Adapt `list_datasets` and `list_spaces` for future release of `huggingface_hub`

app.py

@@ -50,8 +50,8 @@ def create_user_summary(user_name):
 
 
     r = requests.get(f'https://huggingface.co/api/users/{user_name}/likes')
-    user_datasets = list_datasets(author=user_name)
-    user_spaces = list_spaces(author=user_name)
+    user_datasets = [dataset for dataset in list_datasets(author=user_name)]
+    user_spaces = [space for space in list_spaces(author=user_name)]
     
     summary["likes_user_total"] = df_user["likes"].sum()
     summary["likes_user_given"] = len(r.json())
@@ -68,8 +68,8 @@ def create_user_summary(user_name):
     summary["repos_model_top"] = df_ranks["repos"][df_ranks["repos"]["value"]>=summary["repos_model_total"]].iloc[0]["top_perc"]
     summary["repos_model_fav_type"] = Counter(df_user["model_type"].dropna()).most_common(1)[0][0]
     
-    summary["repos_datasets_total"] = len(list(iter(user_datasets)))
-    summary["repos_spaces_total"] = len(list(iter(user_spaces)))
+    summary["repos_datasets_total"] = len(user_datasets)
+    summary["repos_spaces_total"] = len(user_spaces)
     summary["repos_spaces_fav_sdk"] = Counter([getattr(info, "sdk", "n/a") for info in user_spaces]).most_common(1)[0][0]
 
     return dict_to_html(summary)