Update app.py

app.py

@@ -6,6 +6,7 @@ import io
 import contextlib
 import requests
 import random
+from functools import lru_cache
 
 FORBIDDEN_NAMES ={"Judas",
                   "Judas Iscariot"
@@ -87,25 +88,34 @@ download_file(
 # --- Load datasets ---
 ssa_name_txt_files = sorted(Path(".").glob("yob*.txt"))
 
-def load_ssa_names(min_year=0, max_year=9999):
+
+
+@lru_cache(maxsize=1)
+def load_all_ssa_names():
     dfs = []
     for f in ssa_name_txt_files:
         year = int(f.stem.replace("yob", ""))
-        if min_year <= year <= max_year:
-            df = pd.read_csv(f, names=["name", "sex", "count"])
-            df["year"] = year
-            dfs.append(df)
-    if not dfs:
-        return pd.DataFrame(), pd.DataFrame()
-        
+        df = pd.read_csv(f, names=["name", "sex", "count"])
+        df["year"] = year
+        dfs.append(df)
     full_df = pd.concat(dfs, ignore_index=True)
+    return full_df
+    
+def load_ssa_names(min_year=0, max_year=9999):
+    full_df = load_all_ssa_names()
+    filtered_df = full_df[(full_df["year"] >= min_year) & (full_df["year"] <= max_year)]
+    
+    if filtered_df.empty:
+        return pd.DataFrame(), pd.DataFrame()
+
     agg_df = (
-        full_df
+        filtered_df
         .groupby(["name", "sex"], as_index=False)["count"]
         .sum()
         .sort_values("count", ascending=False)
     )
-    return full_df, agg_df
+    return filtered_df, agg_df
+