Update aggregator.py

aggregator.py

@@ -16,41 +16,41 @@ def get_articles_sentiment(ticker, model):
         bezinga_results = pipe(bezinga_list)
     except Exception as e:
         print(e)
-        bezinga_results = 0
+        bezinga_results = []
 
     try:
         newsapi_list = get_newsapi(ticker)
         newsapi_results = pipe(newsapi_list)
     except Exception as e:
         print(e)
-        newsapi_results = 0
+        newsapi_results = []
     try:
         newsdata_list = get_newsdata(ticker)
         newsdata_results = pipe(newsdata_list)
     except Exception as e:
         print(e)
-        newsdata_results = 0
+        newsdata_results = []
 
     try:
         finhub_list = get_finhub(ticker)
         finhub_results = pipe(finhub_list)
     except Exception as e:
         print(e)
-        finhub_results = 0
+        finhub_results = []
         
     try:
         vantage_list = get_vantage(ticker)
         vantage_results = pipe(vantage_list)
     except Exception as e:
         print(e)
-        vantage_results = 0
+        vantage_results = []
 
     try:
         marketaux_list = get_marketaux(ticker)
         marketaux_results = pipe(marketaux_list)
     except Exception as e:
         print(e)
-        marketaux_results = 0
+        marketaux_results = []
     
     
 
@@ -76,16 +76,34 @@ def get_articles_sentiment(ticker, model):
                 dict["label"] = 2
             else:
                 dict["label"] = 1
+
     
     total_articles = len(bezinga_results) + len(finhub_results) + len(marketaux_results) + len(newsapi_results) + len(newsdata_results) + len(vantage_results)
 
+    bezinga_positives = []
+    bezinga_negatives = []
+
+    finhub_positives = []
+    finhub_negatives = []
+
+    marketaux_positives = []
+    marketaux_negatives = []
+
+    newsapi_positives = []
+    newsapi_negatives = []
+
+    newsdata_positives = []
+    newsdata_negatives = []
+
+    vantage_positives = []
+    vantage_negatives = []
+    
     try:
         replace_values(bezinga_results)
 
         bezinga_label_mean = float(sum(d['label'] for d in bezinga_results)) / len(bezinga_results)
         
-        bezinga_positives = []
-        bezinga_negatives = []
+        
 
         for dict in bezinga_results:
             if dict["label"] == 2:
@@ -102,13 +120,12 @@ def get_articles_sentiment(ticker, model):
         print(e)
 
         # finhub
-    if finhub_results:
+    if len(finhub_results) > 0:
         replace_values(finhub_results)
 
         finhub_label_mean = float(sum(d['label'] for d in finhub_results)) / len(finhub_results)
         
-        finhub_positives = []
-        finhub_negatives = []
+        
 
         for dict in finhub_results:
             if dict["label"] == 2:
@@ -123,13 +140,10 @@ def get_articles_sentiment(ticker, model):
             finhub_negative_score_mean = float(sum(d['score'] for d in finhub_negatives)) / len(finhub_negatives)
 
     # marketaux
-    if marketaux_results:
+    if len(marketaux_results) > 0:
         replace_values(marketaux_results)
 
         marketaux_label_mean = float(sum(d['label'] for d in marketaux_results)) / len(marketaux_results)
-        
-        marketaux_positives = []
-        marketaux_negatives = []
 
         for dict in marketaux_results:
             if dict["label"] == 2:
@@ -144,13 +158,10 @@ def get_articles_sentiment(ticker, model):
             marketaux_negative_score_mean = float(sum(d['score'] for d in marketaux_negatives)) / len(marketaux_negatives)
     
     # newsapi
-    if newsapi_results:
+    if len(newsapi_results) > 0:
         replace_values(newsapi_results)
 
         newsapi_label_mean = float(sum(d['label'] for d in newsapi_results) + 1) / (len(newsapi_results) + 2)
-        
-        newsapi_positives = []
-        newsapi_negatives = []
 
         for dict in newsapi_results:
             if dict["label"] == 2:
@@ -166,13 +177,10 @@ def get_articles_sentiment(ticker, model):
 
     
     # newsdata
-    if newsdata_results:
+    if len(newsdata_results) > 0:
         replace_values(newsdata_results)
 
         newsdata_label_mean = float(sum(d['label'] for d in newsdata_results)) / len(newsdata_results)
-        
-        newsdata_positives = []
-        newsdata_negatives = []
 
         for dict in newsdata_results:
             if dict["label"] == 2:
@@ -187,13 +195,10 @@ def get_articles_sentiment(ticker, model):
             newsdata_negative_score_mean = float(sum(d['score'] for d in newsdata_negatives)) / len(newsdata_negatives)
 
     # vantage
-    if vantage_results:
+    if len(vantage_results) > 0:
         replace_values(vantage_results)
 
         vantage_label_mean = float(sum(d['label'] for d in vantage_results)) / len(vantage_results)
-        
-        vantage_positives = []
-        vantage_negatives = []
 
         for dict in vantage_results:
             if dict["label"] == 2:
@@ -212,52 +217,52 @@ def get_articles_sentiment(ticker, model):
 
     results_dict = {
         "bezinga": {
-            "bezinga_articles": len(bezinga_results) if bezinga_results > 0 else 0,
-            "bezinga_positives": len(bezinga_positives) if bezinga_results > 0 else 0,
-            "bezinga_negatives": len(bezinga_negatives) if bezinga_results > 0 else 0,
-            "bezinga_sentiment_mean": bezinga_label_mean if bezinga_results > 0 else 0,
-            "bezinga_positive_score_mean": bezinga_positive_score_mean if bezinga_results > 0 else 0,
-            "bezinga_negative_score_mean": bezinga_negative_score_mean if bezinga_results > 0 else 0
+            "bezinga_articles": len(bezinga_results),
+            "bezinga_positives": len(bezinga_positives),
+            "bezinga_negatives": len(bezinga_negatives),
+            "bezinga_sentiment_mean": bezinga_label_mean if len(bezinga_results) > 0 else 0,
+            "bezinga_positive_score_mean": bezinga_positive_score_mean if len(bezinga_results) > 0 else 0,
+            "bezinga_negative_score_mean": bezinga_negative_score_mean if len(bezinga_results) > 0 else 0
         },
         "finhub": {
-            "finhub_articles": len(finhub_results) if finhub_results > 0 else 0,
-            "finhub_positives": len(finhub_positives) if finhub_results > 0 else 0,
-            "finhub_negatives": len(finhub_negatives) if finhub_results > 0 else 0,
-            "finhub_sentiment_mean": finhub_label_mean if finhub_results > 0 else 0,
-            "finhub_positive_score_mean": finhub_positive_score_mean if finhub_results > 0 else 0,
-            "finhub_negative_score_mean": finhub_negative_score_mean if finhub_results > 0 else 0
+            "finhub_articles": len(finhub_results),
+            "finhub_positives": len(finhub_positives),
+            "finhub_negatives": len(finhub_negatives),
+            "finhub_sentiment_mean": finhub_label_mean if len(finhub_results) > 0 else 0,
+            "finhub_positive_score_mean": finhub_positive_score_mean if len(finhub_results) > 0 else 0,
+            "finhub_negative_score_mean": finhub_negative_score_mean if len(finhub_results) > 0 else 0
         },
         "marketaux": {
-            "marketaux_articles": len(marketaux_results) if marketaux_results > 0 else 0,
-            "marketaux_positives": len(marketaux_positives) if marketaux_results > 0 else 0,
-            "marketaux_negatives": len(marketaux_negatives) if marketaux_results > 0 else 0,
-            "marketaux_sentiment_mean": marketaux_label_mean if marketaux_results > 0 else 0,
-            "marketaux_positive_score_mean": marketaux_positive_score_mean if marketaux_results > 0 else 0,
-            "marketaux_negative_score_mean": marketaux_negative_score_mean if marketaux_results > 0 else 0
+            "marketaux_articles": len(marketaux_results),
+            "marketaux_positives": len(marketaux_positives),
+            "marketaux_negatives": len(marketaux_negatives),
+            "marketaux_sentiment_mean": marketaux_label_mean if len(marketaux_results) > 0 else 0,
+            "marketaux_positive_score_mean": marketaux_positive_score_mean if len(marketaux_results) > 0 else 0,
+            "marketaux_negative_score_mean": marketaux_negative_score_mean if len(marketaux_results) > 0 else 0
         },
         "newsapi": {
-            "newsapi_articles": len(newsapi_results) if newsapi_results > 0 else 0,
-            "newsapi_positives": len(newsapi_positives) if newsapi_results > 0 else 0,
-            "newsapi_negatives": len(newsapi_negatives) if newsapi_results > 0 else 0,
-            "newsapi_sentiment_mean": newsapi_label_mean if newsapi_results > 0 else 0,
-            "newsapi_positive_score_mean": newsapi_positive_score_mean if newsapi_results > 0 else 0,
-            "newsapi_negative_score_mean": newsapi_negative_score_mean if newsapi_results > 0 else 0
+            "newsapi_articles": len(newsapi_results),
+            "newsapi_positives": len(newsapi_positives),
+            "newsapi_negatives": len(newsapi_negatives),
+            "newsapi_sentiment_mean": newsapi_label_mean if len(newsapi_results) > 0 else 0,
+            "newsapi_positive_score_mean": newsapi_positive_score_mean if len(newsapi_results) > 0 else 0,
+            "newsapi_negative_score_mean": newsapi_negative_score_mean if len(newsapi_results) > 0 else 0
         },
         "newsdata": {
-            "newsdata_articles": len(newsdata_results) if newsdata_results > 0 else 0,
-            "newsdata_positives": len(newsdata_positives) if newsdata_results > 0 else 0,
-            "newsdata_negatives": len(newsdata_negatives) if newsdata_results > 0 else 0,
-            "newsdata_sentiment_mean": newsdata_label_mean if newsdata_results > 0 else 0,
-            "newsdata_positive_score_mean": newsdata_positive_score_mean if newsdata_results > 0 else 0,
-            "newsdata_negative_score_mean": newsdata_negative_score_mean if newsdata_results > 0 else 0
+            "newsdata_articles": len(newsdata_results),
+            "newsdata_positives": len(newsdata_positives),
+            "newsdata_negatives": len(newsdata_negatives),
+            "newsdata_sentiment_mean": newsdata_label_mean if len(newsdata_results) > 0 else 0,
+            "newsdata_positive_score_mean": newsdata_positive_score_mean if len(newsdata_results) > 0 else 0,
+            "newsdata_negative_score_mean": newsdata_negative_score_mean if len(newsdata_results) > 0 else 0
         },
         "vantage": {
-            "vantage_articles": len(vantage_results) if vantage_results > 0 else 0,
-            "vantage_positives": len(vantage_positives) if vantage_results > 0 else 0,
-            "vantage_negatives": len(vantage_negatives) if vantage_results > 0 else 0,
-            "vantage_sentiment_mean": vantage_label_mean if vantage_results > 0 else 0,
-            "vantage_positive_score_mean": vantage_positive_score_mean if vantage_results > 0 else 0,
-            "vantage_negative_score_mean": vantage_negative_score_mean if vantage_results > 0 else 0
+            "vantage_articles": len(vantage_results),
+            "vantage_positives": len(vantage_positives),
+            "vantage_negatives": len(vantage_negatives),
+            "vantage_sentiment_mean": vantage_label_mean if len(vantage_results) > 0 else 0,
+            "vantage_positive_score_mean": vantage_positive_score_mean if len(vantage_results) > 0 else 0,
+            "vantage_negative_score_mean": vantage_negative_score_mean if len(vantage_results) > 0 else 0
         },
         "total_articles": total_articles,
         "total_positives": total_positives,