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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 | |
| # Step 7: Set Up Gradio Interface with corrected type parameter | |
| 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="filepath"), # Corrected type parameter | |
| title="Stock Analysis Tool", | |
| description="Enter a stock ticker and period to analyze buy/sell signals based on RSI and MACD.") | |
| iface.launch() |