Create app.py

app.py

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+import gradio as gr
+import random
+import pandas as pd
+import plotly.graph_objects as go
+
+# --- SIMULATION STATE ---
+class MarketSimulation:
+    def __init__(self):
+        self.reset()
+        
+    def reset(self):
+        self.balance = 10000.0
+        self.shares = 0
+        self.avg_buy_price = 0.0
+        self.stock_price = 100.0
+        self.price_history = [100.0]
+        self.market_modes = ["Bull 📈", "Bear 📉", "Sideways ➡️"]
+        self.current_mode = "Sideways ➡️"
+        self.tick_counter = 0
+
+    def tick(self):
+        self.tick_counter += 1
+        
+        # V2: Shift market regimes every 15 seconds
+        if self.tick_counter % 15 == 0:
+            self.current_mode = random.choice(self.market_modes)
+        
+        # Base volatility (percentage-based)
+        base_move = random.uniform(-0.03, 0.03) # ±3%
+        
+        # Apply regime bias
+        if self.current_mode == "Bull 📈":
+            base_move += random.uniform(0.005, 0.02)  # Upward bias
+        elif self.current_mode == "Bear 📉":
+            base_move -= random.uniform(0.005, 0.02)  # Downward bias
+            
+        # Occasional "Black Swan" shock move (2% chance)
+        if random.random() < 0.02:
+            base_move += random.choice([-0.08, 0.08]) # Sudden ±8% spike
+            
+        # Calculate new price
+        self.stock_price = max(1.0, round(self.stock_price * (1 + base_move), 2))
+        self.price_history.append(self.stock_price)
+        
+        # Keep history manageable
+        if len(self.price_history) > 40:
+            self.price_history.pop(0)
+            
+        return self.get_status(), self.update_chart()
+
+    def buy_stock(self):
+        if self.balance >= self.stock_price:
+            # Buy max possible shares for simplicity, or just 10 shares
+            shares_to_buy = min(10, int(self.balance // self.stock_price))
+            if shares_to_buy > 0:
+                total_cost = shares_to_buy * self.stock_price
+                
+                # Recalculate average buy price
+                total_shares = self.shares + shares_to_buy
+                self.avg_buy_price = ((self.shares * self.avg_buy_price) + total_cost) / total_shares
+                
+                self.shares += shares_to_buy
+                self.balance -= total_cost
+        return self.get_status(), self.update_chart()
+
+    def sell_stock(self):
+        if self.shares > 0:
+            shares_to_sell = min(10, self.shares)
+            total_revenue = shares_to_sell * self.stock_price
+            self.shares -= shares_to_sell
+            self.balance += total_revenue
+            if self.shares == 0:
+                self.avg_buy_price = 0.0
+        return self.get_status(), self.update_chart()
+
+    def get_status(self):
+        # Calculate Profit/Loss
+        current_value = self.shares * self.stock_price
+        cost_basis = self.shares * self.avg_buy_price
+        pnl = current_value - cost_basis
+        pnl_string = f"+${pnl:,.2f}" if pnl >= 0 else f"-${abs(pnl):,.2f}"
+        
+        portfolio_value = self.balance + current_value
+        
+        return (
+            f"${self.balance:,.2f}",
+            f"${self.stock_price:,.2f}",
+            f"{self.shares}",
+            f"${self.avg_buy_price:,.2f}",
+            pnl_string,
+            f"${portfolio_value:,.2f}",
+            f"Current Regime: {self.current_mode}"
+        )
+
+    def update_chart(self):
+        fig = go.Figure()
+        fig.add_trace(go.Scatter(
+            y=self.price_history, 
+            mode='lines+markers',
+            line=dict(color='#2196F3', width=3),
+            marker=dict(size=6),
+            name='Price'
+        ))
+        fig.update_layout(
+            title="Live Stock Price (Updates Every Second)",
+            xaxis_title="Time (Ticks)",
+            yaxis_title="Price ($)",
+            template="plotly_dark",
+            margin=dict(l=20, r=20, t=40, b=20),
+            height=350
+        )
+        return fig
+
+# --- GRADIO INTERFACE ---
+sim = MarketSimulation()
+
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 📈 PaperTrader Sim V2")
+    gr.Markdown("A pure-Python live market sandbox. Watch out for regime shifts and black swan shocks!")
+    
+    with gr.Row():
+        with gr.Column(scale=2):
+            chart = gr.Plot(value=sim.update_chart())
+            regime_display = gr.Markdown("Current Regime: Sideways ➡️")
+            
+        with gr.Column(scale=1):
+            gr.Markdown("### 💰 Account & Portfolio")
+            total_net_worth = gr.Textbox(label="Total Net Worth", value="$10,000.00", interactive=False)
+            balance_box = gr.Textbox(label="Cash Balance", value="$10,000.00", interactive=False)
+            shares_box = gr.Textbox(label="Shares Owned", value="0", interactive=False)
+            avg_price_box = gr.Textbox(label="Avg Buy Price", value="$0.00", interactive=False)
+            pnl_box = gr.Textbox(label="Profit / Loss", value="$0.00", interactive=False)
+
+    with gr.Row():
+        btn_buy = gr.Button("🛒 BUY 10 SHARES", variant="primary")
+        btn_sell = gr.Button("💵 SELL 10 SHARES", variant="secondary")
+        btn_reset = gr.Button("🔄 Reset Simulation")
+
+    # Connect UI Components
+    status_outputs = [balance_box, gr.Textbox(visible=False), shares_box, avg_price_box, pnl_box, total_net_worth, regime_display]
+    
+    btn_buy.click(sim.buy_stock, outputs=[status_outputs[0], status_outputs[2], status_outputs[3], status_outputs[4], status_outputs[5], status_outputs[6], chart])
+    btn_sell.click(sim.sell_stock, outputs=[status_outputs[0], status_outputs[2], status_outputs[3], status_outputs[4], status_outputs[5], status_outputs[6], chart])
+    
+    def reset_ui():
+        sim.reset()
+        return sim.get_status() + (sim.update_chart(),)
+        
+    btn_reset.click(reset_ui, outputs=[balance_box, gr.Textbox(visible=False), shares_box, avg_price_box, pnl_box, total_net_worth, regime_display, chart])
+
+    # The magic engine: Trigger a tick every 1.0 second automatically
+    timer = gr.Timer(1.0)
+    timer.tick(sim.tick, outputs=[balance_box, gr.Textbox(visible=False), shares_box, avg_price_box, pnl_box, total_net_worth, regime_display, chart])
+
+demo.launch()