n\nNo heavy framework required. Using confluent-kafka and Apache 
 Arrow\, I'll walk through how to build this from the ground up\, so you un
 derstand every layer of the stack.
DTSTAMP:20260602T223427Z
LOCATION:Doddington Forum
SUMMARY:Kafka Streaming\, the Pythonic Way - Arthur Andres
URL:https://pretalx.com/pydata-london-2026/talk/BPJEKV/
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