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import asyncio
from operator import add
import random
import time
import pytest
pytest.importorskip('dask.distributed')
from tornado import gen
from streamz.dask import scatter
from streamz import RefCounter, Stream
from distributed import Future, Client
from distributed.utils import sync
from distributed.utils_test import gen_cluster, inc, cluster, loop, slowinc # noqa: F401
@gen_cluster(client=True)
async def test_map(c, s, a, b):
source = Stream(asynchronous=True)
futures = scatter(source).map(inc)
futures_L = futures.sink_to_list()
L = futures.gather().sink_to_list()
for i in range(5):
await source.emit(i)
assert L == [1, 2, 3, 4, 5]
assert all(isinstance(f, Future) for f in futures_L)
@gen_cluster(client=True)
async def test_map_on_dict(c, s, a, b):
# dask treats dicts differently, so we have to make sure
# the user sees no difference in the streamz api.
# Regression test against #336
def add_to_dict(d):
d["x"] = d["i"]
return d
source = Stream(asynchronous=True)
futures = source.scatter().map(add_to_dict)
L = futures.gather().sink_to_list()
for i in range(5):
await source.emit({"i": i})
assert len(L) == 5
for i, item in enumerate(sorted(L, key=lambda x: x["x"])):
assert item["x"] == i
assert item["i"] == i
@gen_cluster(client=True)
async def test_partition_then_scatter_async(c, s, a, b):
# Ensure partition w/ timeout before scatter works correctly for
# asynchronous
start = time.monotonic()
source = Stream(asynchronous=True)
L = source.partition(2, timeout=.1).scatter().map(
lambda x: [xx+1 for xx in x]).buffer(2).gather().flatten().sink_to_list()
rc = RefCounter(loop=source.loop)
for i in range(3):
await source.emit(i, metadata=[{'ref': rc}])
while rc.count != 0 and time.monotonic() - start < 1.:
await gen.sleep(1e-2)
assert L == [1, 2, 3]
def test_partition_then_scatter_sync():
# Ensure partition w/ timeout before scatter works correctly for synchronous
with cluster() as (s, [a, b]):
with Client(s['address']) as client: # noqa: F841
start = time.monotonic()
source = Stream()
L = source.partition(2, timeout=.1).scatter().map(
lambda x: [xx+1 for xx in x]).gather().flatten().sink_to_list()
assert source.loop is client.loop
rc = RefCounter()
for i in range(3):
source.emit(i, metadata=[{'ref': rc}])
while rc.count != 0 and time.monotonic() - start < 2.:
time.sleep(1e-2)
assert L == [1, 2, 3]
@gen_cluster(client=True)
async def test_non_unique_emit(c, s, a, b):
"""Regression for https://github.com/python-streamz/streams/issues/397
Non-unique stream entries still need to each be processed.
"""
source = Stream(asynchronous=True)
futures = source.scatter().map(lambda x: random.random())
L = futures.gather().sink_to_list()
for _ in range(3):
# Emit non-unique values
await source.emit(0)
assert len(L) == 3
assert L[0] != L[1] or L[0] != L[2]
@gen_cluster(client=True)
async def test_scan(c, s, a, b):
source = Stream(asynchronous=True)
futures = scatter(source).map(inc).scan(add)
futures_L = futures.sink_to_list()
L = futures.gather().sink_to_list()
for i in range(5):
await source.emit(i)
assert L == [1, 3, 6, 10, 15]
assert all(isinstance(f, Future) for f in futures_L)
@gen_cluster(client=True)
async def test_scan_state(c, s, a, b):
source = Stream(asynchronous=True)
def f(acc, i):
acc = acc + i
return acc, acc
L = scatter(source).scan(f, returns_state=True).gather().sink_to_list()
for i in range(3):
await source.emit(i)
assert L == [0, 1, 3]
@gen_cluster(client=True)
async def test_zip(c, s, a, b):
a = Stream(asynchronous=True)
b = Stream(asynchronous=True)
c = scatter(a).zip(scatter(b))
L = c.gather().sink_to_list()
await a.emit(1)
await b.emit('a')
await a.emit(2)
await b.emit('b')
assert L == [(1, 'a'), (2, 'b')]
@gen_cluster(client=True)
async def test_accumulate(c, s, a, b):
source = Stream(asynchronous=True)
L = source.scatter().accumulate(lambda acc, x: acc + x, with_state=True).gather().sink_to_list()
for i in range(3):
await source.emit(i)
assert L[-1][1] == 3
def test_sync(): # noqa: F811
with cluster() as (s, [a, b]):
with Client(s['address']) as client: # noqa: F841
source = Stream()
L = source.scatter().map(inc).gather().sink_to_list()
async def f():
for i in range(10):
await source.emit(i, asynchronous=True)
sync(client.loop, f)
assert L == list(map(inc, range(10)))
def test_sync_2(): # noqa: F811
with cluster() as (s, [a, b]):
with Client(s['address']): # noqa: F841
source = Stream()
L = source.scatter().map(inc).gather().sink_to_list()
for i in range(10):
source.emit(i)
assert len(L) == i + 1
assert L == list(map(inc, range(10)))
@gen_cluster(client=True, nthreads=[('127.0.0.1', 1)] * 2)
async def test_buffer(c, s, a, b):
source = Stream(asynchronous=True)
L = source.scatter().map(slowinc, delay=0.5).buffer(5).gather().sink_to_list()
start = time.time()
for i in range(5):
await source.emit(i)
end = time.time()
assert end - start < 0.5
for i in range(5, 10):
await source.emit(i)
end2 = time.time()
assert end2 - start > (0.5 / 3)
while len(L) < 10:
await gen.sleep(0.01)
assert time.time() - start < 5
assert L == list(map(inc, range(10)))
assert source.loop == c.loop
def test_buffer_sync(): # noqa: F811
with cluster() as (s, [a, b]):
with Client(s['address']) as c: # noqa: F841
source = Stream()
buff = source.scatter().map(slowinc, delay=0.5).buffer(5)
L = buff.gather().sink_to_list()
start = time.time()
for i in range(5):
source.emit(i)
end = time.time()
assert end - start < 0.5
for i in range(5, 10):
source.emit(i)
while len(L) < 10:
time.sleep(0.01)
assert time.time() - start < 5
assert L == list(map(inc, range(10)))
@pytest.mark.asyncio
@pytest.mark.xfail(reason='')
async def test_stream_shares_client_loop(): # noqa: F811
with cluster() as (s, [a, b]):
with Client(s['address']) as client: # noqa: F841
source = Stream()
d = source.timed_window('20ms').scatter() # noqa: F841
assert source.loop is client.loop
@gen_cluster(client=True)
async def test_starmap(c, s, a, b):
def add(x, y, z=0):
return x + y + z
source = Stream(asynchronous=True)
L = source.scatter().starmap(add, z=10).gather().sink_to_list()
for i in range(5):
await source.emit((i, i))
assert L == [10, 12, 14, 16, 18]
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