Connection
Base URL, credentials and a reachable server.
Product
Product features · Stream reservoir sampling
01
Use SampleThicket to distinguish the retained reservoir from the input stream already consumed.
Selection
A model available through the configured endpoint.
Capabilities
Context limits and tool support are determined by the model and server.
Stream reservoir sampling
● ● ●SampleThicket●
A concrete starting point · Stream reservoir sampling ×
from random import Random
def reservoir_sample(items, size, seed):
if type(size) is not int or not 0 <= size <= 32:
raise ValueError("size.range")
if type(seed) is not int or not 0 <= seed < 2**32:
raise ValueError("seed.range")
rng, sample, count = Random(seed), [], 0
for index, item in enumerate(items):
count = index + 1
if count > 1000:
raise ValueError("stream.limit")
if index < size:
sample.append(item)
elif size:
position = rng.randrange(count)
if position < size:
sample[position] = item
if size > count:
raise ValueError("stream.short")
return sample✳Select a reservoir of at most 32 items from a finite stream of at most 1000 items using a local seeded generator.
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