Ray with JupyterHub

ODP introduces Ray, a “framework for scaling AI and Python applications.

Example:

import ray
import time
ray.init()
items = [ "one", "two", "three", "four", "five", "six", "seven", "eight", "nine", "ten" ]
 
def get_item(idx: int):
    time.sleep(idx / 10.)
    return idx, items[idx]
 
@ray.remote
def retrieve_task(item):
    return get_item(item)
 
def print_runtime(data, start_time):
    print(f"Runtime: {time.time() - start_time:.2f} seconds, data: ")
    print(*data, sep="\n")
 
start = time.time()
data = [get_item(item) for item in range(len(items))]
print("Time to do it the synchronous way:")
print_runtime(data, start)
 
start = time.time()
object_refs = [ retrieve_task.remote(item) for item in range(len(items))]
data = ray.get(object_refs)
print("Time to do it with ray:")
print_runtime(data, start)

Which gives the following output: