skip when empty objects (#83)

Co-authored-by: Abdellatif <[email protected]>

Author: Missoumi

django_opensearch_dsl/documents.py

@@ -113,11 +113,15 @@ def get_indexing_queryset(
         if verbose:
             stdout.write(f"{action} {model}: 0% ({self._eta(start, done, count)})\r")
 
+        if count == 0:
+            stdout.write(f"No {model} objects to {action.lower()}.\n")
+            return
+
         if batch_type == "pk_filters":
             pks = qs.aggregate(min=Min("pk"), max=Max("pk"))
             total_batches = (pks["max"] - pks["min"]) // chunk_size
             for batch_number, offset in enumerate(range(pks["min"], pks["max"] + 1, chunk_size), start=1):
-                batch_qs = list(copy.deepcopy(qs.filter(pk__gte=offset, pk__lt=offset + chunk_size)))
+                batch_qs = list(qs.filter(pk__gte=offset, pk__lt=offset + chunk_size))
                 stdout.write(f"Processing batch {batch_number}/{total_batches}: \n")
                 for obj in batch_qs:
                     done += 1
@@ -127,11 +131,11 @@ def get_indexing_queryset(
                         )
                     yield obj
                 if len(batch_qs) > 0:
-                    stdout.write(f"Max primary key in the current batch: {batch_qs[-1].pk}\n")
+                    stdout.write(f"Max primary key in the current {model} batch: {batch_qs[-1].pk}\n")
         else:
             total_batches = (count + chunk_size - 1) // chunk_size
             for batch_number, offset in enumerate(range(0, count, chunk_size), start=1):
-                batch_qs = list(copy.deepcopy(qs[offset : offset + chunk_size].all()))
+                batch_qs = list(qs[offset : offset + chunk_size].all())
                 stdout.write(f"Processing batch {batch_number}/{total_batches}: \n")
                 for obj in batch_qs:
                     done += 1
@@ -141,7 +145,7 @@ def get_indexing_queryset(
                         )
                     yield obj
                 if len(batch_qs) > 0:
-                    stdout.write(f"Max primary key in the current batch: {batch_qs[-1].pk}\n")
+                    stdout.write(f"Max primary key in the current {model} batch: {batch_qs[-1].pk}\n")
 
     def init_prepare(self):
         """Initialise the data model preparers once here.