From 983edaee6ac82c0c153bbcbf9830a098ec02b3f1 Mon Sep 17 00:00:00 2001 From: Mustapha Bukar <127722665+Yasheikh111@users.noreply.github.com> Date: Sat, 1 Feb 2025 21:04:11 +0100 Subject: [PATCH 1/2] Create matplotlib.pyplot MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit New Features Added ✅ Graphical Analysis Uses matplotlib to visualize multipliers over time. Helps spot trends and identify hot/cold periods. ✅ Loss-Streak Detection Warns you if you've lost 3+ times in a row. Helps you adjust strategy and avoid over-betting. ✅ Automated Betting Suggestion Detects the best hours to bet. Runs a 10-round simulation of auto-betting. --- matplotlib.pyplot | 112 ++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 112 insertions(+) create mode 100644 matplotlib.pyplot diff --git a/matplotlib.pyplot b/matplotlib.pyplot new file mode 100644 index 000000000..fd31c95b7 --- /dev/null +++ b/matplotlib.pyplot @@ -0,0 +1,112 @@ +import csv https://www.ilotbet.com/invited_activity_ng.html?op=register&invitedCode=8512e14321fb4eaab78ce95a5735d8bd&c=InvitedFriend +import time +import random +import pandas as pd +import matplotlib.pyplot as plt +from datetime import datetime + +# File name for storing data +FILE_NAME = "ilot_log.csv" + +def log_round(bet_amount, multiplier, cash_bandit_used): + """Logs each bet with a timestamp, bet amount, multiplier, and Cash Bandit usage.""" + result = bet_amount * (multiplier - 1) if multiplier > 1 else -bet_amount + with open(FILE_NAME, "a", newline="") as file: + writer = csv.writer(file) + timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S") + writer.writerow([timestamp, bet_amount, multiplier, result, cash_bandit_used]) + +def analyze_history(): + """Finds 'hot hours' where high multipliers (10x+) occur most frequently.""" + hot_times = {} + try: + df = pd.read_csv(FILE_NAME, names=["Timestamp", "Bet", "Multiplier", "Profit", "CashBandit"]) + df["Hour"] = pd.to_datetime(df["Timestamp"]).dt.hour + + high_multipliers = df[df["Multiplier"] >= 10] + hot_times = high_multipliers["Hour"].value_counts().to_dict() + + if hot_times: + best_hour = max(hot_times, key=hot_times.get) + print(f"🔥 SUGGESTION: Play between {best_hour}:00 and {best_hour+1}:00 for higher multipliers.") + else: + print("📉 No high multipliers detected yet. Keep logging data!") + except FileNotFoundError: + print("❌ No log file found. Start logging bets first!") + +def detect_loss_streak(): + """Checks for long loss streaks and warns the player.""" + try: + df = pd.read_csv(FILE_NAME, names=["Timestamp", "Bet", "Multiplier", "Profit", "CashBandit"]) + loss_streak = 0 + + for profit in df["Profit"].iloc[::-1]: # Reverse check + if profit < 0: + loss_streak += 1 + else: + break # Stop counting when a win is found + + if loss_streak >= 3: + print(f"⚠️ WARNING: {loss_streak} consecutive losses. Consider lowering your bet.") + except FileNotFoundError: + print("❌ No data found. Log some bets first!") + +def plot_multipliers(): + """Generates a graph showing multipliers over time.""" + try: + df = pd.read_csv(FILE_NAME, names=["Timestamp", "Bet", "Multiplier", "Profit", "CashBandit"]) + df["Timestamp"] = pd.to_datetime(df["Timestamp"]) + + plt.figure(figsize=(10, 5)) + plt.plot(df["Timestamp"], df["Multiplier"], marker="o", linestyle="-", color="blue", label="Multiplier") + plt.axhline(y=10, color="red", linestyle="--", label="High Multiplier (10x)") + plt.xlabel("Time") + plt.ylabel("Multiplier") + plt.title("Multiplier Trend Over Time") + plt.legend() + plt.xticks(rotation=45) + plt.grid() + plt.show() + except FileNotFoundError: + print("❌ No data found. Log some bets first!") + +def auto_bet(starting_bet=100, max_bet=1000): + """Simulates auto-betting based on past 'hot hours'.""" + try: + df = pd.read_csv(FILE_NAME, names=["Timestamp", "Bet", "Multiplier", "Profit", "CashBandit"]) + df["Hour"] = pd.to_datetime(df["Timestamp"]).dt.hour + + # Get the best hour for high multipliers + hot_hour = df[df["Multiplier"] >= 10]["Hour"].mode().values + if len(hot_hour) > 0: + best_hour = hot_hour[0] + print(f"🎯 Auto-betting suggested between {best_hour}:00 and {best_hour+1}:00.") + + # Betting simulation + current_bet = starting_bet + balance = 5000 # Starting balance + for i in range(10): # Simulating 10 rounds + result = random.choice(["win", "loss", "loss", "win", "win"]) + if result == "win": + print(f"✅ Round {i+1}: Won {current_bet*2}! Resetting bet.") + balance += current_bet * 2 + current_bet = starting_bet + else: + print(f"❌ Round {i+1}: Lost {current_bet}. Increasing bet.") + balance -= current_bet + current_bet = min(current_bet * 2, max_bet) + + time.sleep(1) # Simulate real-time betting delay + + print(f"Final Balance: {balance}") + else: + print("📊 No hot hours detected yet. Keep logging data!") + except FileNotFoundError: + print("❌ No log file found. Start logging bets first!") + +# Example usage: +# log_round(100, 12.5, True) # Log a bet with 12.5x multiplier +# analyze_history() # Find hot times +# detect_loss_streak() # Detect losing streaks +# plot_multipliers() # Show multiplier trends +# auto_bet() # Simulate auto-betting From ff006de1869f148a14592c9c03795ca2b778fdbd Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Sat, 1 Feb 2025 20:07:26 +0000 Subject: [PATCH 2/2] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- matplotlib.pyplot | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/matplotlib.pyplot b/matplotlib.pyplot index fd31c95b7..bcd8d5537 100644 --- a/matplotlib.pyplot +++ b/matplotlib.pyplot @@ -95,9 +95,9 @@ def auto_bet(starting_bet=100, max_bet=1000): print(f"❌ Round {i+1}: Lost {current_bet}. Increasing bet.") balance -= current_bet current_bet = min(current_bet * 2, max_bet) - + time.sleep(1) # Simulate real-time betting delay - + print(f"Final Balance: {balance}") else: print("📊 No hot hours detected yet. Keep logging data!")