Enhance CLI output with ASCII dashboard and fix quiet mode

.Jules/palette.md

@@ -1,3 +1,3 @@
-## 2024-05-23 - CLI UX Enhancement
-**Learning:** Even in CLI apps, visual distinction (colors, emojis) significantly reduces cognitive load when scanning logs.
-**Action:** Use ANSI colors and consistent emojis for key events (success/failure) in future CLI tools.
+## 2024-05-22 - [CLI Dashboard Pattern]
+**Learning:** Simple CLI outputs can be significantly improved by using ASCII box-drawing characters and padded alignment to create a "dashboard" feel. Users perceive this as more polished and professional than raw text streams. Also, ensure `--quiet` flags silence *all* intermediate output to respect user intent.
+**Action:** Use Python f-string alignment (`<`, `>`, `^`) and box-drawing characters for final summary reports in CLI tools.

bitcoin.py

@@ -0,0 +1,22 @@
+import requests
+
+
+def calculate_value(amount, price):
+    """
+    Calculates the value of the Bitcoin amount at the given price.
+    """
+    return float(amount * price)
+
+
+def get_bitcoin_price():
+    """
+    Fetches the current Bitcoin price from CoinDesk API.
+    """
+    url = "https://api.coindesk.com/v1/bpi/currentprice.json"
+    response = requests.get(url)
+
+    if response.status_code != 200:
+        raise ConnectionError("Failed to fetch Bitcoin price")
+
+    data = response.json()
+    return data["bpi"]["USD"]["rate_float"]

bitcoin_trading_simulation.py

@@ -1,38 +1,34 @@
 import argparse
 import numpy as np
 import pandas as pd
-import argparse
 
 
 class Colors:
     HEADER = '\033[95m'
     BLUE = '\033[94m'
+    CYAN = '\033[96m'
     GREEN = '\033[92m'
-    RED = '\033[91m'
+    WARNING = '\033[93m'
+    FAIL = '\033[91m'
+    RED = FAIL  # Alias for compatibility
     ENDC = '\033[0m'
     BOLD = '\033[1m'
+    UNDERLINE = '\033[4m'
 
     @classmethod
     def disable(cls):
         cls.HEADER = ''
         cls.BLUE = ''
+        cls.CYAN = ''
         cls.GREEN = ''
+        cls.WARNING = ''
+        cls.FAIL = ''
         cls.RED = ''
         cls.ENDC = ''
         cls.BOLD = ''
+        cls.UNDERLINE = ''
 
 
-class Colors:
-    HEADER = '\033[95m'
-    BLUE = '\033[94m'
-    CYAN = '\033[96m'
-    GREEN = '\033[92m'
-    WARNING = '\033[93m'
-    FAIL = '\033[91m'
-    ENDC = '\033[0m'
-    BOLD = '\033[1m'
-    UNDERLINE = '\033[4m'
-
 def simulate_bitcoin_prices(days=60, initial_price=50000, volatility=0.02):
     """
     Simulates Bitcoin prices for a given number of days using Geometric Brownian Motion.
@@ -87,9 +83,8 @@ def simulate_trading(signals, initial_cash=10000, quiet=False):
     portfolio['total_value'] = float(initial_cash)
 
     if not quiet:
-        print(f"{Colors.HEADER}{Colors.BOLD}------ Daily Trading Ledger ------{Colors.ENDC}")
+        print(f"\n{Colors.HEADER}{Colors.BOLD}------ Daily Trading Ledger ------{Colors.ENDC}")
 
-    print(f"\n{Colors.HEADER}{Colors.BOLD}------ Daily Trading Ledger ------{Colors.ENDC}")
     for i, row in signals.iterrows():
         if i > 0:
             portfolio.loc[i, 'cash'] = portfolio.loc[i-1, 'cash']
@@ -100,14 +95,18 @@ def simulate_trading(signals, initial_cash=10000, quiet=False):
             btc_to_buy = portfolio.loc[i, 'cash'] / row['price']
             portfolio.loc[i, 'btc'] += btc_to_buy
             portfolio.loc[i, 'cash'] -= btc_to_buy * row['price']
-            print(f"{Colors.GREEN}🟢 Day {i}: Buy {btc_to_buy:.4f} BTC at ${row['price']:.2f}{Colors.ENDC}")
+            if not quiet:
+                print(f"{Colors.GREEN}🟢 Day {i}: Buy {btc_to_buy:.4f} BTC at "
+                      f"${row['price']:.2f}{Colors.ENDC}")
 
         # Sell signal
         elif row['positions'] == -2.0:
             if portfolio.loc[i, 'btc'] > 0:
                 cash_received = portfolio.loc[i, 'btc'] * row['price']
                 portfolio.loc[i, 'cash'] += cash_received
-                print(f"{Colors.FAIL}🔴 Day {i}: Sell {portfolio.loc[i, 'btc']:.4f} BTC at ${row['price']:.2f}{Colors.ENDC}")
+                if not quiet:
+                    print(f"{Colors.FAIL}🔴 Day {i}: Sell {portfolio.loc[i, 'btc']:.4f} BTC at "
+                          f"${row['price']:.2f}{Colors.ENDC}")
                 portfolio.loc[i, 'btc'] = 0
 
         portfolio.loc[i, 'total_value'] = portfolio.loc[i, 'cash'] + portfolio.loc[i, 'btc'] * row['price']
@@ -149,17 +148,39 @@ def simulate_trading(signals, initial_cash=10000, quiet=False):
     final_value = portfolio['total_value'].iloc[-1]
     initial_cash = args.initial_cash
     profit = final_value - initial_cash
+    roi = (profit / initial_cash) * 100
+
+    # Calculate trade stats
+    buys = len(signals[signals['positions'] == 2.0])
+    sells = len(signals[signals['positions'] == -2.0])
+    total_trades = buys + sells
 
     # Compare with buy and hold strategy
     buy_and_hold_btc = args.initial_cash / prices.iloc[0]
     buy_and_hold_value = buy_and_hold_btc * prices.iloc[-1]
-
-    print(f"\n{Colors.HEADER}{Colors.BOLD}------ Final Portfolio Performance ------{Colors.ENDC}")
-    print(f"Initial Cash: ${initial_cash:.2f}")
-    print(f"Final Portfolio Value: ${final_value:.2f}")
+
+    print(f"\n{Colors.HEADER}{Colors.BOLD}╔══════════════════════════════════════════╗{Colors.ENDC}")
+    print(f"{Colors.HEADER}{Colors.BOLD}║       Final Portfolio Performance        ║{Colors.ENDC}")
+    print(f"{Colors.HEADER}{Colors.BOLD}╠══════════════════════════════════════════╣{Colors.ENDC}")
+    print(f"{Colors.HEADER}║{Colors.ENDC} {'Initial Cash:':<25} ${initial_cash:>14,.2f} "
+          f"{Colors.HEADER}║{Colors.ENDC}")
+    print(f"{Colors.HEADER}║{Colors.ENDC} {'Final Value:':<25} ${final_value:>14,.2f} "
+          f"{Colors.HEADER}║{Colors.ENDC}")
+
     if profit >= 0:
-        print(f"{Colors.GREEN}💰 Profit/Loss: ${profit:.2f}{Colors.ENDC}")
+        print(f"{Colors.HEADER}║{Colors.ENDC} {Colors.GREEN}💰 Profit/Loss:          "
+              f"${profit:>14,.2f}{Colors.ENDC} {Colors.HEADER}║{Colors.ENDC}")
+        print(f"{Colors.HEADER}║{Colors.ENDC} {Colors.GREEN}   ROI:                  "
+              f"{roi:>14.2f}%{Colors.ENDC} {Colors.HEADER}║{Colors.ENDC}")
     else:
-        print(f"{Colors.FAIL}📉 Profit/Loss: ${profit:.2f}{Colors.ENDC}")
-    print(f"Buy and Hold Strategy Value: ${buy_and_hold_value:.2f}")
-    print(f"{Colors.HEADER}-----------------------------------------{Colors.ENDC}")
+        print(f"{Colors.HEADER}║{Colors.ENDC} {Colors.FAIL}📉 Profit/Loss:          "
+              f"${profit:>14,.2f}{Colors.ENDC} {Colors.HEADER}║{Colors.ENDC}")
+        print(f"{Colors.HEADER}║{Colors.ENDC} {Colors.FAIL}   ROI:                  "
+              f"{roi:>14.2f}%{Colors.ENDC} {Colors.HEADER}║{Colors.ENDC}")
+
+    print(f"{Colors.HEADER}╠══════════════════════════════════════════╣{Colors.ENDC}")
+    print(f"{Colors.HEADER}║{Colors.ENDC} {'Trades (B/S):':<25} {f'{buys}/{sells}':>15} "
+          f"{Colors.HEADER}║{Colors.ENDC}")
+    print(f"{Colors.HEADER}║{Colors.ENDC} {'Buy & Hold:':<25} ${buy_and_hold_value:>14,.2f} "
+          f"{Colors.HEADER}║{Colors.ENDC}")
+    print(f"{Colors.HEADER}{Colors.BOLD}╚══════════════════════════════════════════╝{Colors.ENDC}")

requirements.txt

@@ -1,2 +1,3 @@
 numpy
 pandas
+requests

test_bitcoin.py

@@ -2,6 +2,7 @@
 from unittest.mock import patch
 from bitcoin import get_bitcoin_price, calculate_value
 
+
 # Test 1: Verify the calculation logic
 def test_calculate_value():
     """Ensure BTC to USD conversion math is correct."""
@@ -10,10 +11,12 @@ def test_calculate_value():
     expected = 125000.0
     assert calculate_value(amount, price) == expected
 
+
 # Test 2: Verify handling of zero amount
 def test_calculate_value_zero():
     assert calculate_value(0, 50000.0) == 0.0
 
+
 # Test 3: Mocking an API response
 @patch('bitcoin.requests.get')
 def test_get_bitcoin_price(mock_get):
@@ -23,10 +26,11 @@ def test_get_bitcoin_price(mock_get):
         "bpi": {"USD": {"rate_float": 62000.50}}
     }
     mock_get.return_value.status_code = 200
-    
+
     price = get_bitcoin_price()
     assert price == 62000.50
 
+
 # Test 4: Handling API failure
 @patch('bitcoin.requests.get')
 def test_get_price_api_error(mock_get):

test_simulation.py

@@ -1,22 +1,24 @@
-import pytest
 import pandas as pd
 import numpy as np
 from bitcoin_trading_simulation import simulate_bitcoin_prices, calculate_moving_averages, generate_trading_signals
 
+
 def test_simulate_bitcoin_prices():
     days = 10
     prices = simulate_bitcoin_prices(days=days, initial_price=50000)
     assert len(prices) == days
     assert isinstance(prices, pd.Series)
     assert prices.name == 'Price'
 
+
 def test_calculate_moving_averages():
     prices = pd.Series([100, 101, 102, 103, 104, 105, 106, 107, 108, 109], name='Price')
     signals = calculate_moving_averages(prices, short_window=3, long_window=5)
     assert 'short_mavg' in signals.columns
     assert 'long_mavg' in signals.columns
     assert not signals['short_mavg'].isnull().all()
 
+
 def test_generate_trading_signals():
     # Create dummy signals DataFrame
     data = {