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from __future__ import annotations
import asyncio
import random
import threading
from collections import defaultdict
from time import sleep
import pytest
import dask
from dask import delayed
from distributed import (
Client,
as_completed,
get_client,
get_worker,
wait,
worker_client,
)
from distributed.metrics import time
from distributed.utils_test import double, gen_cluster, inc, slowinc
@gen_cluster(client=True)
async def test_submit_from_worker(c, s, a, b):
def func(x):
with worker_client() as c:
x = c.submit(inc, x)
y = c.submit(double, x)
result = x.result() + y.result()
return result
x, y = c.map(func, [10, 20])
xx, yy = await c.gather([x, y])
assert xx == 10 + 1 + (10 + 1) * 2
assert yy == 20 + 1 + (20 + 1) * 2
assert len(s.transition_log) > 10
assert len([id for id in s.clients if id.lower().startswith("client")]) == 1
@gen_cluster(client=True, nthreads=[("127.0.0.1", 1)] * 2)
async def test_scatter_from_worker(c, s, a, b):
def func():
with worker_client() as c:
futures = c.scatter([1, 2, 3, 4, 5])
assert isinstance(futures, (list, tuple))
assert len(futures) == 5
x = dict(get_worker().data)
y = {f.key: i for f, i in zip(futures, [1, 2, 3, 4, 5])}
assert x == y
total = c.submit(sum, futures)
return total.result()
future = c.submit(func)
result = await future
assert result == sum([1, 2, 3, 4, 5])
def func():
with worker_client() as c:
correct = True
for data in [[1, 2], (1, 2), {1, 2}]:
futures = c.scatter(data)
correct &= type(futures) == type(data)
o = object()
futures = c.scatter({"x": o})
correct &= get_worker().data["x"] is o
return correct
future = c.submit(func)
result = await future
assert result is True
start = time()
while not all(ws.nthreads == 1 for ws in s.workers.values()):
await asyncio.sleep(0.1)
assert time() < start + 5
@gen_cluster(client=True, nthreads=[("127.0.0.1", 1)] * 2)
async def test_scatter_singleton(c, s, a, b):
np = pytest.importorskip("numpy")
def func():
with worker_client() as c:
x = np.ones(5)
future = c.scatter(x)
assert future.type == np.ndarray
await c.submit(func)
@gen_cluster(client=True, nthreads=[("127.0.0.1", 1)] * 2)
async def test_gather_multi_machine(c, s, a, b):
a_address = a.address
b_address = b.address
assert a_address != b_address
def func():
with worker_client() as ee:
x = ee.submit(inc, 1, workers=a_address)
y = ee.submit(inc, 2, workers=b_address)
xx, yy = ee.gather([x, y])
return xx, yy
future = c.submit(func)
result = await future
assert result == (2, 3)
@gen_cluster(client=True)
async def test_same_loop(c, s, a, b):
def f():
with worker_client() as lc:
return lc.loop is get_worker().loop
future = c.submit(f)
result = await future
assert result
def test_sync(client):
def mysum():
result = 0
sub_tasks = [delayed(double)(i) for i in range(100)]
with worker_client() as lc:
futures = lc.compute(sub_tasks)
for f in as_completed(futures):
result += f.result()
return result
assert delayed(mysum)().compute() == 9900
@gen_cluster(client=True)
async def test_async(c, s, a, b):
def mysum():
result = 0
sub_tasks = [delayed(double)(i) for i in range(100)]
with worker_client() as lc:
futures = lc.compute(sub_tasks)
for f in as_completed(futures):
result += f.result()
return result
future = c.compute(delayed(mysum)())
await future
start = time()
while len(a.data) + len(b.data) > 1:
await asyncio.sleep(0.1)
assert time() < start + 3
@gen_cluster(client=True, nthreads=[("127.0.0.1", 3)])
async def test_separate_thread_false(c, s, a):
a.count = 0
def f(i):
with worker_client(separate_thread=False) as client:
get_worker().count += 1
assert get_worker().count <= 3
sleep(random.random() / 40)
assert get_worker().count <= 3
get_worker().count -= 1
return i
futures = c.map(f, range(20))
results = await c._gather(futures)
assert list(results) == list(range(20))
@gen_cluster(client=True)
async def test_client_executor(c, s, a, b):
def mysum():
with worker_client() as c:
with c.get_executor() as e:
return sum(e.map(double, range(30)))
future = c.submit(mysum)
result = await future
assert result == 30 * 29
def test_dont_override_default_get(loop):
import dask.bag as db
def f(x):
with worker_client() as c:
return True
b = db.from_sequence([1, 2])
b2 = b.map(f)
with Client(
loop=loop, processes=False, set_as_default=True, dashboard_address=":0"
) as c:
assert dask.base.get_scheduler() == c.get
for _ in range(2):
b2.compute()
assert dask.base.get_scheduler() == c.get
@gen_cluster(client=True)
async def test_local_client_warning(c, s, a, b):
from distributed import local_client
def func(x):
with pytest.warns(
UserWarning, match=r"local_client has moved to worker_client"
):
cmgr = local_client()
with cmgr as c:
return c.submit(inc, x).result()
future = c.submit(func, 10)
result = await future
assert result == 11
@gen_cluster(client=True)
async def test_closing_worker_doesnt_close_client(c, s, a, b):
def func(x):
get_client()
return
await wait(c.map(func, range(10)))
await a.close()
assert c.status == "running"
def test_timeout(client):
def func():
with worker_client(timeout=0) as wc:
print("hello")
future = client.submit(func)
with pytest.raises(EnvironmentError):
result = future.result()
def test_secede_without_stealing_issue_1262():
"""
Tests that seceding works with the Stealing extension disabled
https://github.com/dask/distributed/issues/1262
"""
# run the loop as an inner function so all workers are closed
# and exceptions can be examined
@gen_cluster(client=True, scheduler_kwargs={"extensions": {}})
async def secede_test(c, s, a, b):
def func(x):
with worker_client() as wc:
y = wc.submit(lambda: 1 + x)
return wc.gather(y)
f = await c.gather(c.submit(func, 1))
return c, s, a, b, f
c, s, a, b, f = secede_test()
assert f == 2
@gen_cluster(client=True)
async def test_compute_within_worker_client(c, s, a, b):
@dask.delayed
def f():
with worker_client():
return dask.delayed(lambda x: x)(1).compute()
result = await c.compute(f())
assert result == 1
@gen_cluster(client=True)
async def test_worker_client_rejoins(c, s, a, b):
def f():
with worker_client():
pass
return threading.current_thread() in get_worker().executor._threads
result = await c.submit(f)
assert result
@pytest.mark.xfail(
reason="Flaky due to https://github.com/dask/distributed/issues/5915"
)
@gen_cluster()
async def test_submit_different_names(s, a, b):
# https://github.com/dask/distributed/issues/2058
da = pytest.importorskip("dask.array")
c = await Client(
"localhost:" + s.address.split(":")[-1], loop=s.loop, asynchronous=True
)
try:
X = c.persist(da.random.uniform(size=(100, 10), chunks=50))
await wait(X)
fut = await c.submit(lambda x: x.sum().compute(), X)
assert fut > 0
finally:
await c.close()
@gen_cluster(client=True)
async def test_secede_does_not_claim_worker(c, s, a, b):
"""A seceded task must not block the task running it. Tasks scheduled from
within should be evenly distributed"""
# https://github.com/dask/distributed/issues/5332
def get_addr(x):
w = get_worker()
slowinc(x)
return w.address
def long_running():
with worker_client() as client:
futs = client.map(get_addr, range(100))
workers = defaultdict(int)
for f in futs:
workers[f.result()] += 1
return dict(workers)
res = await c.submit(long_running)
assert len(res) == 2
assert res[a.address] > 25
assert res[b.address] > 25
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