Minor tweaks to Sphinx documentation (#7041)

distributed/client.py

@@ -4158,8 +4158,8 @@ def subscribe_topic(self, topic, handler):
             single argument `event` which is a tuple `(timestamp, msg)` where
             timestamp refers to the clock on the scheduler.
 
-        Example
-        -------
+        Examples
+        --------
 
         >>> import logging
         >>> logger = logging.getLogger("myLogger")  # Log config not shown

distributed/nanny.py

@@ -89,20 +89,19 @@ class Nanny(ServerNode):
             2. Existing environment variables
             3. Dask configuration
 
-        Note
-        ----
-        Some environment variables, like ``OMP_NUM_THREADS``, must be set before
-        importing numpy to have effect. Others, like ``MALLOC_TRIM_THRESHOLD_`` (see
-        :ref:`memtrim`), must be set before starting the Linux process. Such variables
-        would be ineffective if set here or in ``distributed.nanny.environ``; they
-        must be set in ``distributed.nanny.pre-spawn-environ`` so that they are set
-        before spawning the subprocess, even if this means poisoning the
-        process running the Nanny.
-
-        For the same reason, be warned that changing
-        ``distributed.worker.multiprocessing-method`` from ``spawn`` to ``fork`` or
-        ``forkserver`` may inhibit some environment variables; if you do, you should
-        set the variables yourself in the shell before you start ``dask-worker``.
+        .. note::
+           Some environment variables, like ``OMP_NUM_THREADS``, must be set before
+           importing numpy to have effect. Others, like ``MALLOC_TRIM_THRESHOLD_`` (see
+           :ref:`memtrim`), must be set before starting the Linux process. Such
+           variables would be ineffective if set here or in
+           ``distributed.nanny.environ``; they must be set in
+           ``distributed.nanny.pre-spawn-environ`` so that they are set before spawning
+           the subprocess, even if this means poisoning the process running the Nanny.
+
+           For the same reason, be warned that changing
+           ``distributed.worker.multiprocessing-method`` from ``spawn`` to ``fork`` or
+           ``forkserver`` may inhibit some environment variables; if you do, you should
+           set the variables yourself in the shell before you start ``dask-worker``.
 
     See Also
     --------

distributed/worker_state_machine.py

@@ -363,8 +363,8 @@ def match(cls, **kwargs: Any) -> _InstructionMatch:
         :meth:`WorkerState.handle_stimulus` or in :attr:`WorkerState.stimulus_log` vs.
         an expected list of matches.
 
-        Example
-        -------
+        Examples
+        --------
 
         .. code-block:: python
 

docs/source/scheduling-policies.rst

@@ -117,7 +117,11 @@ functions in ``scheduler.py``.
 
 .. autosummary:: decide_worker
 
-.. autosummary:: Scheduler.decide_worker
+.. autosummary:: Scheduler.decide_worker_non_rootish
+
+.. autosummary:: Scheduler.decide_worker_rootish_queuing_disabled
+
+.. autosummary:: Scheduler.decide_worker_rootish_queuing_enabled
 
 .. autosummary:: Scheduler.worker_objective