[Screenipy Test] New Features Added - Test Passed (#210)

* v2.08 - New ML Model (Nifty + Gold + Crude) for Gap Prediction

---------

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: pranjal-joshi <joshi.pranjal5@gmail.com>

Author: github-actions[bot]

src/classes/Changelog.py

@@ -7,7 +7,7 @@
 
 from classes.ColorText import colorText
 
-VERSION = "2.07"
+VERSION = "2.08"
 
 changelog = colorText.BOLD + '[ChangeLog]\n' + colorText.END + colorText.BLUE + '''
 [1.00 - Beta]
@@ -242,4 +242,7 @@
 1. US S&P 500 Index added - Try Index `15 > US S&P 500`
 2. Minor improvemnets
 
+[2.08]
+1. Nifty Prediction enhanced - New AI model uses Crude and Gold data for Gap Prediction
+
 ''' + colorText.END

src/classes/Fetcher.py

@@ -159,6 +159,21 @@ def fetchLatestNiftyDaily(self, proxyServer=None):
                 progress=False,
                 timeout=10
             )
+        gold = yf.download(
+                tickers="GC=F",
+                period='5d',
+                interval='1d',
+                progress=False,
+                timeout=10
+            ).add_prefix(prefix='gold_')
+        crude = yf.download(
+                    tickers="CL=F",
+                    period='5d',
+                    interval='1d',
+                    progress=False,
+                    timeout=10
+                ).add_prefix(prefix='crude_')
+        data = pd.concat([data, gold, crude], axis=1)
         return data
 
     # Get Data for Five EMA strategy

src/classes/Screener.py

@@ -583,10 +583,8 @@ def getNiftyPrediction(self, data, proxyServer):
         with SuppressOutput(suppress_stderr=True, suppress_stdout=True):
             data = data[pkl['columns']]
             ### v2 Preprocessing
-            data['High'] = data['High'].pct_change() * 100
-            data['Low'] = data['Low'].pct_change() * 100
-            data['Open'] = data['Open'].pct_change() * 100
-            data['Close'] = data['Close'].pct_change() * 100
+            for col in pkl['columns']:
+                data[col] = data[col].pct_change() * 100
             data = data.iloc[-1] 
             ###
             data = pkl['scaler'].transform([data])

src/classes/Utility.py

@@ -309,10 +309,10 @@ def getProgressbarStyle():
         return bar, spinner
 
     def getNiftyModel(proxyServer=None):
-        files = ['nifty_model_v2.h5', 'nifty_model_v2.pkl']
+        files = ['nifty_model_v3.h5', 'nifty_model_v3.pkl']
         urls = [
-            "https://raw.github.com/pranjal-joshi/Screeni-py/new-features/src/ml/nifty_model_v2.h5",
-            "https://raw.github.com/pranjal-joshi/Screeni-py/new-features/src/ml/nifty_model_v2.pkl"
+            f"https://raw.github.com/pranjal-joshi/Screeni-py/new-features/src/ml/{files[0]}",
+            f"https://raw.github.com/pranjal-joshi/Screeni-py/new-features/src/ml/{files[1]}"
         ]
         if os.path.isfile(files[0]) and os.path.isfile(files[1]):
             file_age = (time.time() - os.path.getmtime(files[0]))/604800
@@ -332,7 +332,7 @@ def getNiftyModel(proxyServer=None):
                     resp = requests.get(file_url, stream=True)
                 if resp.status_code == 200:
                     print(colorText.BOLD + colorText.GREEN +
-                            "[+] Downloading AI model (v2) for Nifty predictions, Please Wait.." + colorText.END)
+                            "[+] Downloading AI model (v3) for Nifty predictions, Please Wait.." + colorText.END)
                     try:
                         chunksize = 1024*1024*1
                         filesize = int(int(resp.headers.get('content-length'))/chunksize)