<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def get_solver(self, name=None, refresh=False, **filters):
 """Load the configuration for a single solver. Makes a blocking web call to `{endpoint}/solvers/remote/{solver_name}/`, where `{endpoint}` is a URL configured for the client, and returns a :class:`.Solver` instance that can be used to submit sampling problems to the D-Wave API and retrieve results. Args: name (str):
 ID of the requested solver. ``None`` returns the default solver. If default solver is not configured, ``None`` returns the first available solver in ``Client``'s class (QPU/software/base). **filters (keyword arguments, optional):
 Dictionary of filters over features this solver has to have. For a list of feature names and values, see: :meth:`~dwave.cloud.client.Client.get_solvers`. order_by (callable/str, default='id'):
 Solver sorting key function (or :class:`Solver` attribute name). By default, solvers are sorted by ID/name. refresh (bool):
 Return solver from cache (if cached with ``get_solvers()``), unless set to ``True``. Returns: :class:`.Solver` Examples: This example creates two solvers for a client instantiated from a local system's auto-detected default configuration file, which configures a connection to a D-Wave resource that provides two solvers. The first uses the default solver, the second explicitly selects another solver. [Solver(id='2000Q_ONLINE_SOLVER1'), Solver(id='2000Q_ONLINE_SOLVER2')] '2000Q_ONLINE_SOLVER1' '2000Q_ONLINE_SOLVER2' """

        _LOGGER.debug("Requested a solver that best matches feature filters=%r", filters)

        # backward compatibility: name as the first feature
        if name is not None:
            filters.setdefault('name', name)

        # in absence of other filters, config/env solver filters/name are used
        if not filters and self.default_solver:
            filters = self.default_solver

        # get the first solver that satisfies all filters
        try:
            _LOGGER.debug("Fetching solvers according to filters=%r", filters)
            return self.get_solvers(refresh=refresh, **filters)[0]
        except IndexError:
            raise SolverNotFoundError("Solver with the requested features not available")