Added 2 Backend methods for netpyneunit

docs/source/basics.rst

@@ -22,7 +22,7 @@ capability, and it can be executed to simulate and output results.
 Backend
 
 After being registered by ``register_backends`` function, a ``Backend`` instance
-can be executed by a Ruunable Model at the back end. It usually does some background
+can be executed by a Runnable Model at the back end. It usually does some background
 computing for the runnable model.
 
 

sciunit/models/backends.py

@@ -157,16 +157,42 @@ def backend_run(self) -> Any:
         if self.use_memory_cache or self.use_disk_cache:
             key = self.model.hash()
         if self.use_memory_cache and self.get_memory_cache(key):
-            return self._results
+            return self.cache_to_results(self._results)
         if self.use_disk_cache and self.get_disk_cache(key):
-            return self._results
-        results = self._backend_run()
+            return self.cache_to_results(self._results)
+        results = self.results_to_cache(self._backend_run())
         if self.use_memory_cache:
             self.set_memory_cache(results, key)
         if self.use_disk_cache:
             self.set_disk_cache(results, key)
         return results
 
+    def cache_to_results(self, cache: Any) -> Any:
+        """A method you should override if you have to make some adjustments
+        to the simulation results after they've been restored from the cache.
+
+        Args:
+            cache (Any): An object returned from .get_memory_cache() or .get_disk_cache().
+
+        Returns:
+            Any (optional): Either an object with the results of the simulation,
+            or None (e.g. if cache_to_results() simply injects the results into some global object).
+        """
+        return cache
+
+    def results_to_cache(self, results: Any) -> Any:
+        """A method you should override if you have to make some adjustments
+        to the way your simulation results are stored in cache.
+
+        Args:
+            results (Any): An object returned from your ._backend_run().
+
+        Returns:
+            Any: The results in the format that's good for storing in cache
+            (usually a simple dictionary or an array).
+        """
+        return results
+
     def _backend_run(self) -> Any:
         """Run the model via the backend."""
         raise NotImplementedError("Each backend must implement '_backend_run'")