bubble up the API to QuantumComputer

docs/source/programs_and_gates.rst

@@ -364,13 +364,10 @@ filled in for, say, 200 values between :math:`0` and :math:`2\pi`. We demonstrat
     # Generate a memory map for each set of parameters we want to execute with
     memory_maps = [{"theta": [theta] for theta in np.linspace(0, 2 * np.pi, 200)}]
 
-    # Begin batch execution of the program using each set of parameters.
-    # This returns a list of references to each job, the length and order of which correspond to the memory maps we
+    # Batch execute of the program using each set of parameters.
+    # This returns a list of results for each execution, the length and order of which correspond to the memory maps we
     # pass in.
-    handles = qc.execute_with_memory_map_batch(executable, memory_maps)
-
-    # Use the handles to gather the results
-    parametric_measurements = [qc.get_result(handles) for handle in handles]
+    parametric_measurements = qc.run_with_memory_map_batch(executable, memory_maps)
 
 .. note::
 

pyquil/api/_qam.py

@@ -157,8 +157,7 @@ def execute_with_memory_map_batch(
         How these programs are batched and executed is determined by the executor. See their respective documentation
         for details.
 
-        Returns a list of ``QAMExecutionResult``, which can be used to fetch
-        results in ``QAM#get_result``.
+        Returns a list of handles that can be used to fetch results with ``QAM#get_result``.
         """
 
     @abstractmethod

pyquil/api/_quantum_computer.py

@@ -24,6 +24,7 @@
     Any,
     Tuple,
     Iterator,
+    Iterable,
     Optional,
     Set,
     Union,
@@ -141,6 +142,22 @@ def run(
         """
         return self.qam.run(executable, memory_map, **kwargs)
 
+    def run_with_memory_map_batch(
+        self, executable: QuantumExecutable, memory_maps: Iterable[MemoryMap], **kwargs: Any
+    ) -> List[QAMExecutionResult]:
+        """
+        Run a QuantumExecutable with one or more memory_maps, returning a list of results corresponding to the length
+        and order of the given MemoryMaps.
+
+        How these programs are batched and executed is determined by the executor. See their respective documentation
+        for details.
+
+        Returns a list of ``QAMExecutionResult``, which can be used to fetch
+        results in ``QAM#get_result``.
+        """
+        handles = self.qam.execute_with_memory_map_batch(executable, memory_maps, **kwargs)
+        return [self.qam.get_result(handle) for handle in handles]
+
     def calibrate(self, experiment: Experiment) -> List[ExperimentResult]:
         """
         Perform readout calibration on the various multi-qubit observables involved in the provided