Upload api_logic.py

src/api_logic.py

@@ -70,17 +70,42 @@ def fetch_keyword_ideas(request: KeywordRequestModel):
                         "monthly_searches": mv.monthly_searches
                     })
 
+
+            # According To "Rule Book For GKP With Code" Transform Some Values
+            raw_cpc = (((metrics.low_top_of_page_bid_micros) + (metrics.high_top_of_page_bid_micros)) / 2) / 1000000
+            log_cpc = np.log(raw_cpc + 1)
+
+
             result_items.append({
                 "keyword": idea.text,
                 "avg_monthly_searches": metrics.avg_monthly_searches,
                 "competition": metrics.competition.name,
                 "competition_index": metrics.competition_index,
-                "low_top_of_page_bid_micros": metrics.low_top_of_page_bid_micros,
-                "high_top_of_page_bid_micros": metrics.high_top_of_page_bid_micros,
-                "average_cpc_micros": metrics.average_cpc_micros,
-                "monthly_search_volumes": monthly_volumes
+                "low_top_of_page_bid_micros": metrics.low_top_of_page_bid_micros / 1000000,
+                "high_top_of_page_bid_micros": metrics.high_top_of_page_bid_micros / 1000000,
+                # "average_cpc_micros": metrics.average_cpc_micros,
+                "monthly_search_volumes": monthly_volumes,
+                ##Created Features
+                "log_cpc": log_cpc
+
             })
 
+        #Normalize the Log CPC Values
+        log_values = [item["log_cpc"] for item in result_items]
+        min_log = min(log_values)
+        max_log = max(log_values)
+
+        
+        def scale_0_100(x, min_val, max_val):
+            if max_val == min_val:
+                return 0
+            return ((x - min_val) / (max_val - min_val)) * 100
+
+        #Adding "log_cpc_norm_0_100" to Results_Items
+        for item in result_items:
+            item["log_cpc_norm_0_100"] = scale_0_100(item["log_cpc"], min_log, max_log)
+
+
         # --- Aggregate results ---
         aggregate = response.aggregate_metric_results
         aggregate_device = []