pytest collection errors after following setup guidelines

[GenevieveBuckley]

What happened:
After following the new contributor guidelines for distributed, pytest finds both errors in test collection and failing tests.

What you expected to happen:
I had expected the pytest suite to complete without failures.

Presumably there is something wonky with my sockets, but I haven't done anything strange recently and should have the defaults for everything in Ubuntu.

Minimal Complete Verifiable Example:

git clone git@github.com:dask/distributed.git
cd distributed
conda env create --file continuous_integration/environment-3.8.yaml
conda activate dask-distributed
python -m pip install -e .
py.test distributed --verbose

pytest collection errors:

$ py.test distributed --verbose
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-6.2.4, py-1.10.0, pluggy-0.13.1 -- /home/genevieve/anaconda3/envs/dask-distributed/bin/python
cachedir: .pytest_cache
rootdir: /home/genevieve/GitHub/temp/distributed, configfile: setup.cfg
plugins: asyncio-0.12.0, rerunfailures-10.1, repeat-0.8.0, timeout-1.4.2
timeout: 300.0s
timeout method: thread
timeout func_only: False
collected 2180 items / 2 errors / 10 skipped / 2168 selected                   

==================================== ERRORS ====================================
____________ ERROR collecting distributed/comm/tests/test_comms.py _____________
distributed/utils.py:133: in _get_ip
    sock.connect((host, port))
E   OSError: [Errno 101] Network is unreachable

During handling of the above exception, another exception occurred:
distributed/comm/tests/test_comms.py:47: in <module>
    EXTERNAL_IP6 = get_ipv6()
distributed/utils.py:164: in get_ipv6
    return _get_ip(host, port, family=socket.AF_INET6)
cytoolz/functoolz.pyx:476: in cytoolz.functoolz._memoize.__call__
    ???
distributed/utils.py:142: in _get_ip
    addr_info = socket.getaddrinfo(
../../../anaconda3/envs/dask-distributed/lib/python3.8/socket.py:918: in getaddrinfo
    for res in _socket.getaddrinfo(host, port, family, type, proto, flags):
E   socket.gaierror: [Errno -5] No address associated with hostname
______________ ERROR collecting distributed/comm/tests/test_ws.py ______________
distributed/utils.py:133: in _get_ip
    sock.connect((host, port))
E   OSError: [Errno 101] Network is unreachable

During handling of the above exception, another exception occurred:
distributed/comm/tests/test_ws.py:23: in <module>
    from .test_comms import check_tls_extra
<frozen importlib._bootstrap>:991: in _find_and_load
    ???
<frozen importlib._bootstrap>:975: in _find_and_load_unlocked
    ???
<frozen importlib._bootstrap>:671: in _load_unlocked
    ???
../../../anaconda3/envs/dask-distributed/lib/python3.8/site-packages/_pytest/assertion/rewrite.py:170: in exec_module
    exec(co, module.__dict__)
distributed/comm/tests/test_comms.py:47: in <module>
    EXTERNAL_IP6 = get_ipv6()
distributed/utils.py:164: in get_ipv6
    return _get_ip(host, port, family=socket.AF_INET6)
cytoolz/functoolz.pyx:476: in cytoolz.functoolz._memoize.__call__
    ???
distributed/utils.py:142: in _get_ip
    addr_info = socket.getaddrinfo(
../../../anaconda3/envs/dask-distributed/lib/python3.8/socket.py:918: in getaddrinfo
    for res in _socket.getaddrinfo(host, port, family, type, proto, flags):
E   socket.gaierror: [Errno -5] No address associated with hostname
=========================== short test summary info ============================
SKIPPED [1] distributed/comm/tests/test_ucx.py:7: could not import 'ucp': No module named 'ucp'
SKIPPED [1] distributed/comm/tests/test_ucx_config.py:19: could not import 'ucp': No module named 'ucp'
SKIPPED [1] distributed/diagnostics/tests/test_nvml.py:7: could not import 'pynvml': No module named 'pynvml'
SKIPPED [1] distributed/protocol/tests/test_arrow.py:3: could not import 'pyarrow': No module named 'pyarrow'
SKIPPED [1] distributed/protocol/tests/test_cupy.py:9: could not import 'cupy': No module named 'cupy'
SKIPPED [1] distributed/protocol/tests/test_keras.py:3: could not import 'keras': No module named 'tensorflow'
SKIPPED [1] distributed/protocol/tests/test_numba.py:9: could not import 'numba.cuda': No module named 'numba'
SKIPPED [1] distributed/protocol/tests/test_rmm.py:8: could not import 'numba.cuda': No module named 'numba'
SKIPPED [1] distributed/protocol/tests/test_sparse.py:4: could not import 'sparse': No module named 'sparse'
SKIPPED [1] distributed/protocol/tests/test_torch.py:6: could not import 'torch': No module named 'torch'
ERROR distributed/comm/tests/test_comms.py - socket.gaierror: [Errno -5] No a...
ERROR distributed/comm/tests/test_ws.py - socket.gaierror: [Errno -5] No addr...
!!!!!!!!!!!!!!!!!!! Interrupted: 2 errors during collection !!!!!!!!!!!!!!!!!!!

Anything else we need to know?:

The test collection errors occur in pytest distributed/comm/tests

Additionally, several cli tests fail on my machine as well: pytest distributed/cli/tests

FAILED distributed/cli/tests/test_dask_scheduler.py::test_defaults - socket.g...
FAILED distributed/cli/tests/test_dask_scheduler.py::test_hostport - socket.g...
FAILED distributed/cli/tests/test_dask_scheduler.py::test_no_dashboard - asse...
FAILED distributed/cli/tests/test_dask_scheduler.py::test_dashboard_whitelist

Details:

=================================== FAILURES ===================================
________________________________ test_defaults _________________________________

host = '2001:4860:4860::8888', port = 80, family = <AddressFamily.AF_INET6: 10>

    @toolz.memoize
    def _get_ip(host, port, family):
        # By using a UDP socket, we don't actually try to connect but
        # simply select the local address through which *host* is reachable.
        sock = socket.socket(family, socket.SOCK_DGRAM)
        try:
>           sock.connect((host, port))
E           OSError: [Errno 101] Network is unreachable

distributed/utils.py:133: OSError

During handling of the above exception, another exception occurred:

loop = <tornado.platform.asyncio.AsyncIOLoop object at 0x7f361c988f70>

    def test_defaults(loop):
        with popen(["dask-scheduler"]):
    
            async def f():
                # Default behaviour is to listen on all addresses
                await assert_can_connect_from_everywhere_4_6(8786, timeout=5.0)
    
            with Client(f"127.0.0.1:{Scheduler.default_port}", loop=loop) as c:
>               c.sync(f)

distributed/cli/tests/test_dask_scheduler.py:36: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
distributed/client.py:845: in sync
    return sync(
distributed/utils.py:325: in sync
    raise exc.with_traceback(tb)
distributed/utils.py:308: in f
    result[0] = yield future
../../../anaconda3/envs/dask-distributed/lib/python3.8/site-packages/tornado/gen.py:762: in run
    value = future.result()
distributed/cli/tests/test_dask_scheduler.py:33: in f
    await assert_can_connect_from_everywhere_4_6(8786, timeout=5.0)
distributed/utils_test.py:1193: in assert_can_connect_from_everywhere_4_6
    assert_can_connect("%s://[%s]:%d" % (protocol, get_ipv6(), port), **kwargs),
distributed/utils.py:164: in get_ipv6
    return _get_ip(host, port, family=socket.AF_INET6)
cytoolz/functoolz.pyx:476: in cytoolz.functoolz._memoize.__call__
    ???
distributed/utils.py:142: in _get_ip
    addr_info = socket.getaddrinfo(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

host = 'genevieve-G5-5500', port = 80, family = <AddressFamily.AF_INET6: 10>
type = <SocketKind.SOCK_DGRAM: 2>, proto = 17, flags = 0

    def getaddrinfo(host, port, family=0, type=0, proto=0, flags=0):
        """Resolve host and port into list of address info entries.
    
        Translate the host/port argument into a sequence of 5-tuples that contain
        all the necessary arguments for creating a socket connected to that service.
        host is a domain name, a string representation of an IPv4/v6 address or
        None. port is a string service name such as 'http', a numeric port number or
        None. By passing None as the value of host and port, you can pass NULL to
        the underlying C API.
    
        The family, type and proto arguments can be optionally specified in order to
        narrow the list of addresses returned. Passing zero as a value for each of
        these arguments selects the full range of results.
        """
        # We override this function since we want to translate the numeric family
        # and socket type values to enum constants.
        addrlist = []
>       for res in _socket.getaddrinfo(host, port, family, type, proto, flags):
E       socket.gaierror: [Errno -5] No address associated with hostname

../../../anaconda3/envs/dask-distributed/lib/python3.8/socket.py:918: gaierror
----------------------------- Captured stdout call -----------------------------


Print from stderr
  /
=================

distributed.scheduler - INFO - -----------------------------------------------
distributed.http.proxy - INFO - To route to workers diagnostics web server please install jupyter-server-proxy: python -m pip install jupyter-server-proxy
/home/genevieve/GitHub/temp/distributed/distributed/node.py:160: UserWarning: Port 8787 is already in use.
Perhaps you already have a cluster running?
Hosting the HTTP server on port 33299 instead
  warnings.warn(
distributed.scheduler - INFO - -----------------------------------------------
distributed.scheduler - INFO - Clear task state
distributed.scheduler - INFO -   Scheduler at:  tcp://192.168.1.102:8786
distributed.scheduler - INFO -   dashboard at:                    :33299
distributed.scheduler - INFO - Receive client connection: Client-c457fb8c-fe6f-11eb-b6c8-e19f018f439a
distributed.core - INFO - Starting established connection
distributed.scheduler - INFO - Remove client Client-c457fb8c-fe6f-11eb-b6c8-e19f018f439a
distributed.scheduler - INFO - Remove client Client-c457fb8c-fe6f-11eb-b6c8-e19f018f439a
distributed.scheduler - INFO - Close client connection: Client-c457fb8c-fe6f-11eb-b6c8-e19f018f439a
distributed.scheduler - INFO - End scheduler at 'tcp://192.168.1.102:8786'
Traceback (most recent call last):
  File "/home/genevieve/anaconda3/envs/dask-distributed/bin/dask-scheduler", line 33, in <module>
    sys.exit(load_entry_point('distributed', 'console_scripts', 'dask-scheduler')())
  File "/home/genevieve/GitHub/temp/distributed/distributed/cli/dask_scheduler.py", line 217, in go
    main()
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/click/core.py", line 1137, in __call__
    return self.main(*args, **kwargs)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/click/core.py", line 1062, in main
    rv = self.invoke(ctx)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/click/core.py", line 1404, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/click/core.py", line 763, in invoke
    return __callback(*args, **kwargs)
  File "/home/genevieve/GitHub/temp/distributed/distributed/cli/dask_scheduler.py", line 208, in main
    loop.run_sync(run)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/tornado/ioloop.py", line 529, in run_sync
    raise TimeoutError("Operation timed out after %s seconds" % timeout)
tornado.util.TimeoutError: Operation timed out after None seconds



Print from stdout
=================


________________________________ test_hostport _________________________________

host = '2001:4860:4860::8888', port = 80, family = <AddressFamily.AF_INET6: 10>

    @toolz.memoize
    def _get_ip(host, port, family):
        # By using a UDP socket, we don't actually try to connect but
        # simply select the local address through which *host* is reachable.
        sock = socket.socket(family, socket.SOCK_DGRAM)
        try:
>           sock.connect((host, port))
E           OSError: [Errno 101] Network is unreachable

distributed/utils.py:133: OSError

During handling of the above exception, another exception occurred:

loop = <tornado.platform.asyncio.AsyncIOLoop object at 0x7f361bae7610>

    def test_hostport(loop):
        with popen(["dask-scheduler", "--no-dashboard", "--host", "127.0.0.1:8978"]):
    
            async def f():
                # The scheduler's main port can't be contacted from the outside
                await assert_can_connect_locally_4(8978, timeout=5.0)
    
            with Client("127.0.0.1:8978", loop=loop) as c:
                assert len(c.nthreads()) == 0
>               c.sync(f)

distributed/cli/tests/test_dask_scheduler.py:51: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
distributed/client.py:845: in sync
    return sync(
distributed/utils.py:325: in sync
    raise exc.with_traceback(tb)
distributed/utils.py:308: in f
    result[0] = yield future
../../../anaconda3/envs/dask-distributed/lib/python3.8/site-packages/tornado/gen.py:762: in run
    value = future.result()
distributed/cli/tests/test_dask_scheduler.py:47: in f
    await assert_can_connect_locally_4(8978, timeout=5.0)
distributed/utils_test.py:1226: in assert_can_connect_locally_4
    assert_cannot_connect("tcp://[%s]:%d" % (get_ipv6(), port), **kwargs),
distributed/utils.py:164: in get_ipv6
    return _get_ip(host, port, family=socket.AF_INET6)
cytoolz/functoolz.pyx:476: in cytoolz.functoolz._memoize.__call__
    ???
distributed/utils.py:142: in _get_ip
    addr_info = socket.getaddrinfo(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

host = 'genevieve-G5-5500', port = 80, family = <AddressFamily.AF_INET6: 10>
type = <SocketKind.SOCK_DGRAM: 2>, proto = 17, flags = 0

    def getaddrinfo(host, port, family=0, type=0, proto=0, flags=0):
        """Resolve host and port into list of address info entries.
    
        Translate the host/port argument into a sequence of 5-tuples that contain
        all the necessary arguments for creating a socket connected to that service.
        host is a domain name, a string representation of an IPv4/v6 address or
        None. port is a string service name such as 'http', a numeric port number or
        None. By passing None as the value of host and port, you can pass NULL to
        the underlying C API.
    
        The family, type and proto arguments can be optionally specified in order to
        narrow the list of addresses returned. Passing zero as a value for each of
        these arguments selects the full range of results.
        """
        # We override this function since we want to translate the numeric family
        # and socket type values to enum constants.
        addrlist = []
>       for res in _socket.getaddrinfo(host, port, family, type, proto, flags):
E       socket.gaierror: [Errno -5] No address associated with hostname

../../../anaconda3/envs/dask-distributed/lib/python3.8/socket.py:918: gaierror
----------------------------- Captured stdout call -----------------------------


Print from stderr
  /
=================

distributed.scheduler - INFO - -----------------------------------------------
distributed.http.proxy - INFO - To route to workers diagnostics web server please install jupyter-server-proxy: python -m pip install jupyter-server-proxy
/home/genevieve/GitHub/temp/distributed/distributed/node.py:160: UserWarning: Port 8787 is already in use.
Perhaps you already have a cluster running?
Hosting the HTTP server on port 45903 instead
  warnings.warn(
distributed.scheduler - INFO - -----------------------------------------------
distributed.scheduler - INFO - Clear task state
distributed.scheduler - INFO -   Scheduler at:      tcp://127.0.0.1:8978
distributed.scheduler - INFO -   dashboard at:           127.0.0.1:45903
distributed.scheduler - INFO - Receive client connection: Client-c5649c23-fe6f-11eb-b6c8-e19f018f439a
distributed.core - INFO - Starting established connection
distributed.scheduler - INFO - Remove client Client-c5649c23-fe6f-11eb-b6c8-e19f018f439a
distributed.scheduler - INFO - Remove client Client-c5649c23-fe6f-11eb-b6c8-e19f018f439a
distributed.scheduler - INFO - Close client connection: Client-c5649c23-fe6f-11eb-b6c8-e19f018f439a
distributed.scheduler - INFO - End scheduler at 'tcp://127.0.0.1:8978'
Traceback (most recent call last):
  File "/home/genevieve/anaconda3/envs/dask-distributed/bin/dask-scheduler", line 33, in <module>
    sys.exit(load_entry_point('distributed', 'console_scripts', 'dask-scheduler')())
  File "/home/genevieve/GitHub/temp/distributed/distributed/cli/dask_scheduler.py", line 217, in go
    main()
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/click/core.py", line 1137, in __call__
    return self.main(*args, **kwargs)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/click/core.py", line 1062, in main
    rv = self.invoke(ctx)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/click/core.py", line 1404, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/click/core.py", line 763, in invoke
    return __callback(*args, **kwargs)
  File "/home/genevieve/GitHub/temp/distributed/distributed/cli/dask_scheduler.py", line 208, in main
    loop.run_sync(run)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/tornado/ioloop.py", line 529, in run_sync
    raise TimeoutError("Operation timed out after %s seconds" % timeout)
tornado.util.TimeoutError: Operation timed out after None seconds



Print from stdout
=================


______________________________ test_no_dashboard _______________________________

loop = <tornado.platform.asyncio.AsyncIOLoop object at 0x7f361bbdc670>

    def test_no_dashboard(loop):
        with popen(["dask-scheduler", "--no-dashboard"]):
            with Client(f"127.0.0.1:{Scheduler.default_port}", loop=loop):
                response = requests.get("http://127.0.0.1:8787/status/")
>               assert response.status_code == 404
E               assert 200 == 404
E                 +200
E                 -404

distributed/cli/tests/test_dask_scheduler.py:58: AssertionError
----------------------------- Captured stdout call -----------------------------


Print from stderr
  /
=================

distributed.scheduler - INFO - -----------------------------------------------
distributed.http.proxy - INFO - To route to workers diagnostics web server please install jupyter-server-proxy: python -m pip install jupyter-server-proxy
/home/genevieve/GitHub/temp/distributed/distributed/node.py:160: UserWarning: Port 8787 is already in use.
Perhaps you already have a cluster running?
Hosting the HTTP server on port 43953 instead
  warnings.warn(
distributed.scheduler - INFO - -----------------------------------------------
distributed.scheduler - INFO - Clear task state
distributed.scheduler - INFO -   Scheduler at:  tcp://192.168.1.102:8786
distributed.scheduler - INFO -   dashboard at:                    :43953
distributed.scheduler - INFO - Receive client connection: Client-c67c7632-fe6f-11eb-b6c8-e19f018f439a
distributed.core - INFO - Starting established connection
distributed.scheduler - INFO - Remove client Client-c67c7632-fe6f-11eb-b6c8-e19f018f439a
distributed.scheduler - INFO - Remove client Client-c67c7632-fe6f-11eb-b6c8-e19f018f439a
distributed.scheduler - INFO - Close client connection: Client-c67c7632-fe6f-11eb-b6c8-e19f018f439a
distributed.scheduler - INFO - End scheduler at 'tcp://192.168.1.102:8786'
Traceback (most recent call last):
  File "/home/genevieve/anaconda3/envs/dask-distributed/bin/dask-scheduler", line 33, in <module>
    sys.exit(load_entry_point('distributed', 'console_scripts', 'dask-scheduler')())
  File "/home/genevieve/GitHub/temp/distributed/distributed/cli/dask_scheduler.py", line 217, in go
    main()
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/click/core.py", line 1137, in __call__
    return self.main(*args, **kwargs)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/click/core.py", line 1062, in main
    rv = self.invoke(ctx)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/click/core.py", line 1404, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/click/core.py", line 763, in invoke
    return __callback(*args, **kwargs)
  File "/home/genevieve/GitHub/temp/distributed/distributed/cli/dask_scheduler.py", line 208, in main
    loop.run_sync(run)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/tornado/ioloop.py", line 529, in run_sync
    raise TimeoutError("Operation timed out after %s seconds" % timeout)
tornado.util.TimeoutError: Operation timed out after None seconds



Print from stdout
=================


___________________________ test_dashboard_whitelist ___________________________

loop = <tornado.platform.asyncio.AsyncIOLoop object at 0x7f361bae7b50>

    @pytest.mark.skipif(not LINUX, reason="Need 127.0.0.2 to mean localhost")
    def test_dashboard_whitelist(loop):
        pytest.importorskip("bokeh")
        with pytest.raises(Exception):
>           requests.get("http://localhost:8787/status/").ok
E           Failed: DID NOT RAISE <class 'Exception'>

distributed/cli/tests/test_dask_scheduler.py:123: Failed

Environment:

• Dask version: latest 2021.08.0
• Python version: 3.8
• Operating System: Ubuntu 20.04
• Install method (conda, pip, source): conda environment creation, pip editable installation of distributed

[forana]

Also on ubuntu 20.04 and python 3.8.10 - seeing the same test failures.

[ncclementi]

cc: @jrbourbeau

[QuLogic]

Try to export DISABLE_IPV6=1; see #4514

[GenevieveBuckley]

Thanks @QuLogic export DISABLE_IPV6=1 does help with the test collection errors.

Still, lots of test failures now

Details:

pytest
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-6.2.4, py-1.10.0, pluggy-0.13.1 -- /home/genevieve/anaconda3/envs/dask-distributed/bin/python
cachedir: .pytest_cache
rootdir: /home/genevieve/GitHub/distributed, configfile: setup.cfg
plugins: asyncio-0.12.0, rerunfailures-10.1, repeat-0.8.0, timeout-1.4.2, anyio-3.3.0
timeout: 300.0s
timeout method: thread
timeout func_only: False
collected 2250 items / 10 skipped / 2240 selected                              

distributed/cli/tests/test_dask_scheduler.py::test_defaults FAILED       [  0%]
distributed/cli/tests/test_dask_scheduler.py::test_hostport FAILED       [  0%]
distributed/cli/tests/test_dask_scheduler.py::test_no_dashboard FAILED   [  0%]
distributed/cli/tests/test_dask_scheduler.py::test_dashboard FAILED      [  0%]
distributed/cli/tests/test_dask_scheduler.py::test_dashboard_non_standard_ports FAILED [  0%]
distributed/cli/tests/test_dask_scheduler.py::test_dashboard_whitelist FAILED [  0%]
distributed/cli/tests/test_dask_scheduler.py::test_interface FAILED      [  0%]
distributed/cli/tests/test_dask_scheduler.py::test_pid_file PASSED       [  0%]
distributed/cli/tests/test_dask_scheduler.py::test_scheduler_port_zero 
+++++++++++++++++++++++++++++++++++ Timeout ++++++++++++++++++++++++++++++++++++

~~~~~~~~~~~~~~~~~~~~~~ Stack of IO loop (140206412252928) ~~~~~~~~~~~~~~~~~~~~~~
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/threading.py", line 890, in _bootstrap
    self._bootstrap_inner()
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/threading.py", line 932, in _bootstrap_inner
    self.run()
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/threading.py", line 870, in run
    self._target(*self._args, **self._kwargs)
  File "/home/genevieve/GitHub/distributed/distributed/utils.py", line 403, in run_loop
    loop.start()
  File "/home/genevieve/GitHub/distributed/distributed/utils_test.py", line 131, in start
    orig_start()
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 199, in start
    self.asyncio_loop.run_forever()
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/asyncio/base_events.py", line 570, in run_forever
    self._run_once()
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/asyncio/base_events.py", line 1823, in _run_once
    event_list = self._selector.select(timeout)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/selectors.py", line 468, in select
    fd_event_list = self._selector.poll(timeout, max_ev)

~~~~~~~~~~~~~~~~ Stack of TCP-Executor-9675-1 (140205666182912) ~~~~~~~~~~~~~~~~
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/threading.py", line 890, in _bootstrap
    self._bootstrap_inner()
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/threading.py", line 932, in _bootstrap_inner
    self.run()
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/threading.py", line 870, in run
    self._target(*self._args, **self._kwargs)
  File "/home/genevieve/GitHub/distributed/distributed/threadpoolexecutor.py", line 51, in _worker
    task = work_queue.get(timeout=1)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/queue.py", line 179, in get
    self.not_empty.wait(remaining)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/threading.py", line 306, in wait
    gotit = waiter.acquire(True, timeout)

~~~~~~~~~~~~~~~~ Stack of TCP-Executor-9675-0 (140206554863360) ~~~~~~~~~~~~~~~~
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/threading.py", line 890, in _bootstrap
    self._bootstrap_inner()
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/threading.py", line 932, in _bootstrap_inner
    self.run()
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/threading.py", line 870, in run
    self._target(*self._args, **self._kwargs)
  File "/home/genevieve/GitHub/distributed/distributed/threadpoolexecutor.py", line 51, in _worker
    task = work_queue.get(timeout=1)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/queue.py", line 179, in get
    self.not_empty.wait(remaining)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/threading.py", line 306, in wait
    gotit = waiter.acquire(True, timeout)

~~~~~~~~~~~~~~~~~~ Stack of Dask-Offload_0 (140206127032064) ~~~~~~~~~~~~~~~~~~~
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/threading.py", line 890, in _bootstrap
    self._bootstrap_inner()
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/threading.py", line 932, in _bootstrap_inner
    self.run()
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/threading.py", line 870, in run
    self._target(*self._args, **self._kwargs)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/concurrent/futures/thread.py", line 78, in _worker
    work_item = work_queue.get(block=True)

~~~~~~~~~~~~~~~~~~~~ Stack of MainThread (140207498544960) ~~~~~~~~~~~~~~~~~~~~~
  File "/home/genevieve/anaconda3/envs/dask-distributed/bin/pytest", line 11, in <module>
    sys.exit(console_main())
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/_pytest/config/__init__.py", line 185, in console_main
    code = main()
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/_pytest/config/__init__.py", line 162, in main
    ret: Union[ExitCode, int] = config.hook.pytest_cmdline_main(
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/hooks.py", line 286, in __call__
    return self._hookexec(self, self.get_hookimpls(), kwargs)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/manager.py", line 93, in _hookexec
    return self._inner_hookexec(hook, methods, kwargs)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/manager.py", line 84, in <lambda>
    self._inner_hookexec = lambda hook, methods, kwargs: hook.multicall(
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/callers.py", line 187, in _multicall
    res = hook_impl.function(*args)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/_pytest/main.py", line 316, in pytest_cmdline_main
    return wrap_session(config, _main)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/_pytest/main.py", line 269, in wrap_session
    session.exitstatus = doit(config, session) or 0
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/_pytest/main.py", line 323, in _main
    config.hook.pytest_runtestloop(session=session)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/hooks.py", line 286, in __call__
    return self._hookexec(self, self.get_hookimpls(), kwargs)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/manager.py", line 93, in _hookexec
    return self._inner_hookexec(hook, methods, kwargs)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/manager.py", line 84, in <lambda>
    self._inner_hookexec = lambda hook, methods, kwargs: hook.multicall(
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/callers.py", line 187, in _multicall
    res = hook_impl.function(*args)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/_pytest/main.py", line 348, in pytest_runtestloop
    item.config.hook.pytest_runtest_protocol(item=item, nextitem=nextitem)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/hooks.py", line 286, in __call__
    return self._hookexec(self, self.get_hookimpls(), kwargs)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/manager.py", line 93, in _hookexec
    return self._inner_hookexec(hook, methods, kwargs)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/manager.py", line 84, in <lambda>
    self._inner_hookexec = lambda hook, methods, kwargs: hook.multicall(
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/callers.py", line 187, in _multicall
    res = hook_impl.function(*args)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/_pytest/runner.py", line 109, in pytest_runtest_protocol
    runtestprotocol(item, nextitem=nextitem)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/_pytest/runner.py", line 126, in runtestprotocol
    reports.append(call_and_report(item, "call", log))
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/_pytest/runner.py", line 215, in call_and_report
    call = call_runtest_hook(item, when, **kwds)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/_pytest/runner.py", line 254, in call_runtest_hook
    return CallInfo.from_call(
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/_pytest/runner.py", line 311, in from_call
    result: Optional[TResult] = func()
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/_pytest/runner.py", line 255, in <lambda>
    lambda: ihook(item=item, **kwds), when=when, reraise=reraise
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/hooks.py", line 286, in __call__
    return self._hookexec(self, self.get_hookimpls(), kwargs)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/manager.py", line 93, in _hookexec
    return self._inner_hookexec(hook, methods, kwargs)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/manager.py", line 84, in <lambda>
    self._inner_hookexec = lambda hook, methods, kwargs: hook.multicall(
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/callers.py", line 187, in _multicall
    res = hook_impl.function(*args)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/_pytest/runner.py", line 162, in pytest_runtest_call
    item.runtest()
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/_pytest/python.py", line 1641, in runtest
    self.ihook.pytest_pyfunc_call(pyfuncitem=self)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/hooks.py", line 286, in __call__
    return self._hookexec(self, self.get_hookimpls(), kwargs)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/manager.py", line 93, in _hookexec
    return self._inner_hookexec(hook, methods, kwargs)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/manager.py", line 84, in <lambda>
    self._inner_hookexec = lambda hook, methods, kwargs: hook.multicall(
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/pluggy/callers.py", line 187, in _multicall
    res = hook_impl.function(*args)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/site-packages/_pytest/python.py", line 183, in pytest_pyfunc_call
    result = testfunction(**testargs)
  File "/home/genevieve/GitHub/distributed/distributed/cli/tests/test_dask_scheduler.py", line 210, in test_scheduler_port_zero
    with Client(scheduler_file=fn, loop=loop) as c:
  File "/home/genevieve/GitHub/distributed/distributed/client.py", line 764, in __init__
    self.start(timeout=timeout)
  File "/home/genevieve/GitHub/distributed/distributed/client.py", line 1010, in start
    sync(self.loop, self._start, **kwargs)
  File "/home/genevieve/GitHub/distributed/distributed/utils.py", line 323, in sync
    e.wait(10)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/threading.py", line 558, in wait
    signaled = self._cond.wait(timeout)
  File "/home/genevieve/anaconda3/envs/dask-distributed/lib/python3.8/threading.py", line 306, in wait
    gotit = waiter.acquire(True, timeout)

+++++++++++++++++++++++++++++++++++ Timeout ++++++++++++++++++++++++++++++++++++
(dask-distributed) genevieve@genevieve-G5-5500:~/GitHub/distributed$ 

[GenevieveBuckley]

Perhaps we should add a note to the distributed developer installation docs?