Speed tests with a Stream?

Start by running the two standalone benchmark scripts, comparing the generator loop with Stream.from_iterable() and sink_to_list(). Check the streamz documentation and implementation of source.start() and sink_to_list() to determine whether the polling loop is required. Done means documenting the expected performance and the correct standalone-script usage, or identifying a reproducible defect.

I am trying to compare the speed of operation when a Stream is introduced into the code. These are both scripts that need to be run.

A 'plain' Python example:

from timeit import default_timer as timer
LIMIT = 100000

def sequencer(limit=LIMIT):
    num = 0
    while num < limit:
        yield num
        num += 1

L = []
start = timer()
for i in sequencer():
   L.append(i)

end = timer()
print(end - start)

This takes about 17 milliseconds to run.

An attempt to replicate the above with streamz:

from timeit import default_timer as timer
from streamz import Stream
LIMIT = 100000

def sequencer(limit=LIMIT):
    num = 0
    while num < limit:
        yield num
        num += 1

source = Stream.from_iterable(sequencer())
L = source.sink_to_list()

start = timer()
source.start()
while True:
    if len(L) >= LIMIT:
        break

end = timer()
print(end - start)

This takes about 1200 milliseconds to run. Is this the expected slowdown (two orders-of-magnitude)?

I am not sure though if the streamz code is correct? Its based off of the examples in the docs, but those examples all seem geared towards use in the shell rather than in standalone scripts. If you omit the while True: section, then no data ends up in the output list?