diff --git a/api_client/python/timesketch_api_client/search.py b/api_client/python/timesketch_api_client/search.py
index 2663b60d37..027ffbe870 100644
--- a/api_client/python/timesketch_api_client/search.py
+++ b/api_client/python/timesketch_api_client/search.py
@@ -493,12 +493,19 @@ def _execute_query(self, file_name="", count=False):
         """Execute a search request and store the results.
 
         Args:
-            file_name (str): optional file path to a filename that
+            file_name (str): Optional file path to a filename that
                 all the results will be saved to. If not provided
                 the results will be stored in the search object.
-            count (bool): optional boolean that determines whether
+            count (bool): Optional boolean that determines whether
                 we want to execute the query or only count the
-                number of events that the query would produce.
+                number of events that the query would produce. If
+                set to True, the results will be stored in the
+                search object, and the number of events will be
+                returned.
+
+        Returns:
+            A dict with the search results or the total number of events
+            (if count=True) or None if saved to file.
         """
         query_filter = self.query_filter
         if not isinstance(query_filter, dict):
@@ -531,14 +538,14 @@ def _execute_query(self, file_name="", count=False):
         if file_name:
             with open(file_name, "wb") as fw:
                 fw.write(response.content)
-            return
+            return None
 
         response_json = error.get_response_json(response, logger)
 
         if count:
             meta = response_json.get("meta", {})
             self._total_elastic_size = meta.get("total_count", 0)
-            return
+            return meta.get("total_count", 0)
 
         scroll_id = response_json.get("meta", {}).get("scroll_id", "")
         form_data["scroll_id"] = scroll_id
@@ -579,6 +586,7 @@ def _execute_query(self, file_name="", count=False):
             )
 
         self._raw_response = response_json
+        return response_json
 
     def add_chip(self, chip):
         """Add a chip to the ..."""
@@ -647,7 +655,7 @@ def expected_size(self):
         if self._total_elastic_size:
             return self._total_elastic_size
 
-        self._execute_query(count=True)
+        _ = self._execute_query(count=True)
         return self._total_elastic_size
 
     def from_manual(  # pylint: disable=arguments-differ
@@ -1074,8 +1082,10 @@ def scrolling_enable(self):
 
     def to_dict(self):
         """Returns a dict with the respone of the query."""
-        if not self._raw_response:
+        if self._raw_response is None:
             self._execute_query()
+            if self._raw_response is None:
+                raise ValueError("No results to return.")
 
         return self._raw_response
 
@@ -1098,8 +1108,10 @@ def to_file(self, file_name):
 
     def to_pandas(self):
         """Returns a pandas DataFrame with the response of the query."""
-        if not self._raw_response:
-            self._execute_query()
+        if self._raw_response is None:
+            self._raw_response = self._execute_query()
+            if self._raw_response is None:
+                raise ValueError("No results to return.")
 
         return_list = []
         timelines = {t.id: t.name for t in self._sketch.list_timelines()}
diff --git a/api_client/python/timesketch_api_client/story.py b/api_client/python/timesketch_api_client/story.py
index 92dc0e55cf..6bf49faf3f 100644
--- a/api_client/python/timesketch_api_client/story.py
+++ b/api_client/python/timesketch_api_client/story.py
@@ -729,6 +729,9 @@ def to_string(self):
                 string_list.append(block.text)
             elif block.TYPE == "view":
                 search_obj = block.view
+                if search_obj is None:
+                    logging.warning("Block has no view. Skipping")
+                    continue
                 data_frame = search_obj.to_pandas()
                 string_list.append(data_frame.to_string(index=False))
             elif block.TYPE == "aggregation":