Speed requests improvement on tide_request()

tide/utils.py

@@ -6,6 +6,7 @@
 from bigtree import dict_to_tree, levelordergroup_iter
 from bigtree.node import node
 from typing import TypeVar
+from functools import lru_cache
 
 T = TypeVar("T", bound=node.Node)
 
@@ -33,6 +34,34 @@
     2: {"name": 1},
 }
 
+@lru_cache(maxsize=32)
+def _cached_enriched_columns(columns_tuple: tuple[str, ...]):
+    max_level = get_tags_max_level(columns_tuple)
+
+    enriched_map = {
+        col_name_tag_enrichment(col, max_level): col for col in columns_tuple
+    }
+
+    split_tags = {
+        enriched: enriched.split("__") for enriched in enriched_map
+    }
+
+    return enriched_map, split_tags
+
+@lru_cache(maxsize=32)
+def _build_tag_index(columns_tuple: tuple[str, ...]):
+    max_level = get_tags_max_level(columns_tuple)
+
+    tag_index = {}
+    order = {col: i for i, col in enumerate(columns_tuple)}
+
+    for col in columns_tuple:
+        enriched = col_name_tag_enrichment(col, max_level)
+
+        for tag in enriched.split("__"):
+            tag_index.setdefault(tag, set()).add(col)
+
+    return tag_index, order
 
 def get_tree_depth_from_level(tree_max_depth: int, level: int | str):
     level = LEVEL_NAME_MAP[level] if isinstance(level, int) else level
@@ -213,12 +242,8 @@ def tide_request(
             f"request must be str, list[str], pd.Index or None, got {type(request)}"
         )
 
-    max_level = get_tags_max_level(data_columns)
-
-    # Enrich columns once
-    enriched_map = {
-        col_name_tag_enrichment(col, max_level): col for col in data_columns
-    }
+    columns_tuple = tuple(data_columns)
+    tag_index, order = _build_tag_index(columns_tuple)
 
     selected = []
 
@@ -232,12 +257,17 @@ def tide_request(
                     "Use up to 4 tags separated by '__'."
                 )
 
-            for enriched_name, original in enriched_map.items():
-                tags = enriched_name.split("__")
+            candidate_sets = []
+
+            for tag in group_tags:
+                if tag not in tag_index:
+                    candidate_sets = []
+                    break
+                candidate_sets.append(tag_index[tag])
 
-                # Exact per-tag match
-                if all(tag in tags for tag in group_tags):
-                    selected.append(original)
+            if candidate_sets:
+                matches = set.intersection(*candidate_sets)
+                selected.extend(sorted(matches, key=lambda c: order[c]))
 
     return list(dict.fromkeys(selected))