new chartview class, updated db locations

ChartView.py

@@ -0,0 +1,139 @@
+import mplfinance as mpf
+import pandas as pd
+import matplotlib.pyplot as plt
+from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2Tk
+import matplotlib.animation as animation
+import ccxt
+from matplotlib.dates import date2num
+import threading
+import tkinter as tk
+from tkinter import ttk
+
+class ChartView:
+    def __init__(self, exchange_ids, symbol='BTC/USDT', timeframe='1m', limit=100):
+        self.exchange_ids = exchange_ids
+        self.symbol = symbol
+        self.timeframe = timeframe
+        self.limit = limit
+        self.running = False
+        self.fig = None
+        self.ax1 = None
+        self.ax2 = None
+        self.animation = None
+        self.current_exchange_id = exchange_ids[0]
+        self.root = None
+        self.canvas = None
+        
+        # Create exchanges dictionary to avoid reconnecting each time
+        self.exchanges = {}
+        for exchange_id in exchange_ids:
+            self.connect_to_exchange(exchange_id)
+            
+    def connect_to_exchange(self, exchange_id):
+        if exchange_id in self.exchanges:
+            self.exchange = self.exchanges[exchange_id]
+            return
+            
+        try:
+            exchange_class = getattr(ccxt, exchange_id)
+            exchange = exchange_class({
+                'enableRateLimit': True,
+            })
+            exchange.load_markets()
+            
+            if self.symbol not in exchange.markets:
+                raise Exception(f"Symbol {self.symbol} not found on {exchange_id}")
+                
+            self.exchanges[exchange_id] = exchange
+            self.exchange = exchange
+        except Exception as e:
+            raise Exception(f"Failed to connect to {exchange_id}: {str(e)}")
+
+    def fetch_ohlcv(self, exchange_id):
+        try:
+            exchange = self.exchanges[exchange_id]
+            ohlcv = exchange.fetch_ohlcv(self.symbol, self.timeframe, limit=self.limit)
+            df = pd.DataFrame(ohlcv, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
+            df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
+            df.set_index('timestamp', inplace=True)
+            return df
+        except Exception as e:
+            print(f"Error fetching OHLCV data from {exchange_id}: {str(e)}")
+            return None
+    
+    def update_chart(self):
+        if not self.running:
+            return
+            
+        df = self.fetch_ohlcv(self.current_exchange_id)
+        if df is not None:
+            self.ax1.clear()
+            self.ax2.clear()
+            
+            mpf.plot(df, type='candle', ax=self.ax1, volume=self.ax2, 
+                     style='yahoo', xrotation=0, ylabel='Price', 
+                     ylabel_lower='Volume', show_nontrading=False)
+            
+            latest_price = df['close'].iloc[-1]
+            self.ax1.set_title(f'{self.symbol} on {self.current_exchange_id} - Last: ${latest_price:.2f}')
+            
+            # Refresh the canvas
+            self.canvas.draw()
+    
+    def on_exchange_change(self, event=None):
+        selected_exchange = self.exchange_var.get()
+        if selected_exchange != self.current_exchange_id:
+            self.current_exchange_id = selected_exchange
+            self.update_chart()
+    
+    def start_gui(self):
+        self.root = tk.Tk()
+        self.root.title("Crypto Chart Viewer")
+        self.root.geometry("1200x800")
+        
+        # Create frame for controls
+        control_frame = ttk.Frame(self.root)
+        control_frame.pack(side=tk.TOP, fill=tk.X, padx=10, pady=5)
+        
+        # Dropdown for selecting exchange
+        ttk.Label(control_frame, text="Exchange:").pack(side=tk.LEFT, padx=(0, 5))
+        self.exchange_var = tk.StringVar(value=self.current_exchange_id)
+        exchange_dropdown = ttk.Combobox(control_frame, textvariable=self.exchange_var, values=self.exchange_ids, width=15)
+        exchange_dropdown.pack(side=tk.LEFT, padx=(0, 10))
+        exchange_dropdown.bind("<<ComboboxSelected>>", self.on_exchange_change)
+        
+        # Create the figure
+        self.fig = plt.Figure(figsize=(12, 8), dpi=100)
+        self.ax1 = self.fig.add_subplot(6, 1, (1, 4))
+        self.ax2 = self.fig.add_subplot(6, 1, (5, 6), sharex=self.ax1)
+        
+        # Create the canvas to display the figure
+        self.canvas = FigureCanvasTkAgg(self.fig, master=self.root)
+        self.canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=True)
+        
+        # Add toolbar
+        toolbar = NavigationToolbar2Tk(self.canvas, self.root)
+        toolbar.update()
+        self.canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=True)
+        
+        # Initial chart update
+        self.running = True
+        self.update_chart()
+        
+        # Set up periodic updates
+        def update():
+            if self.running:
+                self.update_chart()
+                self.root.after(10000, update)  # Update every 10 seconds
+        
+        self.root.after(10000, update)
+        
+        # Handle window close
+        def on_closing():
+            self.running = False
+            self.root.destroy()
+            
+        self.root.protocol("WM_DELETE_WINDOW", on_closing)
+        
+        # Start the Tkinter event loop
+        self.root.mainloop()

WhalesWatcher.py

@@ -0,0 +1,218 @@
+import pandas as pd
+import time
+from datetime import datetime
+import logging
+import ccxt
+from sqlalchemy import create_engine, Column, Integer, String, Float, DateTime
+from sqlalchemy.ext.declarative import declarative_base
+from sqlalchemy.orm import sessionmaker
+
+Base = declarative_base()
+
+class Alert(Base):
+    __tablename__ = 'alerts'
+    
+    id = Column(Integer, primary_key=True)
+    exchange = Column(String)
+    order_type = Column(String)
+    amount = Column(Float)
+    price = Column(Float)
+    value_usd = Column(Float)
+    timestamp = Column(DateTime)
+
+class WhalesWatcher:
+    def __init__(self):
+        logging.basicConfig(
+            level=logging.INFO,
+            format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+            filename='whales_watcher.log',
+            filemode='a'  # Append mode
+        )
+        
+        console_handler = logging.StreamHandler()
+        console_handler.setLevel(logging.INFO)
+        console_handler.setFormatter(logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s'))
+        
+        self.logger = logging.getLogger('WhalesWatcher')
+        self.logger.addHandler(console_handler)
+        
+        self.exchanges = {}
+        self.symbol = 'BTC/USDT'
+        self.threshold = 1000000
+        self.check_interval = 5
+        self.large_orders = []
+        self.is_running = False
+        
+        self.logger.info("WhalesWatcher initialized with symbol: %s and threshold: $%d", self.symbol, self.threshold)
+        
+        self.engine = create_engine('sqlite:///databases/alerts.db')
+        Base.metadata.create_all(self.engine)
+        self.Session = sessionmaker(bind=self.engine)
+    
+    def connect_to_exchanges(self, exchange_ids, api_key=None, secret=None):
+        """Connect to multiple cryptocurrency exchanges."""
+        connected_exchanges = {}
+        for exchange_id in exchange_ids:
+            self.logger.info("Attempting to connect to exchange: %s", exchange_id)
+            try:
+                exchange_class = getattr(ccxt, exchange_id)
+                exchange = exchange_class({
+                    'apiKey': api_key,
+                    'secret': secret,
+                    'enableRateLimit': True,
+                })
+                exchange.load_markets()
+                connected_exchanges[exchange_id] = exchange
+                self.logger.info(f"Connected to {exchange_id} successfully")
+            except Exception as e:
+                self.logger.error(f"Failed to connect to {exchange_id}: {str(e)}")
+        
+        return connected_exchanges
+    
+    def fetch_order_book(self, exchange, symbol):
+        """Fetch the current order book for the given symbol on the specified exchange."""
+        try:
+            if exchange.id == 'huobi':
+                order_book = exchange.fetch_order_book(symbol, limit=150)
+            else:
+                order_book = exchange.fetch_order_book(symbol, limit=100)
+            return order_book
+        except Exception as e:
+            self.logger.error(f"Error fetching order book from {exchange.id} for {symbol}: {str(e)}")
+            return None
+    
+    def detect_whales(self, order_book):
+        """Detect whale orders in the order book."""
+        if not order_book:
+            return []
+        
+        whale_orders = []
+        
+        for bid in order_book['bids']:
+            if (len(bid) == 3):
+                price, amount, timestamp = bid
+            else:
+                price, amount = bid
+            value = price * amount
+            if value >= self.threshold:
+                whale_orders.append({
+                    'type': 'bid',
+                    'price': price,
+                    'amount': amount,
+                    'value_usd': value,
+                    'timestamp': datetime.now().isoformat()
+                })
+        
+        for ask in order_book['asks']:
+            if (len(ask) == 3):
+                price, amount, timestamp = ask
+            else:
+                price, amount = ask
+            value = price * amount
+            if value >= self.threshold:
+                whale_orders.append({
+                    'type': 'ask',
+                    'price': price,
+                    'amount': amount,
+                    'value_usd': value,
+                    'timestamp': datetime.now().isoformat()
+                })
+        
+        return whale_orders
+    
+    def analyze_whale_activity(self):
+        """Analyze the collected whale activity."""
+        self.logger.info("Analyzing whale activity")
+        if not self.large_orders:
+            return "No whale activity detected yet."
+        
+        df = pd.DataFrame(self.large_orders)
+        
+        # Basic analysis
+        bid_count = len(df[df['type'] == 'bid'])
+        ask_count = len(df[df['type'] == 'ask'])
+        total_bid_value = df[df['type'] == 'bid']['value_usd'].sum()
+        total_ask_value = df[df['type'] == 'ask']['value_usd'].sum()
+        
+        analysis = {
+            'total_whales': len(df),
+            'buy_orders': bid_count,
+            'sell_orders': ask_count,
+            'buy_pressure': total_bid_value,
+            'sell_pressure': total_ask_value,
+            'net_pressure': total_bid_value - total_ask_value
+        }
+        
+        return analysis
+    
+    def save_data(self, filename='whale_activity.csv'):
+        """Save the collected whale data to a CSV file."""
+        self.logger.info("Saving whale activity data to %s", filename)
+        if self.large_orders:
+            df = pd.DataFrame(self.large_orders)
+            df.to_csv(filename, index=False)
+            self.logger.info(f"Saved whale activity data to {filename}")
+    
+    def log_alert(self, order):
+        """Log the alert to the database."""
+        session = self.Session()
+        alert = Alert(
+            exchange=order['exchange'],
+            order_type='BUY' if order['type'] == 'bid' else 'SELL',
+            amount=order['amount'],
+            price=order['price'],
+            value_usd=order['value_usd'],
+            timestamp=datetime.now()
+        )
+        session.add(alert)
+        session.commit()
+        session.close()
+    
+    def run(self):
+        """Run the whale watcher continuously."""
+        self.logger.info("Running whale watcher")
+        if not self.exchanges:
+            # Connect to multiple exchanges
+            exchange_ids = ['binance', 'kraken', 'coinbase', 'bitfinex', 'huobi', 'kucoin', 'bybit', 'okx', 'gateio', 'mexc']
+            self.exchanges = self.connect_to_exchanges(exchange_ids)
+            if not self.exchanges:
+                self.logger.error("Cannot run whale watcher without connecting to any exchange")
+                return
+        
+        self.is_running = True
+        self.logger.info(f"Starting whale watcher with threshold ${self.threshold:,}")
+        self.logger.info(f"Connected to {len(self.exchanges)} exchanges: {', '.join(self.exchanges.keys())}")
+        
+        try:
+            while self.is_running:
+                for exchange_id, exchange in self.exchanges.items():
+                    if self.symbol not in exchange.markets:
+                        continue
+                    
+                    order_book = self.fetch_order_book(exchange, self.symbol)
+                    if not order_book:
+                        continue
+                    
+                    whale_orders = self.detect_whales(order_book)
+                    
+                    if whale_orders:
+                        for order in whale_orders:
+                            order['exchange'] = exchange_id
+                            self.large_orders.extend(whale_orders)
+                            
+                            self.log_alert(order)
+                            
+                            order_type = "BUY" if order['type'] == 'bid' else "SELL"
+                            self.logger.info(
+                                f"WHALE ALERT on {exchange_id}: {order_type} {order['amount']:.4f} BTC at ${order['price']:,.2f} " +
+                                f"(${order['value_usd']:,.2f})"
+                            )
+                time.sleep(self.check_interval)
+        except Exception as e:
+            self.logger.error(f"Error in run method: {str(e)}")
+    
+    def stop(self):
+        """Stop the whale watcher."""
+        self.logger.info("Stopping whale watcher...")
+        self.is_running = False
+        self.logger.info("Stopping whale watcher...")

main_price_predictor.py

@@ -1,7 +1,7 @@
 from BitcoinPricePredictor import BitcoinPricePredictor
 
 if __name__ == "__main__":
-    predictor = BitcoinPricePredictor(db_path='bitcoin_historical_data.db', timeframe='H')
+    predictor = BitcoinPricePredictor(db_path='databases/bitcoin_historical_data.db', timeframe='H')
     predictor.load_data()
     predictor.train_model()
     predictor.evaluate_model()

main_whales_watcher.py

@@ -0,0 +1,23 @@
+from WhalesWatcher import WhalesWatcher
+from ChartView import ChartView
+import threading
+
+def start_whales_watcher():
+    whales_watcher = WhalesWatcher()
+    whales_watcher.run()
+
+if __name__ == "__main__":
+    # Start WhalesWatcher in a separate thread
+    # watcher_thread = threading.Thread(target=start_whales_watcher)
+    # watcher_thread.daemon = True
+    # Start the watcher thread
+    # watcher_thread.start()
+
+    # Define exchanges for the chart
+    exchange_ids = ['binance', 'kraken', 'coinbase']  # Add more exchanges as needed
+    
+    # Start the chart viewer
+    chart_view = ChartView(exchange_ids)
+        
+    # Run the GUI (this will block until the window is closed)
+    chart_view.start_gui()

poetry.lock

@@ -1,5 +1,160 @@
 # This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand.
 
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+version = "3.2.0"
+description = "Simple DNS resolver for asyncio"
+optional = false
+python-versions = "*"
+groups = ["main"]
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+]
+
+[package.dependencies]
+pycares = ">=4.0.0"
+
+[[package]]
+name = "aiohappyeyeballs"
+version = "2.6.1"
+description = "Happy Eyeballs for asyncio"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
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+
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+async-timeout = {version = ">=4.0,<6.0", markers = "python_version < \"3.11\""}
+attrs = ">=17.3.0"
+frozenlist = ">=1.1.1"
+multidict = ">=4.5,<7.0"
+yarl = ">=1.12.0,<2.0"
+
+[package.extras]
+speedups = ["Brotli ; platform_python_implementation == \"CPython\"", "aiodns (>=3.2.0) ; sys_platform == \"linux\" or sys_platform == \"darwin\"", "brotlicffi ; platform_python_implementation != \"CPython\""]
+
+[[package]]
+name = "aiosignal"
+version = "1.3.2"
+description = "aiosignal: a list of registered asynchronous callbacks"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
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+]
+
+[package.dependencies]
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+
 [[package]]
 name = "annotated-types"
 version = "0.7.0"
@@ -35,6 +190,39 @@ doc = ["Sphinx (>=8.2,<9.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)",
 test = ["anyio[trio]", "blockbuster (>=1.5.23)", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "trustme", "truststore (>=0.9.1) ; python_version >= \"3.10\"", "uvloop (>=0.21) ; platform_python_implementation == \"CPython\" and platform_system != \"Windows\" and python_version < \"3.14\""]
 trio = ["trio (>=0.26.1)"]
 
+[[package]]
+name = "async-timeout"
+version = "5.0.1"
+description = "Timeout context manager for asyncio programs"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+markers = "python_version < \"3.11\""
+files = [
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+    {file = "async_timeout-5.0.1.tar.gz", hash = "sha256:d9321a7a3d5a6a5e187e824d2fa0793ce379a202935782d555d6e9d2735677d3"},
+]
+
+[[package]]
+name = "attrs"
+version = "25.3.0"
+description = "Classes Without Boilerplate"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
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+]
+
+[package.extras]
+benchmark = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"]
+cov = ["cloudpickle ; platform_python_implementation == \"CPython\"", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"]
+dev = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pre-commit-uv", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"]
+docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier"]
+tests = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"]
+tests-mypy = ["mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\""]
+
 [[package]]
 name = "beautifulsoup4"
 version = "4.13.3"
@@ -58,6 +246,32 @@ charset-normalizer = ["charset-normalizer"]
 html5lib = ["html5lib"]
 lxml = ["lxml"]
 
+[[package]]
+name = "ccxt"
+version = "4.4.69"
+description = "A JavaScript / TypeScript / Python / C# / PHP cryptocurrency trading library with support for 100+ exchanges"
+optional = false
+python-versions = "*"
+groups = ["main"]
+files = [
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+    {file = "ccxt-4.4.69.tar.gz", hash = "sha256:ba338f2db29169f5669f152f28b4237cf120fc054dc4069ea38760eaa3d3aff4"},
+]
+
+[package.dependencies]
+aiodns = {version = ">=1.1.1", markers = "python_version >= \"3.5.2\""}
+aiohttp = {version = "<=3.10.11", markers = "python_version >= \"3.5.2\""}
+certifi = ">=2018.1.18"
+cryptography = ">=2.6.1"
+requests = ">=2.18.4"
+setuptools = ">=60.9.0"
+typing-extensions = ">=4.4.0"
+yarl = {version = ">=1.7.2", markers = "python_version >= \"3.5.2\""}
+
+[package.extras]
+qa = ["ruff (==0.0.292)", "tox (>=4.8.0)"]
+type = ["mypy (==1.6.1)"]
+
 [[package]]
 name = "certifi"
 version = "2025.1.31"
@@ -70,6 +284,87 @@ files = [
     {file = "certifi-2025.1.31.tar.gz", hash = "sha256:3d5da6925056f6f18f119200434a4780a94263f10d1c21d032a6f6b2baa20651"},
 ]
 
+[[package]]
+name = "cffi"
+version = "1.17.1"
+description = "Foreign Function Interface for Python calling C code."
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+markers = "platform_python_implementation != \"PyPy\""
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 [[package]]
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 version = "3.4.1"
@@ -259,6 +554,64 @@ mypy = ["contourpy[bokeh,docs]", "docutils-stubs", "mypy (==1.11.1)", "types-Pil
 test = ["Pillow", "contourpy[test-no-images]", "matplotlib"]
 test-no-images = ["pytest", "pytest-cov", "pytest-rerunfailures", "pytest-xdist", "wurlitzer"]
 
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+    {file = "yarl-1.18.3.tar.gz", hash = "sha256:ac1801c45cbf77b6c99242eeff4fffb5e4e73a800b5c4ad4fc0be5def634d2e1"},
+]
+
+[package.dependencies]
+idna = ">=2.0"
+multidict = ">=4.0"
+propcache = ">=0.2.0"
+
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<4.0"
-content-hash = "a348c383fcfd41f6983c876e59076f0a6fa41c4def9bff1558ba782b03593301"
+content-hash = "5880eb67a4d2c3415097b4b66e807fb5a7f4c64852c015f0adc6d46d256ade15"

pyproject.toml

@@ -16,7 +16,9 @@ dependencies = [
     "scikit-learn (>=1.6.1,<2.0.0)",
     "ollama (>=0.4.7,<0.5.0)",
     "transformers (>=4.49.0,<5.0.0)",
-    "markdownify (>=1.1.0,<2.0.0)"
+    "markdownify (>=1.1.0,<2.0.0)",
+    "ccxt (>=4.4.69,<5.0.0)",
+    "mplfinance (>=0.12.10b0,<0.13.0)",
 ]
 
 

utils/parse_btc_csv_to_db.py

@@ -12,7 +12,7 @@ df.set_index('Timestamp', inplace=True)
 df = df[~df.index.isna()]
 
 # Create a connection to the SQLite database
-engine = create_engine('sqlite:///bitcoin_historical_data.db')
+engine = create_engine('sqlite:///databases/bitcoin_historical_data.db')
 
 # Check if the table already exists and get the last timestamp from the database
 with engine.connect() as connection: