ipyparallel

import ipyparallel as ipp import time import os # NOTE: For this code to run, you must have an ipyparallel cluster running. # Start one from your terminal using: ipcluster start # (e.g., 'ipcluster start --n=4' for 4 engines) try: # Connect to the default cluster profile client = ipp.Client() if not client.ids: raise RuntimeError("No engines found in the cluster. Ensure 'ipcluster start' is running.") print(f"Connected to cluster with {len(client.ids)} engines.") # Get a direct view (all engines, tasks are mapped across them) dview = client[:] # Execute a simple parallel task synchronously def square(x): time.sleep(0.01) # Simulate some work return x * x print("Executing map_sync on range(10)...") results = dview.map_sync(square, range(10)) print(f"Parallel results (first 5): {results[:5]}...") # Execute an asynchronous task on each engine print("Executing async getpid()...") ar = dview.apply_async(lambda : os.getpid()) pids = ar.get() print(f"PIDs from engines: {pids}") except Exception as e: print(f"Could not connect to ipyparallel cluster or encountered an error: {e}") print("Please ensure 'ipcluster start' is running and no firewall is blocking access.")