Skip to main content

Reactive data science

Project description

The Reactive Machine Learning Framework

https://badge.fury.io/py/makinage.svg Github WorkFlows Documentation

Maki Nage is a Reactive Data Science framework designed to work on streaming data.

This repository contains the Maki Nage CLI tools, used to deploy RxSci based applications on a Kafka cluster.

Installation

The Maki Nage CLI tools are available on pypi:

pip install makinage

Getting started

An application can be started by providing its manifest file. See the documentation for more information.

makinage --config myconfig.yaml

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

makinage-0.5.0.tar.gz (11.3 kB view details)

Uploaded Source

File details

Details for the file makinage-0.5.0.tar.gz.

File metadata

  • Download URL: makinage-0.5.0.tar.gz
  • Upload date:
  • Size: 11.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/49.2.1 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.8.6

File hashes

Hashes for makinage-0.5.0.tar.gz
Algorithm Hash digest
SHA256 7dbe968ddcfb907236f9713ddf8a147c8161a5d7ad00f10b3fe1b6a26f0faf9a
MD5 95e4f767590d6635a01a20ca1933258c
BLAKE2b-256 f65f98330a1b2144a255a79998773668634703607dce3e1c99730251acd22525

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page