Popularity
7.4
Growing
Activity
9.5
-
2,080
110
836

Description

An interactive parallelization framework which is especially useful in configuring data science workload distribution. Eg. supports openMIP, MPI runs on High Performance Clusters

Code Quality Rank: L3
Programming language: Jupyter Notebook
License: BSD 3-clause "New" or "Revised" License
Latest version: v6.2.4

Interactive Parallel Computing with IPython alternatives and similar packages

Based on the "Science and Data Analysis" category.
Alternatively, view Interactive Parallel Computing with IPython alternatives based on common mentions on social networks and blogs.

Do you think we are missing an alternative of Interactive Parallel Computing with IPython or a related project?

Add another 'Science and Data Analysis' Package

README

Interactive Parallel Computing with IPython

IPython Parallel (ipyparallel) is a Python package and collection of CLI scripts for controlling clusters of IPython processes, built on the Jupyter protocol.

IPython Parallel provides the following commands:

  • ipcluster - start/stop/list clusters
  • ipcontroller - start a controller
  • ipengine - start an engine

Install

Install IPython Parallel:

pip install ipyparallel

This will install and enable the IPython Parallel extensions for Jupyter Notebook and (as of 7.0) Jupyter Lab 3.0.

Run

Start a cluster:

ipcluster start

Use it from Python:

import os
import ipyparallel as ipp

cluster = ipp.Cluster(n=4)
with cluster as rc:
    ar = rc[:].apply_async(os.getpid)
    pid_map = ar.get_dict()

See the docs for more info.