Create app.py

app.py

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+import yfinance as yf
+import plotly.graph_objects as go
+from plotly.subplots import make_subplots
+import pandas as pd
+import gradio as gr
+import os
+
+def fetch_data(ticker, period):
+    data = yf.download(ticker, period=period)
+    return data
+
+def compute_rsi(data, window=14):
+    delta = data['Close'].diff()
+    gain = (delta.where(delta > 0, 0)).rolling(window=window).mean()
+    loss = (-delta.where(delta < 0, 0)).rolling(window=window).mean()
+
+    rs = gain / loss
+    rsi = 100 - (100 / (1 + rs))
+    return rsi
+
+def compute_macd(data, slow=26, fast=12, signal=9):
+    exp1 = data['Close'].ewm(span=fast, adjust=False).mean()
+    exp2 = data['Close'].ewm(span=slow, adjust=False).mean()
+    macd = exp1 - exp2
+    signal_line = macd.ewm(span=signal, adjust=False).mean()
+    histogram = macd - signal_line
+    return macd, signal_line, histogram
+
+def buy_sell_signals(data, rsi, macd, signal_line):
+    buy_signals = []
+    sell_signals = []
+    for i in range(2, len(data)):
+        # RSI Buy Signal (RSI < 30)
+        if rsi[i-1] < 30 and rsi[i] >= 30:
+            buy_signals.append(data['Close'][i])
+            sell_signals.append(float('nan'))
+        # RSI Sell Signal (RSI > 70)
+        elif rsi[i-1] > 70 and rsi[i] <= 70:
+            sell_signals.append(data['Close'][i])
+            buy_signals.append(float('nan'))
+        # MACD Buy Signal (MACD crosses above Signal)
+        elif macd[i-1] < signal_line[i-1] and macd[i] >= signal_line[i]:
+            buy_signals.append(data['Close'][i])
+            sell_signals.append(float('nan'))
+        # MACD Sell Signal (MACD crosses below Signal)
+        elif macd[i-1] > signal_line[i-1] and macd[i] <= signal_line[i]:
+            sell_signals.append(data['Close'][i])
+            buy_signals.append(float('nan'))
+        else:
+            buy_signals.append(float('nan'))
+            sell_signals.append(float('nan'))
+    return buy_signals, sell_signals
+
+
+def plot_data(data, buy_signals, sell_signals, filename="plot.png"):
+    fig = make_subplots(rows=2, cols=1)
+    fig.add_trace(go.Candlestick(x=data.index, open=data['Open'], high=data['High'], low=data['Low'], close=data['Close'], name='Candlesticks'), row=1, col=1)
+    fig.add_trace(go.Scatter(x=data.index, y=buy_signals, mode='markers', marker_symbol='triangle-up', marker_color='green', name='Buy Signal'), row=1, col=1)
+    fig.add_trace(go.Scatter(x=data.index, y=sell_signals, mode='markers', marker_symbol='triangle-down', marker_color='red', name='Sell Signal'), row=1, col=1)
+    fig.update_layout(title='Candlestick Chart with Buy and Sell Signals', xaxis_rangeslider_visible=False)
+    fig.write_image(filename)
+    return filename
+
+def main_interface(ticker, period):
+    data = fetch_data(ticker, period)
+    rsi = compute_rsi(data)
+    macd, signal_line, _ = compute_macd(data)
+    buy_signals, sell_signals = buy_sell_signals(data, rsi, macd, signal_line)
+    plot_filename = plot_data(data, buy_signals, sell_signals)
+    return plot_filename
+
+iface = gr.Interface(fn=main_interface,
+                     inputs=[gr.Textbox(label="Asset Ticker"), gr.Textbox(label="Period: (e.g., 1y, 2y, 5y)")],
+                     outputs=gr.Image(type="file"),
+                     title="Stock Analysis Tool",
+                     description="Enter a stock ticker and period to analyze buy/sell signals based on RSI and MACD.")
+
+iface.launch()