Update app.py

Changed logic, added stochastic checker, split outputs for bullish and bearish lists for easier processing

app.py

@@ -1,31 +1,13 @@
 import gradio as gr
-from gradio.inputs import File as InputFile
+from gradio.inputs import File as InputFile, Number as InputNumber
 from gradio.outputs import File as OutputFile
-from yahoo_fin import stock_info as si
 import yfinance as yf
 import pandas as pd
 import pandas_ta as ta
 import csv
+import os
 
-def detect_head_and_shoulders(hist):
-    local_max = hist['Close'][-60:][((hist['Close'][-60:].shift(1) < hist['Close'][-60:]) & (hist['Close'][-60:].shift(-1) < hist['Close'][-60:]))]
-    if len(local_max) < 3:
-        return False
-    peaks = local_max[-3:]
-    if peaks[0] < peaks[1] and peaks[2] < peaks[1] and abs(peaks[0] - peaks[2]) < peaks[1]*0.05:
-        return True
-    return False
-
-def detect_inverted_head_and_shoulders(hist):
-    local_min = hist['Close'][-60:][((hist['Close'][-60:].shift(1) > hist['Close'][-60:]) & (hist['Close'][-60:].shift(-1) > hist['Close'][-60:]))]
-    if len(local_min) < 3:
-        return False
-    valleys = local_min[-3:]
-    if valleys[0] > valleys[1] and valleys[2] > valleys[1] and abs(valleys[0] - valleys[2]) < valleys[1]*0.05:
-        return True
-    return False
-
-def process_csv(csv_file):
+def process_csv(csv_file, bullish_stoch_value, bearish_stoch_value):
     all_tickers = []
     with open(csv_file.name, 'r') as file:
         reader = csv.reader(file)
@@ -34,8 +16,10 @@ def process_csv(csv_file):
             all_tickers.append(row[0])  # Append the value in the first column
 
     ttl_tickers = len(all_tickers)
-    filtered_tickers = []
+    bullish_tickers = []
+    bearish_tickers = []
     for ticker in all_tickers:
+        print(f"Processing {ticker} ({all_tickers.index(ticker)+1}/{ttl_tickers})")
         try:
             data = yf.Ticker(ticker)
             hist = data.history(period="1y", actions=False)
@@ -45,31 +29,48 @@ def process_csv(csv_file):
                 hist.ta.ema(close='Close', length=100, append=True)
                 hist.ta.sma(close='Close', length=150, append=True)
                 stoch = hist.ta.stoch(high='High', low='Low', close='Close')
-                if all(hist['EMA_20'][-10:] > hist['EMA_50'][-10:]) and all(hist['EMA_50'][-10:] > hist['EMA_100'][-10:]) and all(hist['EMA_100'][-10:] > hist['SMA_150'][-10:]) and stoch['STOCHk_14_3_3'][-1] < 30:
-                    filtered_tickers.append([ticker, hist['Close'][-1], hist['Volume'][-1], 'Bullish', 'Head and Shoulders' if detect_head_and_shoulders(hist) else '', 'Inverted Head and Shoulders' if detect_inverted_head_and_shoulders(hist) else ''])
-                elif all(hist['EMA_20'][-10:] < hist['EMA_50'][-10:]) and all(hist['EMA_50'][-10:] < hist['EMA_100'][-10:]) and all(hist['EMA_100'][-10:] < hist['SMA_150'][-10:]) and stoch['STOCHk_14_3_3'][-1] > 70:
-                    filtered_tickers.append([ticker, hist['Close'][-1], hist['Volume'][-1], 'Bearish', 'Head and Shoulders' if detect_head_and_shoulders(hist) else '', 'Inverted Head and Shoulders' if detect_inverted_head_and_shoulders(hist) else ''])
+                if all(hist['EMA_20'][-10:] > hist['EMA_50'][-10:]) and all(hist['EMA_50'][-10:] > hist['EMA_100'][-10:]) and all(hist['EMA_100'][-10:] > hist['SMA_150'][-10:]) and all(stoch['STOCHk_14_3_3'][-3:] < bullish_stoch_value):
+                    bullish_tickers.append([ticker, hist['Close'][-1], hist['Volume'][-1], 'Bullish'])
+                elif all(hist['EMA_20'][-10:] < hist['EMA_50'][-10:]) and all(hist['EMA_50'][-10:] < hist['EMA_100'][-10:]) and all(hist['EMA_100'][-10:] < hist['SMA_150'][-10:]) and all(stoch['STOCHk_14_3_3'][-3:] > bearish_stoch_value):
+                    bearish_tickers.append([ticker, hist['Close'][-1], hist['Volume'][-1], 'Bearish'])
         except Exception as e:
             print(f"An error occurred with ticker {ticker}: {e}")
 
-    df = pd.DataFrame(filtered_tickers, columns=['Ticker', 'Close', 'Volume', 'Trend', 'Head and Shoulders', 'Inverted Head and Shoulders'])
-    output_xlsx = 'ema_stacks_list.xlsx'
-    df.to_excel(output_xlsx, index=False)
-    output_txt = 'pyScreener.txt'
-    with open(output_txt, 'w') as f:
-        for ticker in df['Ticker']:
+    df_bullish = pd.DataFrame(bullish_tickers, columns=['Ticker', 'Close', 'Volume', 'Trend'])
+    df_bearish = pd.DataFrame(bearish_tickers, columns=['Ticker', 'Close', 'Volume', 'Trend'])
+
+    base_filename = os.path.splitext(os.path.basename(csv_file.name))[0]
+    output_bullish_xlsx = f'{base_filename}-bullish.xlsx'
+    output_bearish_xlsx = f'{base_filename}-bearish.xlsx'
+    df_bullish.to_excel(output_bullish_xlsx, index=False)
+    df_bearish.to_excel(output_bearish_xlsx, index=False)
+
+    output_bullish_txt = f'{base_filename}-bullish.txt'
+    output_bearish_txt = f'{base_filename}-bearish.txt'
+    with open(output_bullish_txt, 'w') as f:
+        for ticker in df_bullish['Ticker']:
+            f.write(f"{ticker}\n")
+    with open(output_bearish_txt, 'w') as f:
+        for ticker in df_bearish['Ticker']:
             f.write(f"{ticker}\n")
-    return output_xlsx, output_txt
+
+    return output_bullish_xlsx, output_bearish_xlsx, output_bullish_txt, output_bearish_txt
 
 iface = gr.Interface(
     fn=process_csv, 
-    inputs=InputFile(label="Upload CSV"), 
+    inputs=[
+        InputFile(label="Upload CSV"), 
+        InputNumber(label="Bullish Stochastic Value", default=30),
+        InputNumber(label="Bearish Stochastic Value", default=70)
+    ], 
     outputs=[
-        OutputFile(label="Download XLSX"),
-        OutputFile(label="Download TXT")
+        OutputFile(label="Download Bullish XLSX"),
+        OutputFile(label="Download Bearish XLSX"),
+        OutputFile(label="Download Bullish TXT"),
+        OutputFile(label="Download Bearish TXT")
     ],
-    title="Stock Shortlist",
-    description="Upload a CSV file with columns: Ticker	| Description | Industry | Market Capitalization | Sector from TradingView and get shortlisted, stacked EMA trends in return."
+    title="Stock Analysis",
+    description="Upload a CSV file and get XLSX and TXT files in return."
 )
 
-iface.launch()
+iface.launch()