SCOOP (Scalable COncurrent Operations in Python) VS pipelines

Compare SCOOP (Scalable COncurrent Operations in Python) vs pipelines and see what are their differences.

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SCOOP (Scalable COncurrent Operations in Python) pipelines
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616 372
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0.0 0.0
about 1 year ago over 4 years ago
Python Nim
LGPL MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

SCOOP (Scalable COncurrent Operations in Python)

Posts with mentions or reviews of SCOOP (Scalable COncurrent Operations in Python). We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning SCOOP (Scalable COncurrent Operations in Python) yet.
Tracking mentions began in Dec 2020.

pipelines

Posts with mentions or reviews of pipelines. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning pipelines yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing SCOOP (Scalable COncurrent Operations in Python) and pipelines you can also consider the following projects:

Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

aiochan - CSP-style concurrency for Python

Thespian Actor Library - Python Actor concurrency library

Wallaroo - Distributed Stream Processing

Faust - Python Stream Processing

eventlet - Concurrent networking library for Python

pyeventbus - Python Eventbus

deco