{"categories":[{"label":"Distributed Computing","url":"https://skillfed.io/packages/category/system-distributed-computing/2"},{"label":"Networking","url":"https://skillfed.io/packages/category/system-networking"}],"enrichment":{"capability":"Faust-streaming is a Python library for building stream processing applications that consume from Kafka topics, perform stateful transformations, and persist distributed key-value state using RocksDB.","skillfed_tags":["kafka-streaming","async-processing","stateful-computation"],"use_cases":["Count page views or events by URL/key using windowed tables and Kafka topic partitioning","Process order streams with stateful validation, enrichment, and async side effects like email notifications","Build real-time dashboards by aggregating metrics into tables that are replicated across worker nodes","Implement event-driven microservices that react to Kafka events with custom business logic","Migrate from Kafka Streams (Java) to Python while preserving stream topology and state semantics"],"what_it_does":"Faust-streaming is a fork of the original Faust project that brings Kafka Streams semantics to Python using async/await and static typing. It lets you write stream processors as simple Python functions decorated with @app.agent(), consuming from Kafka topics and processing events asynchronously. The library handles distributed state through Tables\u2014persistent, replicated key-value stores backed by RocksDB\u2014allowing you to maintain aggregate counts, windowed metrics, and other stateful computations across a cluster of worker instances.\n\nThe package is designed for high-throughput, low-latency event processing pipelines. It supports windowing (tumbling, hopping, sliding), automatic failover via standby replicas, and changelog topics for durability. Unlike other stream frameworks, Faust requires only Kafka and Python\u2014no DSL, no separate cluster manager\u2014making it straightforward to integrate with existing Python libraries like NumPy, Pandas, or Django.","worth_installing":"Yes, if you need to build distributed stream processing applications in Python with Kafka. The fork is actively maintained, supports modern Python versions (3.10\u20133.14), has no known vulnerabilities, and offers a permissive license. Install friction is moderate due to multiple dependencies, but pre-built wheels reduce friction. Not recommended if you need a simpler event queue or if your team lacks async/await experience."},"id":"faust-streaming","links":{"html":"https://skillfed.io/packages/faust-streaming","md":"https://skillfed.io/packages/faust-streaming.md","pypi":"https://pypi.org/project/faust-streaming/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-10","license_spdx":null,"license_treatment":"permissive","name":"faust-streaming","python_support":"supports_current","summary":"Python Stream Processing. A Faust fork"},"popularity":{"monthly_downloads":387857,"position":7041,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.13.2"}