Skip to main content

pico-kafka

PyPI Ask DeepWiki License: MIT CI (tox matrix) codecov Quality Gate Status Duplicated Lines (%) Maintainability Rating PyPI Downloads Docs Interactive Lab

Kafka for the pico ecosystem: @kafka_consumer methods and declarative @kafka_producer clients over aiokafka.

Installation

pip install pico-kafka

Quick start

kafka:
  bootstrap_servers: kafka.internal:9092
  group_id: myapp

Consume — a component method per topic, JSON value decoded for you:

from pico_ioc import component
from pico_kafka import kafka_consumer

@component
class OrderProjection:
    @kafka_consumer("orders")
    async def on_order(self, message: dict):
        ...

    @kafka_consumer("orders", group_id="analytics")   # independent fan-out
    def on_order_analytics(self, message: dict):
        ...

Produce — stubs, like a pico-httpx client:

from pico_kafka import kafka_producer, produce

@kafka_producer
class OrderEvents:
    @produce("orders")
    def order_created(self, message): ...

Semantics:

  • Consumers and producers run on a dedicated background loop — works in sync scripts, FastAPI apps and workers alike, no lifespan wiring.
  • Each record resolves its component through the container (prototype scope = fresh instance per record).
  • A record whose handler raises is logged and skipped — offsets advance, a poison record cannot stall the partition.
  • Sync produce stubs block until the broker acks; async stubs await it. Everything stops with the container.

Documentation

Full documentation: https://dperezcabrera.github.io/pico-kafka/

Built for AI-assisted development

pico-kafka is part of an ecosystem designed for humans and coding agents building software together. Every package ships AGENTS.md working conventions, an llms.txt machine-readable docs index and documented behaviour pinned by regression tests; pico-testing gives agents a verification loop for their own changes, and releases are gated by the whole ecosystem booting together against real infrastructure. The full story: Built for AI-assisted development.

Install the agent skills for Claude Code or OpenAI Codex:

curl -sL https://raw.githubusercontent.com/dperezcabrera/pico-skills/main/install.sh | bash

The pico-conventions skill teaches the assistant this module's API surface and invariants; /add-component and /add-tests scaffold components and tests that use it.

License

MIT

Metadata

Release files for pico-kafka 0.1.6

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pico-kafka 0.1.6
File Size Uploaded
pico_kafka-0.1.6.tar.gz 28.8 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for pico-kafka 0.1.6
File Interpreter ABI Platform
pico_kafka-0.1.6-py3-none-any.whl Python 3 none any Details

Total release size: 38.3 kB

Release files / pico_kafka-0.1.6.tar.gz

Download URL pico_kafka-0.1.6.tar.gz
Size 28.8 kB
Tags Source
SHA-256 checksum
How to use checksums
0360d8fb9f23ac04f4751c565f6faaec126fee6a23b315ae89897a74948cfdd1
BLAKE2b-256 checksum
How to use checksums
ad7b06bfb06f2c6ca4c9c9159fdffaaed74ee39eaee1b042a3142e338732fa7d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 29, 2026.

Transparency log

Release files / pico_kafka-0.1.6-py3-none-any.whl

Download URL pico_kafka-0.1.6-py3-none-any.whl
Size 9.4 kB
Tags Python 3
SHA-256 checksum
How to use checksums
b9c9b7e85ff6f0483236bd1afd5abedfaccb6fee9dc3468ef01f3d19f75ea86d
BLAKE2b-256 checksum
How to use checksums
0ccb2b15a93da69763259da9f2e442ebd04e76b2e56ac968f130fd9f656e77d8
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Sep 29, 2026.

Transparency log

Release history Release notifications | RSS feed

This release

0.1.6 This release

2 release files

0.1.5

2 release files

0.1.4

2 release files

0.1.3

2 release files

0.1.2

2 release files

0.1.1

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page