An interactive parallelization framework which is especially useful in configuring data science workload distribution. Eg. supports openMIP, MPI runs on High Performance Clusters
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.
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Do you think we are missing an alternative of Interactive Parallel Computing with IPython or a related project?
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:
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.
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.
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