Introduce new document_retagger option

docs/administration.md

@@ -351,7 +351,7 @@ currently-imported docs. This problem is common enough that there are
 tools for it.
 
 ```
-document_retagger [-h] [-c] [-T] [-t] [-i] [--use-first] [-f]
+document_retagger [-h] [-c] [-T] [-t] [-i] [--id-range] [--use-first] [-f]
 
 optional arguments:
 -c, --correspondent
@@ -359,6 +359,7 @@ optional arguments:
 -t, --document_type
 -s, --storage_path
 -i, --inbox-only
+--id-range
 --use-first
 -f, --overwrite
 ```
@@ -375,6 +376,11 @@ Specify `-i` to have the document retagger work on documents tagged with
 inbox tags only. This is useful when you don't want to mess with your
 already processed documents.
 
+Specify `--id-range 1 100` to have the document retagger work only on a
+specific range of document id´s. This can be useful if you have a lot of
+documents and want to test the matching rules only on a subset of
+documents.
+
 When multiple document types or correspondents match a single document,
 the retagger won't assign these to the document. Specify `--use-first`
 to override this behavior and just use the first correspondent or type

src/documents/management/commands/document_retagger.py

@@ -63,6 +63,12 @@ class Command(BaseCommand):
             "--base-url",
             help="The base URL to use to build the link to the documents.",
         )
+        parser.add_argument(
+            "--id-range",
+            help="A range of document id's on which the retagging should be applied.",
+            nargs=2,
+            type=int,
+        )
 
     def handle(self, *args, **options):
         # Detect if we support color
@@ -72,6 +78,12 @@ class Command(BaseCommand):
             queryset = Document.objects.filter(tags__is_inbox_tag=True)
         else:
             queryset = Document.objects.all()
+
+        if options["id_range"]:
+            queryset = queryset.filter(
+                id__range=(options["id_range"][0], options["id_range"][1]),
+            )
+
         documents = queryset.distinct()
 
         classifier = load_classifier()