code: def SSHCluster(
      hosts: list[str] | None = None,
      connect_options: dict | list[dict] | None = None,
      worker_options: dict | None = None,
      scheduler_options: dict | None = None,
      worker_module: str = "deprecated",
      worker_class: str = "distributed.Nanny",
      remote_python: str | list[str] | None = None,
      **kwargs: Any,
  ) -> SpecCluster:
      """Deploy a Dask cluster using SSH
  
      The SSHCluster function deploys a Dask Scheduler and Workers for you on a
      set of machine addresses that you provide.  The first address will be used
      for the scheduler while the rest will be used for the workers (feel free to
      repeat the first hostname if you want to have the scheduler and worker
      co-habitate one machine.)
  
      You may configure the scheduler and workers by passing
      ``scheduler_options`` and ``worker_options`` dictionary keywords.  See the
      ``dask.distributed.Scheduler`` and ``dask.distributed.Worker`` classes for
      details on the available options, but the defaults should work in most
      situations.
  
      You may configure your use of SSH itself using the ``connect_options``
      keyword, which passes values to the ``asyncssh.connect`` function.  For
      more information on these see the documentation for the ``asyncssh``
      library https://asyncssh.readthedocs.io .
  
      Parameters
      ----------
      hosts
          List of hostnames or addresses on which to launch our cluster.
          The first will be used for the scheduler and the rest for workers.
      connect_options
          Keywords to pass through to :func:`asyncssh.connect`.
          This could include things such as ``port``, ``username``, ``password``
          or ``known_hosts``. See docs for :func:`asyncssh.connect` and
          :class:`asyncssh.SSHClientConnectionOptions` for full information.
          If a list it must have the same length as ``hosts``.
      worker_options
          Keywords to pass on to workers.
      scheduler_options
          Keywords to pass on to scheduler.
      worker_class
          The python class to use to create the worker(s).
      remote_python
          Path to Python on remote nodes.
  
      Examples
      --------
      Create a cluster with one worker:
  
      >>> from dask.distributed import Client, SSHCluster
      >>> cluster = SSHCluster(["localhost", "localhost"])
      >>> client = Client(cluster)
  
      Create a cluster with three workers, each with two threads
      and host the dashdoard on port 8797:
  
      >>> from dask.distributed import Client, SSHCluster
      >>> cluster = SSHCluster(
      ...     ["localhost", "localhost", "localhost", "localhost"],
      ...     connect_options={"known_hosts": None},
      ...     worker_options={"nthreads": 2},
      ...     scheduler_options={"port": 0, "dashboard_address": ":8797"}
      ... )
      >>> client = Client(cluster)
  
      Create a cluster with two workers on each host:
  
      >>> from dask.distributed import Client, SSHCluster
      >>> cluster = SSHCluster(
      ...     ["localhost", "localhost", "localhost", "localhost"],
      ...     connect_options={"known_hosts": None},
      ...     worker_options={"nthreads": 2, "n_workers": 2},
      ...     scheduler_options={"port": 0, "dashboard_address": ":8797"}
      ... )
      >>> client = Client(cluster)
  
      An example using a different worker class, in particular the
      ``CUDAWorker`` from the ``dask-cuda`` project:
  
      >>> from dask.distributed import Client, SSHCluster
      >>> cluster = SSHCluster(
      ...     ["localhost", "hostwithgpus", "anothergpuhost"],
      ...     connect_options={"known_hosts": None},
      ...     scheduler_options={"port": 0, "dashboard_address": ":8797"},
      ...     worker_class="dask_cuda.CUDAWorker")
      >>> client = Client(cluster)
  
      See Also
      --------
      dask.distributed.Scheduler
      dask.distributed.Worker
      asyncssh.connect
      """
      connect_options = connect_options or {}
      worker_options = worker_options or {}
      scheduler_options = scheduler_options or {}
  
      if worker_module != "deprecated":
          raise ValueError(
              "worker_module has been deprecated in favor of worker_class. "
              "Please specify a Python class rather than a CLI module."
          )
  
      if set(kwargs) & old_cluster_kwargs:
          from distributed.deploy.old_ssh import (
              SSHCluster as OldSSHCluster,
          )
  
          warnings.warn(
              "Note that the SSHCluster API has been replaced.  "
              "We're routing you to the older implementation.  "
              "This will be removed in the future"
          )
          kwargs.setdefault("worker_addrs", hosts)
          return OldSSHCluster(**kwargs)  # type: ignore
  
      if not hosts:
          raise ValueError(
              f"`hosts` must be a non empty list, value {repr(hosts)!r} found."
          )
      if isinstance(connect_options, list) and len(
          connect_options
      ) != len(hosts):
          raise RuntimeError(
              "When specifying a list of connect_options you must provide a "
              "dictionary for each address."
          )
  
      if isinstance(remote_python, list) and len(remote_python) != len(
          hosts
      ):
          raise RuntimeError(
              "When specifying a list of remote_python you must provide a "
              "path for each address."
          )
  
      scheduler = {
          "cls": Scheduler,
          "options": {
              "address": hosts[0],
              "connect_options": connect_options
              if isinstance(connect_options, dict)
              else connect_options[0],
              "kwargs": scheduler_options,
              "remote_python": remote_python[0]
              if isinstance(remote_python, list)
              else remote_python,
          },
      }
      workers = {
          i: {
              "cls": Worker,
              "options": {
                  "address": host,
                  "connect_options": connect_options
                  if isinstance(connect_options, dict)
                  else connect_options[i + 1],
                  "kwargs": worker_options,
                  "worker_class": worker_class,
                  "remote_python": remote_python[i + 1]
                  if isinstance(remote_python, list)
                  else remote_python,
              },
          }
          for i, host in enumerate(hosts[1:])
      }
      return SpecCluster(
          workers, scheduler, name="SSHCluster", **kwargs
      )
  
imports: from __future__ import annotations
  import copy
  import logging
  import sys
  import warnings
  import weakref
  from json import dumps
  from typing import Any
  import dask
  import dask.config
  from distributed.deploy.spec import ProcessInterface, SpecCluster
label_desc: Use image node_id 1 for calling a global function with example usage: SSHCluster(hosts, connect_options, worker_options, scheduler_options, worker_module, worker_class, remote_python) and returns: SpecCluster, OldSSHCluster