🌊 Online machine learning in Python
Utils for streaming large files (S3, HDFS, gzip, bz2...)
Python Stream Processing
Python Streaming DataFrames for Kafka
Real-time stream processing for python
A machine learning package for streaming data in Python. The other ancestor of River.
Optimal binning: monotonic binning with constraints. Support batch & stream optimal binning. Scorecard modelling and counterfactual explanations.
🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams
distributed structured concurrency
Benchmarks for data processing systems: Pathway Live Data Framework, Spark, Flink, Kafka Streams
Streaming anomaly detection in Python: 16 online detectors (xStream, LODA, RS-Hash, Half-Space Trees, RRCF…) plus calibration and prequential evaluation for real-time data.
A stream processing runtime that allows connecting any streaming data source to any destination and act on it
Clustering for arbitrary data and dissimilarity function
Materialize is a streaming database for real-time analytics. This is a collection of Materialize demos and tutorials.
CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system
AI agent skills for building, operating and troubleshooting Apache Kafka applications. Topic audit, consumer lag, schema review, security, connectors and DLQ
Streaming Synthetic Sales Data Generator: Streaming sales data generator for Apache Kafka, written in Python
Stream Processing Made Easy
Slipstream provides a data-flow model to simplify development of stateful streaming applications.
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