Using IPython for parallel computing¶
Oct 18, 2021
Installing IPython Parallel¶
As of 4.0, IPython parallel is now a standalone package called
You can install it with:
pip install ipyparallel
conda install ipyparallel
As of IPython Parallel 7, this will include installing/enabling an extension for both the classic Jupyter Notebook and JupyterLab ≥ 3.0.
A quick example to:
allocate a cluster (collection of IPython engines for use in parallel)
run a collection of tasks on the cluster
wait interactively for results
cleanup resources after the task is done
import time import ipyparallel as ipp task_durations =  * 25 # request a cluster with ipp.Cluster() as rc: # get a view on the cluster view = rc.load_balanced_view() # submit the tasks asyncresult = view.map_async(time.sleep, task_durations) # wait interactively for results asyncresult.wait_interactive() # retrieve actual results result = asyncresult.get() # at this point, the cluster processes have been shutdown
Follow the tutorial to learn more.