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6 changes: 3 additions & 3 deletions .Jules/palette.md
Original file line number Diff line number Diff line change
@@ -1,3 +1,3 @@
## 2026-01-24 - [CLI Visual Hierarchy]
**Learning:** UX principles like visual hierarchy and semantic coloring apply equally to CLI tools. Using ANSI codes and emojis transforms a wall of text into a scannable dashboard.
**Action:** For future CLI tools, prioritize a `Colors` class or library early to establish a visual language (Green=Success/Buy, Red=Failure/Sell).
## 2024-05-22 - Visual Hierarchy in CLI Output
**Learning:** Adding color-coded indicators (Green/Red) and emojis (💰, 📉) in CLI tools significantly reduces cognitive load when parsing financial data streams. It transforms a wall of text into a scannable narrative.
**Action:** For data-heavy CLI applications, always implement a semantic color system and visual anchors (icons/emojis) for key events.
23 changes: 11 additions & 12 deletions bitcoin_trading_simulation.py
Original file line number Diff line number Diff line change
@@ -1,13 +1,13 @@
import numpy as np
import pandas as pd

# ANSI color codes for visual enhancement
class Colors:
HEADER = '\033[95m'
BLUE = '\033[94m'
GREEN = '\033[92m'
RED = '\033[91m'
PURPLE = '\033[95m'
ENDC = '\033[0m'
BOLD = '\033[1m'
RESET = '\033[0m'

def simulate_bitcoin_prices(days=60, initial_price=50000, volatility=0.02):
"""
Expand Down Expand Up @@ -57,9 +57,9 @@ def simulate_trading(signals, initial_cash=10000):
portfolio['price'] = signals['price']
portfolio['cash'] = float(initial_cash)
portfolio['btc'] = 0.0
portfolio['total_value'] = portfolio['cash']
portfolio['total_value'] = float(initial_cash)

print(f"\n{Colors.PURPLE}{Colors.BOLD}------ Daily Trading Ledger ------{Colors.RESET}")
print(f"{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 @@ -70,14 +70,14 @@ 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}: {Colors.GREEN}📈 [BUY]{Colors.RESET} {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}: {Colors.RED}📉 [SELL]{Colors.RESET} {portfolio.loc[i, 'btc']:.4f} BTC at ${row['price']:.2f}")
print(f"{Colors.RED}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 @@ -107,15 +107,14 @@ 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(f"\n{Colors.PURPLE}{Colors.BOLD}------ Final Portfolio Performance ------{Colors.RESET}")
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}")

if profit >= 0:
profit_str = f"{Colors.GREEN}💰 +${profit:.2f}{Colors.RESET}"
print(f"Profit/Loss: {Colors.GREEN}📈 ${profit:.2f}{Colors.ENDC}")
else:
profit_str = f"{Colors.RED}📉 -${abs(profit):.2f}{Colors.RESET}"
print(f"Profit/Loss: {Colors.RED}📉 ${profit:.2f}{Colors.ENDC}")

print(f"Profit/Loss: {profit_str}")
print(f"Buy and Hold Strategy Value: ${buy_and_hold_value:.2f}")
print(f"{Colors.PURPLE}-----------------------------------------{Colors.RESET}")
print(f"{Colors.HEADER}-----------------------------------------{Colors.ENDC}")
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