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🎨 Palette: Improved CLI readability with colors and emojis #16

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🎨 Palette: Improved CLI readability with colors and emojis #16

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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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## 2024-05-22 - [CLI Color Coding]
**Learning:** Even in CLI tools, color coding and emojis drastically improve the "glanceability" of data streams (logs). Users can instantly distinguish good (Buy/Profit) from bad (Sell/Loss) events without reading the text.
**Action:** When working on CLI tools in the future, check if output is a "wall of text" and introduce semantic coloring for key events. Use a simple `Colors` class to keep it dependency-free for small scripts.
28 changes: 20 additions & 8 deletions bitcoin_trading_simulation.py
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@@ -1,6 +1,13 @@
import numpy as np
import pandas as pd

# ANSI Color Codes
class Colors:
HEADER = '\033[95m'
GREEN = '\033[92m'
RED = '\033[91m'
RESET = '\033[0m'

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 +54,11 @@ 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']
portfolio['total_value'] = float(initial_cash)

print("------ Daily Trading Ledger ------")
print(f"{Colors.HEADER}------ 📊 Daily Trading Ledger ------{Colors.RESET}")
for i, row in signals.iterrows():
if i > 0:
portfolio.loc[i, 'cash'] = portfolio.loc[i-1, 'cash']
Expand All @@ -62,14 +69,14 @@ 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"Day {i}: {Colors.GREEN}🟢 Buy {btc_to_buy:.4f} BTC at ${row['price']:.2f}{Colors.RESET}")

# 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"Day {i}: {Colors.RED}🔴 Sell {portfolio.loc[i, 'btc']:.4f} BTC at ${row['price']:.2f}{Colors.RESET}")
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 +106,14 @@ 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}------ 📈 Final Portfolio Performance ------{Colors.RESET}")
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"Profit/Loss: {Colors.GREEN}🚀 ${profit:.2f}{Colors.RESET}")
else:
print(f"Profit/Loss: {Colors.RED}📉 ${profit:.2f}{Colors.RESET}")

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