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🎨 Palette: Enhance CLI output with colors and emojis #13

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🎨 Palette: Enhance CLI output with colors and emojis #13

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3 changes: 3 additions & 0 deletions .Jules/palette.md
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Original file line number Diff line number Diff line change
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## 2024-05-23 - CLI Visual Hierarchy
**Learning:** CLI tools often neglect visual hierarchy. Adding simple colors (Green for good, Red for bad, Purple for headers) and emojis drastically improves scannability and "delight" without adding heavy dependencies.
**Action:** For future CLI tools, always implement a basic `Colors` class or use `rich`/`click` to ensure the user isn't staring at a wall of white text.
30 changes: 23 additions & 7 deletions bitcoin_trading_simulation.py
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import numpy as np
import pandas as pd

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.
Expand Down Expand Up @@ -47,11 +58,11 @@ def simulate_trading(signals, initial_cash=10000):
"""
portfolio = pd.DataFrame(index=signals.index).fillna(0.0)
portfolio['price'] = signals['price']
portfolio['cash'] = initial_cash
portfolio['cash'] = float(initial_cash)
portfolio['btc'] = 0.0
portfolio['total_value'] = portfolio['cash']

print("------ Daily Trading Ledger ------")
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']
Expand All @@ -62,14 +73,14 @@ def simulate_trading(signals, initial_cash=10000):
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"Day {i}: Buy {btc_to_buy:.4f} BTC at ${row['price']:.2f}")
print(f"{Colors.GREEN}🟢 Day {i}: Buy {btc_to_buy:.4f} BTC at ${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"Day {i}: Sell {portfolio.loc[i, 'btc']:.4f} BTC at ${row['price']:.2f}")
print(f"{Colors.FAIL}🔴 Day {i}: Sell {portfolio.loc[i, 'btc']:.4f} BTC at ${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']
Expand Down Expand Up @@ -99,9 +110,14 @@ def simulate_trading(signals, initial_cash=10000):
buy_and_hold_btc = initial_cash / prices.iloc[0]
buy_and_hold_value = buy_and_hold_btc * prices.iloc[-1]

print("\n------ Final Portfolio Performance ------")
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"Profit/Loss: ${profit:.2f}")

if profit >= 0:
print(f"{Colors.GREEN}💰 Profit: ${profit:.2f}{Colors.ENDC}")
else:
print(f"{Colors.FAIL}📉 Loss: ${profit:.2f}{Colors.ENDC}")

print(f"Buy and Hold Strategy Value: ${buy_and_hold_value:.2f}")
print("-----------------------------------------")
print(f"{Colors.HEADER}-----------------------------------------{Colors.ENDC}")
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