Using IPython for parallel computing¶
- Release
7.1.0
- Date
Sep 30, 2021
Installing IPython Parallel¶
As of 4.0, IPython parallel is now a standalone package called ipyparallel
.
You can install it with:
pip install ipyparallel
or:
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.
Quickstart¶
IPython Parallel
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 = [1] * 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.