# python-streamz/streamz

Real-time stream processing for python

Repository: https://github.com/python-streamz/streamz
Canonical: https://ross.abutalabs.com/products/streamz
Homepage: https://streamz.readthedocs.io/en/latest/
Language: Python
License: BSD-3-Clause
License Family: permissive
Topics: streaming-data, python, async, real-time
Last push: 2026-04-07T14:11:52+00:00

## Health v2 (maintenance only)
Score: 66/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 76, release rhythm 35, longevity 100
- inputs: {"age_days": 3438, "days_push": 148, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1303, forks 149 (observed 2026-08-28T04:04:18.351226+00:00)

## What it is
Streamz is a Python library for building pipelines that manage continuous streams of real-time data. It supports complex pipelines with branching, joining, flow control, feedback, and back pressure, and integrates with Pandas and cuDF for streaming tabular data operations.

## Use cases
- process real-time data streams in python
- build streaming data pipelines with branching and joins
- apply pandas operations to continuous streaming dataframes
- handle back pressure in async data pipelines
- stream process kafka data with cudf on gpu
- monitor live event feeds and transform them on the fly

## When to choose
- you need lightweight real-time stream processing in pure python
- you want streaming dataframe operations with pandas or cuDF
- your pipelines need flow control, feedback, or back pressure

## When to avoid
- you need large-scale distributed stream processing like Flink or Spark Streaming
- your data is batch-oriented rather than continuous
- you need a maintained project with frequent releases and active development

## Facets
- artifact type: library
- maturity: maintenance
- function: streaming, etl, data-science
- domain: big-data
- platform: python, cross-platform
- tags: stream-processing, data-pipelines, backpressure, pandas, async, data-engineering, real-time

## Member repositories
- python-streamz/streamz (main) score 66

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:18.351226+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:51:13.723954+00:00, confidence not recorded.
  - readme: https://github.com/python-streamz/streamz (fetched 2026-08-28T04:04:18.351226+00:00, sha f17551b0a65c)
  - registry_pypi: https://pypi.org/pypi/streamz/json (fetched 2026-08-29T12:09:50.131060+00:00, sha aef966a40788)
- Data as of 2026-08-30T08:39:29.467469+00:00.