dane z plików - nie chodzi

.gitignore

@@ -1 +1,2 @@
 *.csv
+historical_data_1m.json

app.py

@@ -4,17 +4,19 @@ import asyncio
 import os
 import json
 import csv
+import re
 from flask import Flask, render_template, request
 from flask_socketio import SocketIO
 from binance import Client
 import websockets
 from threading import Lock
-from datetime import datetime, timedelta, timezone
+from datetime import datetime, timedelta
 
 # --- Configuration ---
 SYMBOL = 'ETHUSDT'
-# The CSV file is now the primary source of historical data.
+HISTORY_FILE = 'historical_data_1m.json'
-HISTORY_CSV_FILE = 'ETHUSDT_1m_Binance.csv'
+DATA_FOLDER = 'data'
+USER_PREFERENCES_FILE = 'user_preferences.json'
 RESTART_TIMEOUT_S = 15
 BINANCE_WS_URL = f"wss://stream.binance.com:9443/ws/{SYMBOL.lower()}@trade"
 
@@ -29,141 +31,290 @@ socketio = SocketIO(app, async_mode='threading')
 # --- Global State ---
 app_initialized = False
 app_init_lock = Lock()
-# This cache will hold the filtered historical data to be sent to the frontend.
+current_bar = {} # To track the currently forming 1-minute candle
-historical_data_cache = []
+selected_csv_file = None  # Currently selected CSV file
+csv_file_lock = Lock()  # Lock for CSV file operations
 
-# --- Helper Function for Optimized Reading ---
+# --- Utility Functions ---
-def get_last_timestamp_from_csv(filepath):
+def get_available_csv_files():
-    """
+    """Get list of available CSV files with their start dates."""
-    Efficiently reads the end of a CSV to get the timestamp from the last valid row.
+    csv_files = []
-    This avoids reading the entire file into memory.
+    if not os.path.exists(DATA_FOLDER):
-    Returns a datetime object or None.
+        os.makedirs(DATA_FOLDER)
-    """
+        return csv_files
+    
+    for filename in os.listdir(DATA_FOLDER):
+        if filename.endswith('.csv') and SYMBOL in filename:
+            # Extract date from filename like ETHUSDT_20250101.csv
+            match = re.search(r'(\d{8})', filename)
+            if match:
+                date_str = match.group(1)
                 try:
-        with open(filepath, 'rb') as f:
+                    start_date = datetime.strptime(date_str, '%Y%m%d')
-            # Seek to a position near the end of the file to read a chunk.
+                    file_path = os.path.join(DATA_FOLDER, filename)
-            # 4096 bytes should be enough to contain several lines.
+                    file_size = os.path.getsize(file_path)
-            f.seek(0, os.SEEK_END)
+                    csv_files.append({
-            filesize = f.tell()
+                        'filename': filename,
-            if filesize == 0:
+                        'start_date_str': start_date.strftime('%Y-%m-%d'),
-                return None
+                        'date_str': date_str,
-            
+                        'size': file_size,
-            f.seek(max(0, filesize - 4096), os.SEEK_SET)
+                        'display_name': f"{start_date.strftime('%Y-%m-%d')} ({filename})"
-            
+                    })
-            # Read the last part of the file
+                    logging.info(f"Found CSV file: {filename}, size: {file_size}, date: {date_str}")
-            lines = f.readlines()
+                except ValueError:
-            if not lines:
+                    logging.warning(f"Could not parse date from filename: {filename}")
-                return None
-
-            # Get the last non-empty line
-            last_line_str = ''
-            for line in reversed(lines):
-                decoded_line = line.decode('utf-8').strip()
-                if decoded_line:
-                    last_line_str = decoded_line
-                    break
-            
-            if not last_line_str or 'Open time' in last_line_str:
-                return None
-
-            last_row = last_line_str.split(',')
-            dt_obj = datetime.strptime(last_row[0], '%Y-%m-%d %H:%M:%S')
-            return dt_obj.replace(tzinfo=timezone.utc)
-
-    except (IOError, IndexError, ValueError) as e:
-        logging.error(f"Could not get last timestamp from CSV: {e}")
-        return None
-
-# --- Data Management ---
-def load_and_update_data():
-    """
-    Loads historical data from the CSV, updates it with the latest data from Binance,
-    and then filters it for the frontend.
-    """
-    global historical_data_cache
-    client = Client()
-    
-    # 1. Check if the primary CSV data source exists.
-    if not os.path.exists(HISTORY_CSV_FILE):
-        logging.critical(f"CRITICAL: History file '{HISTORY_CSV_FILE}' not found. Please provide the CSV file. Halting data load.")
-        historical_data_cache = []
-        return
-
-    # 2. OPTIMIZED: Efficiently get the last timestamp to determine where to start fetching.
-    last_dt_in_csv = get_last_timestamp_from_csv(HISTORY_CSV_FILE)
-    
-    start_fetch_date = None
-    if last_dt_in_csv:
-        start_fetch_date = last_dt_in_csv + timedelta(minutes=1)
-        logging.info(f"Last record in CSV is from {last_dt_in_csv}. Checking for new data since {start_fetch_date}.")
-    else:
-        logging.warning("Could not determine last timestamp from CSV. Assuming file is new or empty. No new data will be fetched.")
-
-    # 3. Fetch new data from Binance.
-    new_klines = []
-    if start_fetch_date and start_fetch_date < datetime.now(timezone.utc):
-        while True:
-            logging.info(f"Fetching new klines from {start_fetch_date}...")
-            fetched = client.get_historical_klines(SYMBOL, Client.KLINE_INTERVAL_1MINUTE, start_fetch_date.strftime("%Y-%m-%d %H:%M:%S"))
-            if not fetched:
-                logging.info("No new klines to fetch.")
-                break
-            
-            new_klines.extend(fetched)
-            last_fetched_dt = datetime.fromtimestamp(fetched[-1][0] / 1000, tz=timezone.utc)
-            start_fetch_date = last_fetched_dt + timedelta(minutes=1)
-            logging.info(f"Fetched {len(fetched)} new klines, up to {last_fetched_dt}.")
-            if len(fetched) < 1000:
-                break
-            time.sleep(0.1)
-
-    # 4. If new data was found, append it to the CSV file.
-    if new_klines:
-        logging.info(f"Appending {len(new_klines)} new candles to {HISTORY_CSV_FILE}.")
-        try:
-            with open(HISTORY_CSV_FILE, 'a', newline='') as f:
-                writer = csv.writer(f)
-                for kline in new_klines:
-                    open_time_dt = datetime.fromtimestamp(kline[0] / 1000, tz=timezone.utc)
-                    open_time_str = open_time_dt.strftime('%Y-%m-%d %H:%M:%S')
-                    close_time_dt = datetime.fromtimestamp(kline[6] / 1000, tz=timezone.utc)
-                    close_time_str = close_time_dt.strftime('%Y-%m-%d %H:%M:%S.%f')[:-3]
-                    writer.writerow([open_time_str] + kline[1:6] + [close_time_str] + kline[7:])
-        except Exception as e:
-            logging.error(f"Failed to append new data to {HISTORY_CSV_FILE}: {e}")
-
-    # 5. OPTIMIZED: Read the CSV and load only the necessary data (2025 onwards) for the frontend.
-    logging.info("Reading CSV to populate cache with data from 01.01.2025 onwards...")
-    frontend_klines = []
-    frontend_start_dt = datetime(2025, 1, 1, tzinfo=timezone.utc)
-    
-    try:
-        with open(HISTORY_CSV_FILE, 'r', newline='') as f:
-            reader = csv.reader(f)
-            next(reader) # Skip header
-            for row in reader:
-                try:
-                    dt_obj = datetime.strptime(row[0], '%Y-%m-%d %H:%M:%S').replace(tzinfo=timezone.utc)
-                    if dt_obj >= frontend_start_dt:
-                        timestamp_ms = int(dt_obj.timestamp() * 1000)
-                        frontend_klines.append([
-                            timestamp_ms, row[1], row[2], row[3], row[4],
-                            "0", "0", "0", "0", "0", "0" 
-                        ])
-                except (ValueError, IndexError):
                     continue
     
-        historical_data_cache = frontend_klines
+    # Sort by start date (newest first)
-        logging.info(f"--- Data initialization complete. {len(historical_data_cache)} candles cached for frontend. ---")
+    csv_files.sort(key=lambda x: x['date_str'], reverse=True)
+    logging.info(f"Available CSV files: {[f['filename'] for f in csv_files]}")
+    return csv_files
+
+def get_default_csv_file():
+    """Get the default CSV file (smallest one or last used)."""
+    # Try to load last used file
+    if os.path.exists(USER_PREFERENCES_FILE):
+        try:
+            with open(USER_PREFERENCES_FILE, 'r') as f:
+                prefs = json.load(f)
+                last_file = prefs.get('last_csv_file')
+                if last_file and os.path.exists(os.path.join(DATA_FOLDER, last_file)):
+                    logging.info(f"Using last selected file: {last_file}")
+                    return last_file
+        except:
+            pass
+    
+    # Fall back to smallest file
+    csv_files = get_available_csv_files()
+    if csv_files:
+        # Filter to exclude the large Binance file for better performance
+        filtered_files = [f for f in csv_files if not f['filename'].endswith('_Binance.csv')]
+        if filtered_files:
+            smallest_file = min(filtered_files, key=lambda x: x['size'])
+            logging.info(f"Using smallest filtered file: {smallest_file['filename']} ({smallest_file['size']} bytes)")
+        else:
+            smallest_file = min(csv_files, key=lambda x: x['size'])
+            logging.info(f"Using smallest file: {smallest_file['filename']} ({smallest_file['size']} bytes)")
+        return smallest_file['filename']
+    
+    logging.warning("No CSV files found")
+    return None
+
+def save_user_preference(csv_filename):
+    """Save the user's CSV file preference."""
+    prefs = {}
+    if os.path.exists(USER_PREFERENCES_FILE):
+        try:
+            with open(USER_PREFERENCES_FILE, 'r') as f:
+                prefs = json.load(f)
+        except:
+            pass
+    
+    prefs['last_csv_file'] = csv_filename
+    with open(USER_PREFERENCES_FILE, 'w') as f:
+        json.dump(prefs, f)
+
+def read_csv_data(csv_filename):
+    """Read historical data from CSV file."""
+    csv_path = os.path.join(DATA_FOLDER, csv_filename)
+    if not os.path.exists(csv_path):
+        return []
+    
+    klines = []
+    try:
+        with open(csv_path, 'r', newline='', encoding='utf-8') as csvfile:
+            reader = csv.DictReader(csvfile)
+            for row in reader:
+                # Convert CSV row to kline format
+                open_time = datetime.strptime(row['Open time'], '%Y-%m-%d %H:%M:%S')
+                close_time = datetime.strptime(row['Close time'].split('.')[0], '%Y-%m-%d %H:%M:%S')
+                
+                # =================================================================
+                # --- FIX START: Convert string values to numeric types ---
+                # The original code passed the string values from the CSV directly.
+                # This caused the historical data to be misinterpreted by the chart.
+                # By converting to float/int here, we ensure data consistency.
+                # =================================================================
+                kline = [
+                    int(open_time.timestamp() * 1000),      # Open time (ms)
+                    float(row['Open']),                     # Open
+                    float(row['High']),                     # High
+                    float(row['Low']),                      # Low
+                    float(row['Close']),                    # Close
+                    float(row['Volume']),                   # Volume
+                    int(close_time.timestamp() * 1000),     # Close time (ms)
+                    float(row['Quote asset volume']),       # Quote asset volume
+                    int(row['Number of trades']),           # Number of trades
+                    float(row['Taker buy base asset volume']), # Taker buy base asset volume
+                    float(row['Taker buy quote asset volume']), # Taker buy quote asset volume
+                    float(row['Ignore'])                    # Ignore
+                ]
+                # --- FIX END ---
+                # =================================================================
+                klines.append(kline)
+    except Exception as e:
+        logging.error(f"Error reading CSV file {csv_filename}: {e}")
+        return []
+    
+    return klines
+
+def append_to_csv(csv_filename, candle_data):
+    """Append new candle data to CSV file."""
+    csv_path = os.path.join(DATA_FOLDER, csv_filename)
+    
+    try:
+        with csv_file_lock:
+            # Convert candle data to CSV row
+            open_time = datetime.fromtimestamp(candle_data['time'])
+            close_time = open_time.replace(second=59, microsecond=999000)
+            
+            row = [
+                open_time.strftime('%Y-%m-%d %H:%M:%S'),
+                candle_data['open'],
+                candle_data['high'],
+                candle_data['low'],
+                candle_data['close'],
+                0.0,  # Volume (placeholder)
+                close_time.strftime('%Y-%m-%d %H:%M:%S.%f')[:-3],
+                0.0,  # Quote asset volume (placeholder)
+                1,    # Number of trades (placeholder)
+                0.0,  # Taker buy base asset volume (placeholder)
+                0.0,  # Taker buy quote asset volume (placeholder)
+                0.0   # Ignore
+            ]
+            
+            # Check if file exists and has header
+            file_exists = os.path.exists(csv_path)
+            
+            with open(csv_path, 'a', newline='', encoding='utf-8') as csvfile:
+                writer = csv.writer(csvfile)
+                
+                # Write header if file is new
+                if not file_exists:
+                    headers = [
+                        'Open time', 'Open', 'High', 'Low', 'Close', 'Volume',
+                        'Close time', 'Quote asset volume', 'Number of trades',
+                        'Taker buy base asset volume', 'Taker buy quote asset volume', 'Ignore'
+                    ]
+                    writer.writerow(headers)
+                
+                writer.writerow(row)
                 
     except Exception as e:
-        logging.error(f"Failed to read CSV for frontend cache: {e}")
+        logging.error(f"Error appending to CSV file {csv_filename}: {e}")
-        historical_data_cache = []
 
+def fill_missing_data(csv_filename):
+    """Fill missing data by downloading from Binance."""
+    global selected_csv_file
+    
+    try:
+        logging.info(f"Checking for missing data in {csv_filename}")
+        
+        # Get the start date from filename
+        match = re.search(r'(\d{8})', csv_filename)
+        if not match:
+            return
+        
+        date_str = match.group(1)
+        start_date = datetime.strptime(date_str, '%Y%m%d')
+        
+        # Read existing data
+        existing_data = read_csv_data(csv_filename)
+        
+        # Determine what data we need to fetch
+        if existing_data:
+            # Get the last timestamp from existing data
+            last_timestamp = existing_data[-1][0] // 1000  # Convert to seconds
+            fetch_start = datetime.fromtimestamp(last_timestamp) + timedelta(minutes=1)
+        else:
+            fetch_start = start_date
+        
+        # Fetch missing data up to current time
+        now = datetime.now()
+        if fetch_start >= now:
+            logging.info(f"No missing data for {csv_filename}")
+            return existing_data
+        
+        logging.info(f"Fetching missing data from {fetch_start} to {now}")
+        
+        client = Client()
+        missing_klines = client.get_historical_klines(
+            SYMBOL,
+            Client.KLINE_INTERVAL_1MINUTE,
+            start_str=fetch_start.strftime('%Y-%m-%d %H:%M:%S'),
+            end_str=now.strftime('%Y-%m-%d %H:%M:%S')
+        )
+        
+        if missing_klines:
+            # Append missing data to CSV
+            csv_path = os.path.join(DATA_FOLDER, csv_filename)
+            with csv_file_lock:
+                with open(csv_path, 'a', newline='', encoding='utf-8') as csvfile:
+                    writer = csv.writer(csvfile)
+                    
+                    for kline in missing_klines:
+                        open_time = datetime.fromtimestamp(kline[0] / 1000)
+                        close_time = datetime.fromtimestamp(kline[6] / 1000)
+                        
+                        row = [
+                            open_time.strftime('%Y-%m-%d %H:%M:%S'),
+                            kline[1], kline[2], kline[3], kline[4], kline[5],
+                            close_time.strftime('%Y-%m-%d %H:%M:%S.%f')[:-3],
+                            kline[7], kline[8], kline[9], kline[10], kline[11]
+                        ]
+                        writer.writerow(row)
+            
+            logging.info(f"Added {len(missing_klines)} missing candles to {csv_filename}")
+            existing_data.extend(missing_klines)
+        
+        return existing_data
+        
+    except Exception as e:
+        logging.error(f"Error filling missing data for {csv_filename}: {e}")
+        return existing_data if 'existing_data' in locals() else []
+
+# --- Historical Data Streaming ---
+def stream_historical_data(sid):
+    """
+    Loads historical data from the selected CSV file and sends it to the client.
+    """
+    global selected_csv_file
+    
+    try:
+        logging.info(f"Starting historical data stream for SID={sid}")
+        
+        # Get selected CSV file or default
+        if not selected_csv_file:
+            selected_csv_file = get_default_csv_file()
+        
+        if not selected_csv_file:
+            # No CSV files available, create a default one
+            logging.warning("No CSV files available, creating default file")
+            selected_csv_file = f"ETHUSDT_{datetime.now().strftime('%Y%m%d')}.csv"
+            
+        logging.info(f"Using CSV file: {selected_csv_file}")
+        
+        # Fill missing data and get all klines
+        all_klines = fill_missing_data(selected_csv_file)
+        
+        # Send progress update
+        socketio.emit('history_progress', {'progress': 100}, to=sid)
+        
+        logging.info(f"Finished data stream for SID={sid}. Sending final payload of {len(all_klines)} klines.")
+        socketio.emit('history_finished', {'klines_1m': all_klines}, to=sid)
+        
+    except Exception as e:
+        logging.error(f"Error in stream_historical_data for SID={sid}: {e}", exc_info=True)
+        socketio.emit('history_error', {'message': str(e)}, to=sid)
 
 # --- Real-time Data Listener ---
 def binance_listener_thread():
+    """
+    Connects to Binance, manages the 1-minute candle, and emits updates.
+    """
+    global current_bar
     async def listener():
+        global current_bar
         while True:
             try:
                 logging.info(f"Connecting to Binance WebSocket at {BINANCE_WS_URL}...")
@@ -171,7 +322,31 @@ def binance_listener_thread():
                     logging.info("Binance WebSocket connected successfully.")
                     while True:
                         message = await websocket.recv()
-                        socketio.emit('trade', json.loads(message))
+                        trade = json.loads(message)
+                        
+                        price = float(trade['p'])
+                        trade_time_s = trade['T'] // 1000
+                        candle_timestamp = trade_time_s - (trade_time_s % 60)
+
+                        if not current_bar or candle_timestamp > current_bar.get("time", 0):
+                            if current_bar:
+                                # The previous candle is now closed, emit it and save to CSV
+                                logging.info(f"Candle closed at {current_bar['close']}. Emitting 'candle_closed' event.")
+                                socketio.emit('candle_closed', current_bar)
+                                
+                                # Append to selected CSV file
+                                if selected_csv_file:
+                                    append_to_csv(selected_csv_file, current_bar)
+                            
+                            current_bar = {"time": candle_timestamp, "open": price, "high": price, "low": price, "close": price}
+                        else:
+                            current_bar['high'] = max(current_bar.get('high', price), price)
+                            current_bar['low'] = min(current_bar.get('low', price), price)
+                            current_bar['close'] = price
+                        
+                        # Emit the live, updating candle for visual feedback
+                        socketio.emit('candle_update', current_bar)
+
             except Exception as e:
                 logging.error(f"Binance listener error: {e}. Reconnecting...")
                 await asyncio.sleep(RESTART_TIMEOUT_S)
@@ -183,32 +358,46 @@ def binance_listener_thread():
 def handle_connect():
     global app_initialized
     logging.info(f"Client connected: IP={request.remote_addr}, SID={request.sid}")
-    
     with app_init_lock:
         if not app_initialized:
-            logging.info("--- First client connected, initializing application data ---")
+            logging.info("--- Initializing Application ---")
-            socketio.start_background_task(load_and_update_data)
             socketio.start_background_task(binance_listener_thread)
             app_initialized = True
+    socketio.start_background_task(target=stream_historical_data, sid=request.sid)
 
-    # Wait until the cache is populated.
+@socketio.on('get_csv_files')
-    while not historical_data_cache:
+def handle_get_csv_files():
-        logging.info(f"SID={request.sid} is waiting for historical data cache...")
+    """Send available CSV files to client."""
-        socketio.sleep(1)
+    logging.info(f"Received get_csv_files request from SID={request.sid}")
+    csv_files = get_available_csv_files()
+    default_file = get_default_csv_file()
+    logging.info(f"Sending CSV files list: {len(csv_files)} files, default: {default_file}")
+    socketio.emit('csv_files_list', {
+        'files': csv_files,
+        'selected': default_file
+    })
 
-    logging.info(f"Sending {len(historical_data_cache)} cached klines to SID={request.sid}")
+@socketio.on('select_csv_file')
-    socketio.emit('history_finished', {'klines_1m': historical_data_cache}, to=request.sid)
+def handle_select_csv_file(data):
+    """Handle CSV file selection by user."""
+    global selected_csv_file
     
+    logging.info(f"Received select_csv_file request from SID={request.sid} with data: {data}")
+    filename = data.get('filename')
+    if filename:
+        csv_files = get_available_csv_files()
+        valid_files = [f['filename'] for f in csv_files]
         
-@socketio.on('analyze_chart')
+        if filename in valid_files:
-def handle_analyze_chart(data):
+            selected_csv_file = filename
-    sid = request.sid
+            save_user_preference(filename)
-    logging.info(f"Received 'analyze_chart' request from frontend (SID={sid})")
+            logging.info(f"User selected CSV file: {filename}")
-    recent_data = data[-100:]
-    prompt_data = "\n".join([f"Time: {c['time']}, Open: {c['open']}, High: {c['high']}, Low: {c['low']}, Close: {c['close']}" for c in recent_data])
-    prompt = (f"You are a financial analyst. Based on the following recent candlestick data for {SYMBOL}, provide a brief technical analysis (3-4 sentences). Mention the current trend and any potential short-term support or resistance levels.\n\nData:\n{prompt_data}")
-    socketio.emit('analysis_result', {'analysis': "AI analysis is currently unavailable."}, to=sid)
             
+            # Stream new historical data
+            socketio.start_background_task(target=stream_historical_data, sid=request.sid)
+        else:
+            logging.error(f"Invalid CSV file selected: {filename}")
+            socketio.emit('error', {'message': f'Invalid CSV file: {filename}'})
 
 # --- Flask Routes ---
 @app.route('/')

data/data_miner.py

@@ -0,0 +1,102 @@
+import csv
+from datetime import datetime
+
+def filter_csv_by_date(input_file, output_file, start_date_str):
+    """
+    Reads a large CSV file line by line, filters by a start date,
+    and writes the results to a new file.
+
+    Args:
+        input_file (str): Path to the large input CSV.
+        output_file (str): Path to the output CSV file.
+        start_date_str (str): The start date in 'YYYY-MM-DD' format.
+    """
+    try:
+        # Convert the start date string into a datetime object for comparison
+        start_date = datetime.strptime(start_date_str, '%Y-%m-%d')
+        print(f"Filtering for dates on or after {start_date_str}...")
+        print(f"Output will be saved to: {output_file}")
+
+
+        # Open the input and output files
+        with open(input_file, 'r', newline='') as infile, \
+             open(output_file, 'w', newline='') as outfile:
+
+            reader = csv.reader(infile)
+            writer = csv.writer(outfile)
+
+            # 1. Read and write the header
+            header = next(reader)
+            writer.writerow(header)
+
+            # Find the index of the 'Open time' column
+            try:
+                date_column_index = header.index('Open time')
+            except ValueError:
+                print("Error: 'Open time' column not found in the header.")
+                return
+
+            # 2. Process the rest of the file line by line
+            processed_lines = 0
+            written_lines = 0
+            for row in reader:
+                processed_lines += 1
+
+                # Avoid errors from empty or malformed rows
+                if not row:
+                    continue
+
+                try:
+                    # Get the date string from the correct column
+                    row_date_str = row[date_column_index]
+                    # Convert the row's date string to a datetime object
+                    row_date = datetime.strptime(row_date_str, '%Y-%m-%d %H:%M:%S')
+
+                    # 3. Compare dates and write to new file if it's a match
+                    if row_date >= start_date:
+                        writer.writerow(row)
+                        written_lines += 1
+
+                except (ValueError, IndexError) as e:
+                    # This will catch errors if a date is in the wrong format
+                    # or if a row doesn't have enough columns.
+                    print(f"Skipping malformed row {processed_lines + 1}: {row}. Error: {e}")
+                    continue
+                
+                # Optional: Print progress for very long operations
+                if processed_lines % 5000000 == 0:
+                    print(f"Processed {processed_lines:,} lines...")
+
+        print("\n--- Processing Complete ---")
+        print(f"Total lines processed: {processed_lines:,}")
+        print(f"Total lines written: {written_lines:,}")
+        print(f"Filtered data saved to: {output_file}")
+
+    except FileNotFoundError:
+        print(f"Error: The file '{input_file}' was not found.")
+    except Exception as e:
+        print(f"An unexpected error occurred: {e}")
+
+# --- Configuration ---
+# 1. Replace with the name of your large input file
+input_filename = 'ETHUSDT_1m_Binance.csv' 
+
+# 2. Provide the start date in YYYY-MM-DD format
+start_date_filter = '2025-07-01' # <-- REPLACE THIS
+
+# 3. The output filename is generated automatically in the requested format
+if start_date_filter != 'YYYY-MM-DD':
+    # This line removes the hyphens for the filename
+    filename_date_part = start_date_filter.replace('-', '')
+    output_filename = f'ETHUSDT_{filename_date_part}.csv'
+else:
+    output_filename = 'ETHUSDT_unfiltered.csv'
+
+
+# --- Run the script ---
+if start_date_filter == 'YYYY-MM-DD':
+    print("Please update the 'start_date_filter' variable in the script with a date like '2025-07-01'.")
+else:
+    filter_csv_by_date(input_filename, output_filename, start_date_filter)
+    
+    

static/candle-aggregator.js

@@ -17,8 +17,19 @@ function aggregateCandles(data, intervalMinutes) {
         let currentAggCandle = null;
     
         data.forEach(candle => {
+            // Validate candle data
+            if (!candle || !candle.time || 
+                isNaN(candle.open) || isNaN(candle.high) || 
+                isNaN(candle.low) || isNaN(candle.close) ||
+                candle.open <= 0 || candle.high <= 0 || 
+                candle.low <= 0 || candle.close <= 0) {
+                console.warn('Skipping invalid candle during aggregation:', candle);
+                return; // Skip this candle
+            }
+    
             // Calculate the timestamp for the start of the interval bucket
-        const bucketTimestamp = candle.time - (candle.time % intervalSeconds);
+            // Properly align to interval boundaries (e.g., 5-min intervals start at :00, :05, :10, etc.)
+            const bucketTimestamp = Math.floor(candle.time / intervalSeconds) * intervalSeconds;
     
             if (!currentAggCandle || bucketTimestamp !== currentAggCandle.time) {
                 // If a previous aggregated candle exists, push it to the results
@@ -48,3 +59,4 @@ function aggregateCandles(data, intervalMinutes) {
     
         return aggregated;
     }
+    

static/hurst.js

@@ -0,0 +1,223 @@
+/**
+ * Indicator Definition Object for Hurst Bands (Multi-Timeframe).
+ * This object is used by the indicator manager to create and control the indicator.
+ * It defines the parameters and the calculation functions.
+ */
+const HURST_INDICATOR = {
+    name: 'Hurst',
+    label: 'Hurst Bands (Multi-TF)',
+    params: [
+        { name: 'cycle', type: 'number', defaultValue: 30, min: 2 },
+        { name: 'timeframe_mult', type: 'number', defaultValue: 5, min: 2, step: 1 },
+    ],
+    // The output is { topBand, bottomBand, topBand_h, bottomBand_h }
+    calculateFull: calculateFullHurst,
+    createRealtime: createRealtimeHurstCalculator,
+};
+
+// --- Helper Functions (private to this file) ---
+
+/**
+ * Aggregates candle data into a higher timeframe.
+ * @param {Array<Object>} data - The original candle data.
+ * @param {number} multiplier - The timeframe multiplier (e.g., 5 for 5-minute candles from 1-minute data).
+ * @returns {Array<Object>} A new array of aggregated candle objects.
+ */
+function _aggregateCandles(data, multiplier) {
+    if (multiplier <= 1) return data;
+
+    const aggregatedData = [];
+    for (let i = 0; i < data.length; i += multiplier) {
+        const chunk = data.slice(i, i + multiplier);
+        if (chunk.length > 0) {
+            const newCandle = {
+                open: chunk[0].open,
+                high: Math.max(...chunk.map(c => c.high)),
+                low: Math.min(...chunk.map(c => c.low)),
+                close: chunk[chunk.length - 1].close,
+                // The timestamp of the new candle corresponds to the end of the period.
+                time: chunk[chunk.length - 1].time,
+            };
+            aggregatedData.push(newCandle);
+        }
+    }
+    return aggregatedData;
+}
+
+
+/**
+ * Calculates RMA (Relative Moving Average), a type of EMA.
+ * @param {number[]} series - An array of numbers.
+ * @param {number} period - The smoothing period.
+ * @returns {number[]} The calculated RMA series.
+ */
+function _calculateRMA(series, period) {
+    if (series.length < period) return [];
+    const alpha = 1 / period;
+    let rma = [];
+    let sum = 0;
+    for (let i = 0; i < period; i++) {
+        sum += series[i];
+    }
+    rma.push(sum / period);
+    for (let i = period; i < series.length; i++) {
+        const val = alpha * series[i] + (1 - alpha) * rma[rma.length - 1];
+        rma.push(val);
+    }
+    return rma;
+}
+
+/**
+ * Calculates ATR (Average True Range).
+ * @param {Array<Object>} data - The full candle data.
+ * @param {number} period - The ATR period.
+ * @returns {number[]} The calculated ATR series.
+ */
+function _calculateATR(data, period) {
+    if (data.length < period) return [];
+    let tr_series = [data[0].high - data[0].low];
+    for (let i = 1; i < data.length; i++) {
+        const h = data[i].high;
+        const l = data[i].low;
+        const prev_c = data[i - 1].close;
+        const tr = Math.max(h - l, Math.abs(h - prev_c), Math.abs(l - prev_c));
+        tr_series.push(tr);
+    }
+    return _calculateRMA(tr_series, period);
+}
+
+/**
+ * A generic function to calculate a single set of Hurst Bands.
+ * This is the core calculation logic.
+ * @param {Array<Object>} data - An array of candle objects for a specific timeframe.
+ * @param {number} cycle - The cycle length for this calculation.
+ * @param {number} atr_mult - The ATR multiplier for this calculation.
+ * @returns {Object} An object containing two arrays: { topBand: [...], bottomBand: [...] }.
+ */
+function _calculateSingleBandSet(data, cycle, atr_mult) {
+    const mcl = Math.floor(cycle / 2);
+    const mcl_2 = Math.floor(mcl / 2);
+
+    if (data.length < cycle + mcl_2) {
+        return { topBand: [], bottomBand: [] };
+    }
+    
+    const closePrices = data.map(d => d.close);
+    const ma_mcl_full = _calculateRMA(closePrices, mcl);
+    const atr_full = _calculateATR(data, mcl);
+
+    const topBand = [];
+    const bottomBand = [];
+    const startIndex = mcl - 1 + mcl_2;
+
+    for (let i = startIndex; i < data.length; i++) {
+        const rma_atr_base_index = i - (mcl - 1);
+        const center_ma_index = rma_atr_base_index - mcl_2;
+        
+        if (center_ma_index >= 0 && rma_atr_base_index >= 0) {
+            const center = ma_mcl_full[center_ma_index];
+            const offset = atr_full[rma_atr_base_index] * atr_mult;
+
+            if (center !== undefined && offset !== undefined) {
+                topBand.push({ time: data[i].time, value: center + offset });
+                bottomBand.push({ time: data[i].time, value: center - offset });
+            }
+        }
+    }
+    return { topBand, bottomBand };
+}
+
+// --- Main Calculation Functions ---
+
+/**
+ * Calculates both primary and higher-timeframe Hurst Bands for an entire dataset.
+ * @param {Array<Object>} data - An array of candle objects.
+ * @param {Object} params - An object with { cycle, timeframe_mult }.
+ * @returns {Object} An object containing four arrays: { topBand, bottomBand, topBand_h, bottomBand_h }.
+ */
+function calculateFullHurst(data, params) {
+    const { cycle, timeframe_mult } = params;
+
+    // 1. Calculate Primary Bands (e.g., 1-minute)
+    const primaryBands = _calculateSingleBandSet(data, cycle, 1.8);
+
+    // 2. Aggregate candles to higher timeframe (e.g., 5-minute)
+    const higherTfData = _aggregateCandles(data, timeframe_mult);
+
+    // 3. Calculate Higher Timeframe Bands
+    const higherTFBandsRaw = _calculateSingleBandSet(higherTfData, cycle, 1.9);
+
+    // 4. Align higher timeframe results back to the primary timeframe for plotting
+    const higherTfResults = new Map(higherTFBandsRaw.topBand.map((p, i) => [
+        p.time,
+        { top: p.value, bottom: higherTFBandsRaw.bottomBand[i].value }
+    ]));
+    
+    const topBand_h = [];
+    const bottomBand_h = [];
+    let lastKnownTop = null;
+    let lastKnownBottom = null;
+
+    for (const candle of data) {
+        if (higherTfResults.has(candle.time)) {
+            const bands = higherTfResults.get(candle.time);
+            lastKnownTop = bands.top;
+            lastKnownBottom = bands.bottom;
+        }
+        // Carry forward the last known value until a new one is calculated
+        if (lastKnownTop !== null) {
+            topBand_h.push({ time: candle.time, value: lastKnownTop });
+            bottomBand_h.push({ time: candle.time, value: lastKnownBottom });
+        }
+    }
+
+    return {
+        topBand: primaryBands.topBand,
+        bottomBand: primaryBands.bottomBand,
+        topBand_h,
+        bottomBand_h,
+    };
+}
+
+/**
+ * Creates a stateful Hurst calculator for real-time updates.
+ * @param {Object} params - An object with { cycle, timeframe_mult }.
+ * @returns {Object} A calculator object with `update` and `prime` methods.
+ */
+function createRealtimeHurstCalculator(params) {
+    const { cycle, timeframe_mult } = params;
+    // Buffer needs to be large enough to contain enough aggregated candles for a valid calculation.
+    const minHigherTfCandles = cycle + Math.floor(Math.floor(cycle / 2) / 2);
+    const bufferSize = minHigherTfCandles * timeframe_mult * 2; // Use a safe buffer size
+    let buffer = [];
+
+    return {
+        update: function(candle) {
+            buffer.push(candle);
+            if (buffer.length > bufferSize) {
+                buffer.shift();
+            }
+            
+            // Check if there's enough data for at least one calculation on the higher timeframe.
+            const requiredLength = minHigherTfCandles * timeframe_mult;
+            if (buffer.length < requiredLength) {
+                return null;
+            }
+
+            const result = calculateFullHurst(buffer, params);
+            
+            if (result.topBand.length > 0 && result.topBand_h.length > 0) {
+                return { 
+                    topBand: result.topBand[result.topBand.length - 1], 
+                    bottomBand: result.bottomBand[result.bottomBand.length - 1],
+                    topBand_h: result.topBand_h[result.topBand_h.length - 1],
+                    bottomBand_h: result.bottomBand_h[result.bottomBand_h.length - 1],
+                };
+            }
+            return null;
+        },
+        prime: function(historicalCandles) {
+            buffer = historicalCandles.slice(-bufferSize);
+        }
+    };
+}

static/indicator-manager.js

@@ -1,32 +1,32 @@
 /**
  * Creates and manages all indicator-related logic for the chart.
  * @param {Object} chart - The Lightweight Charts instance.
- * @param {Array<Object>} baseCandleData - A reference to the array holding the chart's BASE 1m candle data.
+ * @param {Array<Object>} baseCandleDataRef - A reference to the array holding the chart's BASE 1m candle data.
+ * @param {Array<Object>} displayedCandleDataRef - A reference to the array with currently visible candles.
  * @returns {Object} A manager object with public methods to control indicators.
  */
-function createIndicatorManager(chart, baseCandleData) {
+function createIndicatorManager(chart, baseCandleDataRef, displayedCandleDataRef) {
-    // This holds the candle data currently displayed on the chart (e.g., 5m, 10m)
+    // --- FIX: --- Added `debounceTimerId` to each slot object to track pending updates.
-    let currentAggregatedData = [];
-
-    // Defines the 4 slots available in the UI for indicators.
     const indicatorSlots = [
-        { id: 1, cellId: 'indicator-cell-1', series: [], definition: null, params: {} },
+        { id: 1, cellId: 'indicator-cell-1', series: [], definition: null, params: {}, calculator: null, debounceTimerId: null },
-        { id: 2, cellId: 'indicator-cell-2', series: [], definition: null, params: {} },
+        { id: 2, cellId: 'indicator-cell-2', series: [], definition: null, params: {}, calculator: null, debounceTimerId: null },
-        { id: 3, cellId: 'indicator-cell-3', series: [], definition: null, params: {} },
+        { id: 3, cellId: 'indicator-cell-3', series: [], definition: null, params: {}, calculator: null, debounceTimerId: null },
-        { id: 4, cellId: 'indicator-cell-4', series: [], definition: null, params: {} },
+        { id: 4, cellId: 'indicator-cell-4', series: [], definition: null, params: {}, calculator: null, debounceTimerId: null },
     ];
 
-    // Pre-defined colors for the indicator lines.
     const colors = {
-        bb1: { upper: '#FF9800', lower: '#FF9800' }, // Orange
+        bb: {
-        bb2: { upper: '#2196F3', lower: '#2196F3' }, // Blue
+            bb1_upper: 'rgba(128, 25, 34, 0.5)',
-        bb3: { upper: '#9C27B0', lower: '#9C27B0' }, // Purple
+            bb2_upper: 'rgba(128, 25, 34, 0.75)',
-        default: ['#FF5722', '#03A9F4', '#8BC34A', '#F44336'] // Fallback colors for other indicators
+            bb3_upper: 'rgba(128, 25, 34, 1)',
+            bb1_lower: 'rgba(6, 95, 6, 0.5)',
+            bb2_lower: 'rgba(6, 95, 6, 0.75)',
+            bb3_lower: 'rgba(6, 95, 6, 1.0)',
+        },
+        hurst: { topBand: '#787b86', bottomBand: '#787b86', topBand_h: '#673ab7', bottomBand_h: '#673ab7' },
+        default: ['#00BCD4', '#FFEB3B', '#4CAF50', '#E91E63']
     };
 
-    /**
-     * Populates the dropdown menus in each indicator cell.
-     */
     function populateDropdowns() {
         indicatorSlots.forEach(slot => {
             const cell = document.getElementById(slot.cellId);
@@ -41,32 +41,30 @@ function createIndicatorManager(chart, baseCandleData) {
             const controlsContainer = document.createElement('div');
             controlsContainer.className = 'indicator-controls';
 
-            cell.innerHTML = ''; // Clear previous content
+            cell.innerHTML = '';
             cell.appendChild(select);
             cell.appendChild(controlsContainer);
 
-            select.addEventListener('change', (e) => {
+            select.addEventListener('change', (e) => loadIndicator(slot.id, e.target.value));
-                const indicatorName = e.target.value;
-                loadIndicator(slot.id, indicatorName);
-            });
         });
     }
 
-    /**
-     * Loads a new indicator into a specified slot.
-     * @param {number} slotId - The ID of the slot (1-4).
-     * @param {string} indicatorName - The name of the indicator to load (e.g., 'SMA').
-     */
     function loadIndicator(slotId, indicatorName) {
         const slot = indicatorSlots.find(s => s.id === slotId);
         if (!slot) return;
 
-        // Clean up any previous indicator series in this slot
+        // --- FIX: --- Cancel any pending debounced update from the previous indicator's controls.
+        // This is the core of the fix, preventing the race condition.
+        if (slot.debounceTimerId) {
+            clearTimeout(slot.debounceTimerId);
+            slot.debounceTimerId = null;
+        }
+
         slot.series.forEach(s => chart.removeSeries(s));
         slot.series = [];
-        
         slot.definition = null;
         slot.params = {};
+        slot.calculator = null;
 
         const controlsContainer = document.querySelector(`#${slot.cellId} .indicator-controls`);
         controlsContainer.innerHTML = '';
@@ -78,7 +76,6 @@ function createIndicatorManager(chart, baseCandleData) {
 
         slot.definition = definition;
 
-        // Create UI controls for the indicator's parameters
         definition.params.forEach(param => {
             const label = document.createElement('label');
             label.textContent = param.label || param.name;
@@ -90,15 +87,15 @@ function createIndicatorManager(chart, baseCandleData) {
             if (param.min !== undefined) input.min = param.min;
             if (param.step !== undefined) input.step = param.step;
             input.className = 'input-field';
-            input.placeholder = param.name;
             slot.params[param.name] = input.type === 'number' ? parseFloat(input.value) : input.value;
 
-            let debounceTimer;
             input.addEventListener('input', () => {
-                clearTimeout(debounceTimer);
+                // --- FIX: --- Use the slot's `debounceTimerId` property to manage the timeout.
-                debounceTimer = setTimeout(() => {
+                clearTimeout(slot.debounceTimerId);
+                slot.debounceTimerId = setTimeout(() => {
                     slot.params[param.name] = input.type === 'number' ? parseFloat(input.value) : input.value;
-                    updateIndicator(slot.id);
+                    updateIndicator(slot.id, true);
+                    slot.debounceTimerId = null; // Clear the ID after the function has run.
                 }, 500);
             });
             const controlGroup = document.createElement('div');
@@ -109,91 +106,110 @@ function createIndicatorManager(chart, baseCandleData) {
             controlsContainer.appendChild(controlGroup);
         });
 
-        updateIndicator(slot.id);
+        updateIndicator(slot.id, true);
     }
 
-    /**
+    function updateIndicator(slotId, isFullRecalculation = false) {
-     * Recalculates and redraws the lines for a specific indicator.
-     * @param {number} slotId - The ID of the slot to update.
-     */
-    function updateIndicator(slotId) {
         const slot = indicatorSlots.find(s => s.id === slotId);
+        if (!slot || !slot.definition) return;
 
-        const candleDataForCalc = (slot.definition.usesBaseData) ? baseCandleData : currentAggregatedData;
+        const candleDataForCalc = (slot.definition.usesBaseData) ? baseCandleDataRef : displayedCandleDataRef;
+        if (candleDataForCalc.length === 0) return;
 
-        if (!slot || !slot.definition || candleDataForCalc.length === 0) {
-            return;
-        }
 
-        // Clean up previous series before creating new ones
+        if (isFullRecalculation) {
             slot.series.forEach(s => chart.removeSeries(s));
             slot.series = [];
 
-        console.log(`Recalculating ${slot.definition.name} for slot ${slot.id} on ${candleDataForCalc.length} candles.`);
-        
             const indicatorResult = slot.definition.calculateFull(candleDataForCalc, slot.params);
 
-        // Handle multi-line indicators like Bollinger Bands
             if (typeof indicatorResult === 'object' && !Array.isArray(indicatorResult)) {
                 Object.keys(indicatorResult).forEach(key => {
                     const seriesData = indicatorResult[key];
-                const bandName = key.split('_')[0]; 
+                    const indicatorNameLower = slot.definition.name.toLowerCase();
-                const bandType = key.split('_')[1]; 
-                
                     const series = chart.addLineSeries({
-                    color: colors[bandName] ? colors[bandName][bandType] : colors.default[slot.id - 1],
+                        color: (colors[indicatorNameLower] && colors[indicatorNameLower][key]) ? colors[indicatorNameLower][key] : colors.default[slot.id - 1],
-                    lineWidth: 2,
+                        lineWidth: 1,
-                    title: `${slot.definition.label} - ${key}`,
+                        title: '',
                         lastValueVisible: false,
                         priceLineVisible: false,
                     });
                     series.setData(seriesData);
                     slot.series.push(series);
                 });
-        } else { // Handle single-line indicators like SMA/EMA
+            } else {
                 const series = chart.addLineSeries({
                     color: colors.default[slot.id - 1],
-                lineWidth: 2,
+                    lineWidth: 1,
-                title: slot.definition.label,
+                    title: '',
+                    lastValueVisible: false,
+                    priceLineVisible: false,
                 });
                 series.setData(indicatorResult);
                 slot.series.push(series);
             }
+
+            if (slot.definition.createRealtime) {
+                slot.calculator = slot.definition.createRealtime(slot.params);
+                slot.calculator.prime(candleDataForCalc);
+            }
+        } else if (slot.calculator) {
+            const lastCandle = candleDataForCalc[candleDataForCalc.length - 1];
+            if (!lastCandle) return;
+
+            const newPoint = slot.calculator.update(lastCandle);
+
+            if (newPoint && typeof newPoint === 'object') {
+                if (slot.series.length > 1) { // Multi-line indicator
+                    Object.keys(newPoint).forEach((key, index) => {
+                        if (slot.series[index] && newPoint[key]) {
+                            slot.series[index].update(newPoint[key]);
+                        }
+                    });
+                } else if (slot.series.length === 1) { // Single-line indicator
+                    slot.series[0].update(newPoint);
+                }
+            }
+        }
     }
 
-    /**
+    function recalculateAllAfterHistory(baseData, displayedData) {
-     * Internal function to recalculate all active indicators.
+        baseCandleDataRef = baseData;
-     */
+        displayedCandleDataRef = displayedData;
-    function recalculateAllIndicators() {
+
+        // --- FIX: --- Clear any pending debounced updates from parameter changes.
+        // This prevents a stale update from a parameter input from running after 
+        // the chart has already been reset for a new timeframe.
+        indicatorSlots.forEach(slot => {
+            if (slot.debounceTimerId) {
+                clearTimeout(slot.debounceTimerId);
+                slot.debounceTimerId = null;
+            }
+        });
+
+        // --- FIX: --- Defer the full recalculation to the next frame.
+        // This prevents a race condition where indicators are removed/added while the chart
+        // is still processing the main series' `setData` operation from a timeframe change.
+        setTimeout(() => {
             indicatorSlots.forEach(slot => {
                 if (slot.definition) {
-                updateIndicator(slot.id);
+                    updateIndicator(slot.id, true);
+                }
+            });
+        }, 0);
+    }
+
+    function updateAllOnNewCandle() {
+        indicatorSlots.forEach(slot => {
+            if (slot.definition) {
+                updateIndicator(slot.id, false);
             }
         });
     }
 
-    /**
-     * Sets the candle data for indicators and triggers a full recalculation.
-     * @param {Array<Object>} aggregatedCandleData - The candle data for the currently selected timeframe.
-     */
-    function recalculateAllAfterHistory(aggregatedCandleData) {
-         currentAggregatedData = aggregatedCandleData;
-         recalculateAllIndicators();
-    }
-
-    /**
-     * Updates all indicators in response to a new candle closing.
-     * @param {Array<Object>} aggregatedCandleData - The latest candle data for the currently selected timeframe.
-     */
-    function updateIndicatorsOnNewCandle(aggregatedCandleData) {
-        currentAggregatedData = aggregatedCandleData;
-        recalculateAllIndicators();
-    }
-
-    // Public API for the manager
     return {
         populateDropdowns,
         recalculateAllAfterHistory,
-        updateIndicatorsOnNewCandle
+        updateAllOnNewCandle,
     };
 }

static/indicators.js

@@ -9,5 +9,6 @@ const AVAILABLE_INDICATORS = [
     SMA_INDICATOR,
     EMA_INDICATOR,
     BB_INDICATOR, // Added the new Bollinger Bands indicator
-    // Add other indicators here, e.g., RSI_INDICATOR
+    HURST_INDICATOR // Added the new Hurst Bands indicator
+    // Add other indicators here as needed
 ];

templates/index.html

@@ -5,11 +5,13 @@
     <script src="https://unpkg.com/lightweight-charts@4.1.3/dist/lightweight-charts.standalone.production.js"></script>
     <script src="https://cdn.socket.io/4.7.5/socket.io.min.js"></script>
     
-    <!-- Indicator & Aggregation Scripts -->
+    <!-- NOTE: These 'url_for' will not work in a static HTML file. -->
+    <!-- They are placeholders for a Flask environment. For a standalone file, you would link directly to the JS files. -->
     <script src="{{ url_for('static', filename='candle-aggregator.js') }}"></script>
     <script src="{{ url_for('static', filename='sma.js') }}"></script>
     <script src="{{ url_for('static', filename='ema.js') }}"></script>
     <script src="{{ url_for('static',filename='bb.js') }}"></script>
+    <script src="{{ url_for('static', filename='hurst.js') }}"></script>
     <script src="{{ url_for('static', filename='indicators.js') }}"></script>
     <script src="{{ url_for('static', filename='indicator-manager.js') }}"></script>
 
@@ -18,6 +20,13 @@
             --background-dark: #161A25; --container-dark: #1E222D; --border-color: #2A2E39;
             --text-primary: #D1D4DC; --text-secondary: #8A91A0; --button-bg: #363A45;
             --button-hover-bg: #434651; --accent-orange: #F0B90B; --green: #26a69a; --red: #ef5350;
+            
+            /* Colors for measure tool */
+            --measure-tool-up-bg: rgba(41, 98, 255, 0.2);
+            --measure-tool-up-border: #2962FF;
+            --measure-tool-down-bg: rgba(239, 83, 80, 0.2);
+            --measure-tool-down-border: #ef5350;
+            --measure-tool-text: #FFFFFF;
         }
         body {
             background-color: var(--background-dark); color: var(--text-primary);
@@ -29,7 +38,8 @@
             border-bottom: 1px solid var(--border-color); margin-bottom: 20px;
         }
         .header h1 { margin: 0; font-size: 24px; }
-        #chart { width: 90%; max-width: 1400px; height: 500px; }
+        #chart-wrapper { position: relative; width: 90%; max-width: 1400px; height: 500px; }
+        #chart { width: 100%; height: 100%; }
         .control-panel {
             display: grid; grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
             gap: 15px; width: 90%; max-width: 1400px; padding: 20px 0;
@@ -47,20 +57,55 @@
             border-radius: 5px; cursor: pointer; transition: background-color 0.3s, color 0.3s;
         }
         .action-button:hover, .control-cell select:hover { background-color: var(--button-hover-bg); }
-        #analyzeButton:hover { color: var(--accent-orange); }
         .input-field { width: 60px; }
-        .analysis-section {
-            width: 90%; max-width: 1400px; background-color: var(--container-dark);
-            border: 1px solid var(--border-color); border-radius: 8px; padding: 20px;
-            margin-top: 10px; text-align: center;
-        }
-        #analysisResult {
-            margin-top: 15px; font-size: 0.95rem; line-height: 1.6; text-align: left;
-            white-space: pre-wrap; color: var(--text-primary); background-color: var(--background-dark);
-            padding: 15px; border-radius: 5px; min-height: 50px;
-        }
         #candle-timer { font-size: 2rem; font-weight: 500; color: var(--accent-orange); }
-        #timeframe-select { margin-top: 10px; }
+        #timeframe-display { margin-top: 10px; min-width: 60px; }
+        .progress-bar-container {
+            width: 80%; height: 4px; background-color: var(--button-bg);
+            border-radius: 2px; margin-top: 10px; overflow: hidden;
+        }
+        .progress-bar {
+            width: 0%; height: 100%; background-color: var(--green);
+            transition: width 0.4s ease-out;
+        }
+
+        /* --- Styles for Measure Tool --- */
+        #measure-tool {
+            position: absolute; top: 0; left: 0; width: 100%; height: 100%;
+            pointer-events: none; overflow: hidden; z-index: 10;
+        }
+        #measure-box { position: absolute; }
+        #measure-svg { position: absolute; width: 100%; height: 100%; top: 0; left: 0; }
+        #measure-tooltip {
+            position: absolute; color: var(--measure-tool-text); padding: 4px 8px;
+            border-radius: 4px; font-size: 11px; line-height: 1.2;
+            display: flex; flex-direction: column; align-items: center; justify-content: center;
+        }
+
+        /* --- Styles for Timeframe Modal --- */
+        .modal-overlay {
+            position: fixed; top: 0; left: 0; width: 100%; height: 100%;
+            background-color: rgba(0, 0, 0, 0.7);
+            display: none; /* Hidden by default */
+            justify-content: center; align-items: center; z-index: 1000;
+        }
+        .modal {
+            background-color: var(--container-dark); padding: 25px; border-radius: 8px;
+            border: 1px solid var(--border-color); text-align: center;
+            width: 300px; box-shadow: 0 5px 15px rgba(0,0,0,0.3);
+        }
+        .modal h2 {
+            margin-top: 0; margin-bottom: 20px; font-size: 18px; color: var(--text-primary);
+        }
+        .modal .input-field {
+            width: 100%; box-sizing: border-box; font-size: 24px;
+            padding: 10px; margin-bottom: 10px; text-align: center;
+        }
+        .modal #timeframe-preview-text {
+            color: var(--text-secondary); font-size: 14px; margin-top: 0;
+            margin-bottom: 20px; min-height: 20px;
+        }
+        .modal .action-button { width: 100%; }
     </style>
 </head>
 <body>
@@ -68,24 +113,32 @@
         <h1 id="chart-title">{{ symbol }} Chart</h1>
     </div>
 
+    <div id="chart-wrapper">
         <div id="chart"></div>
+        <div id="measure-tool" style="display: none;">
+            <div id="measure-box"></div>
+            <svg id="measure-svg"></svg>
+            <div id="measure-tooltip"></div>
+        </div>
+    </div>
 
     <div class="control-panel">
         <div class="control-cell">
             <h3>Candle Closes In</h3>
             <div id="candle-timer">--:--</div>
-            <select id="timeframe-select">
+            <div id="timeframe-display" class="action-button">1m</div>
-                <option value="1">1m</option>
+            <div id="progress-container" class="progress-bar-container">
-                <option value="2">2m</option>
+                <div class="progress-bar"></div>
-                <option value="3">3m</option>
+            </div>
-                <option value="4">4m</option>
+            
-                <option value="5">5m</option>
+            <!-- CSV File Selection Dropdown -->
-                <option value="6">6m</option>
+            <div style="margin-top: 15px; width: 100%;">
-                <option value="7">7m</option>
+                <label for="csv-file-select" style="display: block; margin-bottom: 5px; font-size: 12px; color: var(--text-secondary);">Data Source:</label>
-                <option value="8">8m</option>
+                <select id="csv-file-select" style="width: 100%; background-color: var(--button-bg); border: 1px solid var(--border-color); color: var(--text-primary); padding: 6px; border-radius: 4px; font-size: 12px; cursor: pointer;">
-                <option value="9">9m</option>
+                    <option value="">Loading...</option>
-                <option value="10">10m</option>
                 </select>
+                <div id="csv-info" style="font-size: 10px; color: var(--text-secondary); margin-top: 3px; text-align: center;"></div>
+            </div>
         </div>
         <div class="control-cell" id="indicator-cell-1"></div>
         <div class="control-cell" id="indicator-cell-2"></div>
@@ -93,10 +146,14 @@
         <div class="control-cell" id="indicator-cell-4"></div>
     </div>
 
-    <div class="analysis-section">
+    <!-- Timeframe Modal -->
-        <h3>Analysis ✨</h3>
+    <div id="timeframe-modal-overlay" class="modal-overlay">
-        <button id="analyzeButton" class="action-button">Analyze Recent Price Action</button>
+        <div id="timeframe-modal" class="modal">
-        <div id="analysisResult">Click the button for AI analysis.</div>
+            <h2>Change interval</h2>
+            <input type="number" id="timeframe-input" class="input-field" min="1" placeholder="Enter minutes"/>
+            <p id="timeframe-preview-text"></p>
+            <button id="timeframe-confirm-btn" class="action-button">OK</button>
+        </div>
     </div>
 
     <script>
@@ -106,101 +163,508 @@
                 width: chartElement.clientWidth, height: 500,
                 layout: { background: { type: 'solid', color: '#1E222D' }, textColor: '#D1D4DC' },
                 grid: { vertLines: { color: '#2A2E39' }, horzLines: { color: '#2A2E39' } },
-                timeScale: { timeVisible: true, secondsVisible: true }
+                timeScale: { timeVisible: true, secondsVisible: true },
+                crosshair: {
+                    mode: LightweightCharts.CrosshairMode.Normal,
+                },
             });
             const candlestickSeries = chart.addCandlestickSeries({
-                upColor: '#26a69a', downColor: '#ef5350', borderDownColor: '#ef5350',
+                upColor: 'rgba(255, 152, 0, 1.0)', downColor: 'rgba(255, 152, 0, 0.66)', borderDownColor: 'rgba(255, 152, 0, 0.66)',
-                borderUpColor: '#26a69a', wickDownColor: '#ef5350', wickUpColor: '#26a69a',
+                borderUpColor: 'rgba(255, 152, 0, 1.0)', wickDownColor: 'rgba(255, 152, 0, 0.66)', wickUpColor: 'rgba(255, 152, 0, 1.0)'
             });
 
+            const originalAddLineSeries = chart.addLineSeries;
+            chart.addLineSeries = function(options) {
+                const newOptions = { ...options, crosshairMarkerVisible: false, };
+                return originalAddLineSeries.call(this, newOptions);
+            };
+
             let baseCandleData1m = [];
             let displayedCandleData = [];
-            let currentCandle1m = null;
             let manager;
+            let currentTimeframeMinutes = 1;
 
-            const timeframeSelect = document.getElementById('timeframe-select');
             const candleTimerDiv = document.getElementById('candle-timer');
             const chartTitle = document.getElementById('chart-title');
-            const analyzeButton = document.getElementById('analyzeButton');
+            const progressContainer = document.getElementById('progress-container');
-            const analysisResultDiv = document.getElementById('analysisResult');
+            const progressBar = document.querySelector('.progress-bar');
             
-            manager = createIndicatorManager(chart, baseCandleData1m);
+            const measureToolEl = document.getElementById('measure-tool');
+            const measureBoxEl = document.getElementById('measure-box');
+            const measureSvgEl = document.getElementById('measure-svg');
+            const measureTooltipEl = document.getElementById('measure-tooltip');
+            let measureState = { active: false, finished: false, startPoint: null, endPoint: null };
+            let isRedrawScheduled = false;
+
+            const timeframeDisplay = document.getElementById('timeframe-display');
+            const modalOverlay = document.getElementById('timeframe-modal-overlay');
+            const modalInput = document.getElementById('timeframe-input');
+            const modalPreviewText = document.getElementById('timeframe-preview-text');
+            const modalConfirmBtn = document.getElementById('timeframe-confirm-btn');
+            const csvFileSelect = document.getElementById('csv-file-select');
+            const csvInfoDiv = document.getElementById('csv-info');
+
+            function openModal(initialValue = '') {
+                modalOverlay.style.display = 'flex';
+                modalInput.value = initialValue;
+                updatePreviewText();
+                modalInput.focus();
+                modalInput.select();
+            }
+
+            function closeModal() {
+                modalOverlay.style.display = 'none';
+            }
+
+            function updatePreviewText() {
+                const value = modalInput.value;
+                if (value && parseInt(value) > 0) {
+                    modalPreviewText.textContent = `${value} minute${parseInt(value) > 1 ? 's' : ''}`;
+                } else {
+                    modalPreviewText.textContent = '';
+                }
+            }
+
+            function confirmTimeframe() {
+                const newTimeframe = parseInt(modalInput.value);
+                if (newTimeframe && newTimeframe > 0) {
+                    currentTimeframeMinutes = newTimeframe;
+                    timeframeDisplay.textContent = `${newTimeframe}m`;
+                    updateChartForTimeframe(true);
+                    closeModal();
+                }
+            }
+
+            timeframeDisplay.addEventListener('click', () => openModal(currentTimeframeMinutes));
+            modalConfirmBtn.addEventListener('click', confirmTimeframe);
+            modalInput.addEventListener('input', updatePreviewText);
+            modalInput.addEventListener('keydown', (e) => { if (e.key === 'Enter') confirmTimeframe(); });
+            modalOverlay.addEventListener('click', (e) => { if (e.target === modalOverlay) closeModal(); });
+            window.addEventListener('keydown', (e) => {
+                if (modalOverlay.style.display === 'flex' && e.key === 'Escape') {
+                    closeModal();
+                } 
+                else if (modalOverlay.style.display !== 'flex' && !isNaN(parseInt(e.key)) && !e.ctrlKey && !e.metaKey) {
+                    const activeEl = document.activeElement;
+                    if (activeEl.tagName !== 'INPUT' && activeEl.tagName !== 'TEXTAREA') {
+                        e.preventDefault();
+                        openModal(e.key);
+                    }
+                }
+            });
+
+            manager = createIndicatorManager(chart, baseCandleData1m, displayedCandleData);
             manager.populateDropdowns();
 
             const socket = io();
-            socket.on('connect', () => console.log('Socket.IO connected.'));
+            socket.on('connect', () => {
+                console.log('Socket.IO connected.');
+                // Request available CSV files
+                socket.emit('get_csv_files');
+            });
+
+            socket.on('history_progress', (data) => {
+                if (data && data.progress) progressBar.style.width = `${data.progress}%`;
+            });
+
+            socket.on('csv_files_list', (data) => {
+                console.log('Received CSV files list:', data);
+                populateCsvDropdown(data.files, data.selected);
+            });
+
+            function populateCsvDropdown(files, selectedFile) {
+                csvFileSelect.innerHTML = '';
+                
+                if (files.length === 0) {
+                    const option = document.createElement('option');
+                    option.value = '';
+                    option.textContent = 'No CSV files available';
+                    csvFileSelect.appendChild(option);
+                    csvInfoDiv.textContent = '';
+                    return;
+                }
+                
+                files.forEach(file => {
+                    const option = document.createElement('option');
+                    option.value = file.filename;
+                    option.textContent = file.display_name;
+                    if (file.filename === selectedFile) {
+                        option.selected = true;
+                        // Show info about selected file
+                        const sizeInMB = (file.size / (1024 * 1024)).toFixed(1);
+                        csvInfoDiv.textContent = `${sizeInMB} MB - ${file.filename}`;
+                    }
+                    csvFileSelect.appendChild(option);
+                });
+            }
+
+            csvFileSelect.addEventListener('change', (e) => {
+                const selectedFile = e.target.value;
+                if (selectedFile) {
+                    console.log('User selected CSV file:', selectedFile);
+                    
+                    // Update info display
+                    const selectedOption = e.target.selectedOptions[0];
+                    const files = Array.from(e.target.options).map(option => ({
+                        filename: option.value,
+                        display_name: option.textContent,
+                        size: 0 // Will be updated by server response
+                    }));
+                    
+                    socket.emit('select_csv_file', { filename: selectedFile });
+                    
+                    // Show loading state
+                    progressContainer.style.display = 'block';
+                    progressBar.style.width = '0%';
+                    csvInfoDiv.textContent = 'Loading...';
+                }
+            });
 
             socket.on('history_finished', (data) => {
                 if (!data || !data.klines_1m) return;
-                
+                progressBar.style.width = '100%';
-                const mappedKlines = data.klines_1m.map(k => ({
+                baseCandleData1m = data.klines_1m
-                    time: k[0] / 1000, open: parseFloat(k[1]), high: parseFloat(k[2]),
+                    .map(k => ({
-                    low: parseFloat(k[3]), close: parseFloat(k[4])
+                        time: k[0] / 1000, 
-                }));
+                        open: parseFloat(k[1]), 
-                
+                        high: parseFloat(k[2]),
-                baseCandleData1m.length = 0;
+                        low: parseFloat(k[3]), 
-                for (const kline of mappedKlines) {
+                        close: parseFloat(k[4])
-                    baseCandleData1m.push(kline);
+                    }))
-                }
+                    .filter(candle => {
-
+                        // Filter out invalid candles with null, undefined, or NaN values
-                updateChartForTimeframe();
+                        return candle.time && 
+                               !isNaN(candle.open) && !isNaN(candle.high) && 
+                               !isNaN(candle.low) && !isNaN(candle.close) &&
+                               candle.open > 0 && candle.high > 0 && 
+                               candle.low > 0 && candle.close > 0;
+                    });
+                updateChartForTimeframe(true);
+                setTimeout(() => { progressContainer.style.display = 'none'; }, 500);
             });
 
-            socket.on('trade', (trade) => {
+            // --- MODIFICATION START: Rewritten candle update and creation logic ---
-                const price = parseFloat(trade.p);
+            function handleLiveUpdate(update) {
-                const tradeTime = Math.floor(trade.T / 1000);
+                if (baseCandleData1m.length === 0 || displayedCandleData.length === 0) return;
-                const candleTimestamp1m = tradeTime - (tradeTime % 60);
                 
-                if (!currentCandle1m || candleTimestamp1m > currentCandle1m.time) {
+                // Validate the update data
-                    if (currentCandle1m) baseCandleData1m.push(currentCandle1m);
+                if (!update || !update.time || 
-                    currentCandle1m = { time: candleTimestamp1m, open: price, high: price, low: price, close: price };
+                    isNaN(update.open) || isNaN(update.high) || 
+                    isNaN(update.low) || isNaN(update.close) ||
+                    update.open <= 0 || update.high <= 0 || 
+                    update.low <= 0 || update.close <= 0) {
+                    console.warn('Invalid update data received:', update);
+                    return;
+                }
+
+                // First, ensure the base 1m data is up-to-date.
+                const lastBaseCandle = baseCandleData1m[baseCandleData1m.length - 1];
+                if (update.time > lastBaseCandle.time) {
+                    baseCandleData1m.push(update);
+                } else if (update.time === lastBaseCandle.time) {
+                    baseCandleData1m[baseCandleData1m.length - 1] = update;
+                }
+
+                const candleDurationSeconds = currentTimeframeMinutes * 60;
+                let lastDisplayedCandle = displayedCandleData[displayedCandleData.length - 1];
+
+                // Calculate which bucket this update belongs to using simple division
+                const updateBucketTime = Math.floor(update.time / candleDurationSeconds) * candleDurationSeconds;
+
+                // Check if the update belongs to the currently forming displayed candle
+                if (updateBucketTime === lastDisplayedCandle.time) {
+                    // It does, so just update the High, Low, and Close prices
+                    lastDisplayedCandle.high = Math.max(lastDisplayedCandle.high, update.high);
+                    lastDisplayedCandle.low = Math.min(lastDisplayedCandle.low, update.low);
+                    lastDisplayedCandle.close = update.close;
+                    candlestickSeries.update(lastDisplayedCandle);
+                } else if (updateBucketTime > lastDisplayedCandle.time) {
+                    // This update is for a NEW candle.
+                    // Create the new candle. Its O,H,L,C are all from this first tick.
+                    const newCandle = {
+                        time: updateBucketTime,
+                        open: update.open,
+                        high: update.high,
+                        low: update.low,
+                        close: update.close,
+                    };
+
+                    displayedCandleData.push(newCandle);
+                    candlestickSeries.update(newCandle);
+
+                    // Since a new candle has been formed, we should recalculate indicators
+                    manager.recalculateAllAfterHistory(baseCandleData1m, displayedCandleData);
+                }
+            }
+            
+            let latestCandleUpdate = null;
+            let isUpdateScheduled = false;
+
+            function processLatestUpdate() {
+                if (latestCandleUpdate) {
+                    handleLiveUpdate(latestCandleUpdate);
+                    latestCandleUpdate = null;
+                }
+                isUpdateScheduled = false;
+            }
+
+            socket.on('candle_update', (update) => {
+                latestCandleUpdate = update;
+                if (!isUpdateScheduled) {
+                    isUpdateScheduled = true;
+                    requestAnimationFrame(processLatestUpdate);
+                }
+            });
+
+            socket.on('candle_closed', (closedCandle) => {
+                // This handler's primary job is to ensure data integrity by using the final, closed 1m candle.
+                
+                // 1. Update the master 1-minute data array with the final version of the candle.
+                const candleIndex = baseCandleData1m.findIndex(c => c.time === closedCandle.time);
+                if (candleIndex !== -1) {
+                    baseCandleData1m[candleIndex] = closedCandle;
                 } else {
-                    currentCandle1m.high = Math.max(currentCandle1m.high, price);
+                    // This case might happen if connection was lost and we missed updates for this candle
-                    currentCandle1m.low = Math.min(currentCandle1m.low, price);
+                    baseCandleData1m.push(closedCandle);
-                    currentCandle1m.close = price;
+                    baseCandleData1m.sort((a, b) => a.time - b.time); // Keep it sorted just in case
                 }
                 
-                const selectedInterval = parseInt(timeframeSelect.value, 10) * 60;
+                if (displayedCandleData.length === 0) return;
-                const displayedCandleTimestamp = tradeTime - (tradeTime % selectedInterval);
-                const lastDisplayedCandle = displayedCandleData[displayedCandleData.length - 1];
 
-                let candleForUpdate;
+                // 2. Determine which displayed candle this closed 1m candle belongs to.
-                if (lastDisplayedCandle && displayedCandleTimestamp === lastDisplayedCandle.time) {
+                const candleDurationSeconds = currentTimeframeMinutes * 60;
-                    candleForUpdate = { ...lastDisplayedCandle };
+                const bucketTime = Math.floor(closedCandle.time / candleDurationSeconds) * candleDurationSeconds;
-                    candleForUpdate.high = Math.max(candleForUpdate.high, price);
-                    candleForUpdate.low = Math.min(candleForUpdate.low, price);
-                    candleForUpdate.close = price;
-                    displayedCandleData[displayedCandleData.length - 1] = candleForUpdate;
-                } else if (!lastDisplayedCandle || displayedCandleTimestamp > lastDisplayedCandle.time) {
-                    candleForUpdate = { time: displayedCandleTimestamp, open: price, high: price, low: price, close: price };
-                    displayedCandleData.push(candleForUpdate);
 
-                    // A new candle has started, so update the indicators.
+                // 3. Find the displayed candle that needs to be corrected with final data.
-                    manager.updateIndicatorsOnNewCandle(displayedCandleData);
+                const displayedCandleToUpdate = displayedCandleData.find(c => c.time === bucketTime);
+                if (!displayedCandleToUpdate) {
+                    console.warn("Could not find a displayed candle to update for closed 1m candle at", new Date(closedCandle.time * 1000).toISOString());
+                    // As a fallback, a full redraw can fix inconsistencies.
+                    // updateChartForTimeframe(true); 
+                    return;
                 }
 
-                if (candleForUpdate) candlestickSeries.update(candleForUpdate);
+                // 4. Find all 1m source candles for this bucket.
+                const sourceCandles = baseCandleData1m.filter(c => 
+                    c.time >= bucketTime && c.time < bucketTime + candleDurationSeconds
+                );
+
+                // 5. If we have source candles, aggregate them to get the CORRECT final data.
+                if (sourceCandles.length > 0) {
+                    const finalCandle = {
+                        time: bucketTime,
+                        open: sourceCandles[0].open,
+                        high: Math.max(...sourceCandles.map(c => c.high)),
+                        low: Math.min(...sourceCandles.map(c => c.low)),
+                        close: sourceCandles[sourceCandles.length - 1].close
+                    };
+
+                    // 6. Update the specific candle in the displayed data array
+                    const displayedIndex = displayedCandleData.findIndex(c => c.time === bucketTime);
+                    if (displayedIndex !== -1) {
+                        displayedCandleData[displayedIndex] = finalCandle;
+                    }
+
+                    // 7. Update the series on the chart and recalculate indicators for accuracy.
+                    candlestickSeries.update(finalCandle);
+                    manager.recalculateAllAfterHistory(baseCandleData1m, displayedCandleData);
+                }
             });
+            // --- MODIFICATION END ---
             
-            function updateChartForTimeframe() {
+            function updateChartForTimeframe(isFullReset = false) {
-                const selectedIntervalMinutes = parseInt(timeframeSelect.value, 10);
                 if (baseCandleData1m.length === 0) return;
                 
-                const newCandleData = aggregateCandles(baseCandleData1m, selectedIntervalMinutes);
+                try {
+                    const visibleTimeRange = isFullReset ? null : chart.timeScale().getVisibleTimeRange();
+                    const newCandleData = aggregateCandles(baseCandleData1m, currentTimeframeMinutes);
                     
-                if (newCandleData.length > 0) {
+                    // Validate the aggregated data
-                    displayedCandleData = newCandleData;
+                    const validCandleData = newCandleData.filter(candle => {
+                        return candle && candle.time && 
+                               !isNaN(candle.open) && !isNaN(candle.high) && 
+                               !isNaN(candle.low) && !isNaN(candle.close) &&
+                               candle.open > 0 && candle.high > 0 && 
+                               candle.low > 0 && candle.close > 0;
+                    });
+                    
+                    if (validCandleData.length > 0) {
+                        displayedCandleData = validCandleData;
                         candlestickSeries.setData(displayedCandleData);
-                    chartTitle.textContent = `{{ symbol }} Chart (${selectedIntervalMinutes}m)`;
+                        chartTitle.textContent = `{{ symbol }} Chart (${currentTimeframeMinutes}m)`;
-                    manager.recalculateAllAfterHistory(displayedCandleData);
+                        manager.recalculateAllAfterHistory(baseCandleData1m, displayedCandleData);
+                        if (visibleTimeRange) {
+                            chart.timeScale().setVisibleRange(visibleTimeRange);
+                        } else {
                             chart.timeScale().fitContent();
                         }
+                    } else {
+                        console.warn('No valid candle data available for timeframe:', currentTimeframeMinutes);
+                    }
+                } catch (error) {
+                    console.error('Error updating chart for timeframe:', error);
+                    console.error('Current timeframe:', currentTimeframeMinutes);
+                    console.error('Base data length:', baseCandleData1m.length);
+                }
             }
 
-            timeframeSelect.addEventListener('change', updateChartForTimeframe);
+            function clearMeasureTool() {
+                measureState = { active: false, finished: false, startPoint: null, endPoint: null };
+                measureToolEl.style.display = 'none';
+                measureSvgEl.innerHTML = '';
+            }
+
+            function formatDuration(seconds) {
+                const d = Math.floor(seconds / (3600*24));
+                const h = Math.floor(seconds % (3600*24) / 3600);
+                const m = Math.floor(seconds % 3600 / 60);
+                let result = '';
+                if (d > 0) result += `${d}d `;
+                if (h > 0) result += `${h}h `;
+                if (m > 0) result += `${m}m`;
+                return result.trim() || '0m';
+            }
+
+            function drawMeasureTool() {
+                if (!measureState.startPoint || !measureState.endPoint) return;
+                const startCoord = {
+                    x: chart.timeScale().timeToCoordinate(measureState.startPoint.time),
+                    y: candlestickSeries.priceToCoordinate(measureState.startPoint.price)
+                };
+                const endCoord = {
+                    x: chart.timeScale().timeToCoordinate(measureState.endPoint.time),
+                    y: candlestickSeries.priceToCoordinate(measureState.endPoint.price)
+                };
+                if (startCoord.x === null || startCoord.y === null || endCoord.x === null || endCoord.y === null) {
+                    measureToolEl.style.display = 'none';
+                    return;
+                }
+                measureToolEl.style.display = 'block';
+                const isUp = measureState.endPoint.price >= measureState.startPoint.price;
+                const boxColor = isUp ? 'var(--measure-tool-up-bg)' : 'var(--measure-tool-down-bg)';
+                const borderColor = isUp ? 'var(--measure-tool-up-border)' : 'var(--measure-tool-down-border)';
+                measureBoxEl.style.backgroundColor = boxColor;
+                measureBoxEl.style.borderColor = borderColor;
+                measureTooltipEl.style.backgroundColor = borderColor;
+                const minX = Math.min(startCoord.x, endCoord.x);
+                const maxX = Math.max(startCoord.x, endCoord.x);
+                const minY = Math.min(startCoord.y, endCoord.y);
+                const maxY = Math.max(startCoord.y, endCoord.y);
+                measureBoxEl.style.left = `${minX}px`;
+                measureBoxEl.style.top = `${minY}px`;
+                measureBoxEl.style.width = `${maxX - minX}px`;
+                measureBoxEl.style.height = `${maxY - minY}px`;
+                const midX = minX + (maxX - minX) / 2;
+                const midY = minY + (maxY - minY) / 2;
+                const arrowSize = 5;
+                const isTimeGoingForward = measureState.endPoint.time >= measureState.startPoint.time;
+                let hArrowPoints = isTimeGoingForward
+                    ? `${maxX - arrowSize},${midY - arrowSize} ${maxX},${midY} ${maxX - arrowSize},${midY + arrowSize}`
+                    : `${minX + arrowSize},${midY - arrowSize} ${minX},${midY} ${minX + arrowSize},${midY + arrowSize}`;
+                let vArrowPoints = isUp
+                    ? `${midX - arrowSize},${minY + arrowSize} ${midX},${minY} ${midX + arrowSize},${minY + arrowSize}`
+                    : `${midX - arrowSize},${maxY - arrowSize} ${midX},${maxY} ${midX + arrowSize},${maxY - arrowSize}`;
+                measureSvgEl.innerHTML = `
+                    <line x1="${minX}" y1="${midY}" x2="${maxX}" y2="${midY}" stroke="${borderColor}" stroke-width="1"/>
+                    <polygon points="${hArrowPoints}" fill="${borderColor}" />
+                    <line x1="${midX}" y1="${minY}" x2="${midX}" y2="${maxY}" stroke="${borderColor}" stroke-width="1"/>
+                    <polygon points="${vArrowPoints}" fill="${borderColor}" />
+                `;
+                const priceChange = measureState.endPoint.price - measureState.startPoint.price;
+                const pctChange = (priceChange / measureState.startPoint.price) * 100;
+                const timeDifference = measureState.endPoint.time - measureState.startPoint.time;
+                const bars = Math.round(timeDifference / (currentTimeframeMinutes * 60));
+                const duration = formatDuration(Math.abs(timeDifference));
+                measureTooltipEl.innerHTML = `
+                    <div>${priceChange.toFixed(2)} (${pctChange.toFixed(2)}%)</div>
+                    <div>${bars} bars, ${duration}</div>
+                `;
+                measureTooltipEl.style.left = `${midX}px`;
+                const tooltipMargin = 8; 
+                if (isUp) {
+                    measureTooltipEl.style.top = `${minY}px`;
+                    measureTooltipEl.style.transform = `translate(-50%, calc(-100% - ${tooltipMargin}px))`;
+                } else {
+                    measureTooltipEl.style.top = `${maxY}px`;
+                    measureTooltipEl.style.transform = `translate(-50%, ${tooltipMargin}px)`;
+                }
+            }
+
+            const onMeasureMove = (param) => {
+                if (!measureState.active || !param.point) return;
+                measureState.endPoint.time = chart.timeScale().coordinateToTime(param.point.x);
+                measureState.endPoint.price = candlestickSeries.coordinateToPrice(param.point.y);
+                if (!measureState.endPoint.time || !measureState.endPoint.price) return;
+                drawMeasureTool();
+            };
+            
+            const onMeasureUp = () => {
+                measureState.active = false;
+                measureState.finished = true;
+                chart.unsubscribeCrosshairMove(onMeasureMove);
+            };
+
+            let priceScaleDragState = { isDragging: false };
+            function priceScaleRedrawLoop() {
+                if (!priceScaleDragState.isDragging) return;
+                drawMeasureTool();
+                requestAnimationFrame(priceScaleRedrawLoop);
+            }
+            chartElement.addEventListener('mousedown', (e) => {
+                if (!measureState.finished) return;
+                const rect = chartElement.getBoundingClientRect();
+                const priceScaleWidth = chart.priceScale('right').width();
+                if (e.clientX > rect.left + rect.width - priceScaleWidth) {
+                    priceScaleDragState.isDragging = true;
+                    requestAnimationFrame(priceScaleRedrawLoop);
+                }
+            });
+            window.addEventListener('mouseup', () => {
+                if (priceScaleDragState.isDragging) {
+                    priceScaleDragState.isDragging = false;
+                }
+            });
+
+            chart.timeScale().subscribeVisibleTimeRangeChange(() => {
+                if (measureState.finished) {
+                    drawMeasureTool();
+                }
+            });
+
+            chart.subscribeCrosshairMove(() => {
+                if (measureState.finished && !isRedrawScheduled) {
+                    isRedrawScheduled = true;
+                    requestAnimationFrame(() => {
+                        drawMeasureTool();
+                        isRedrawScheduled = false;
+                    });
+                }
+            });
+
+            chart.subscribeClick((param) => {
+                if (measureState.finished) {
+                    clearMeasureTool();
+                    return;
+                }
+                if (!param.point || !param.sourceEvent.shiftKey) return;
+                if (measureState.active) {
+                    onMeasureUp();
+                    return;
+                }
+                clearMeasureTool();
+                const time = chart.timeScale().coordinateToTime(param.point.x);
+                const price = candlestickSeries.coordinateToPrice(param.point.y);
+                if (!time || !price) return;
+                measureState.startPoint = { time, price };
+                measureState.endPoint = { time, price };
+                measureState.active = true;
+                measureToolEl.style.display = 'block';
+                drawMeasureTool();
+                chart.subscribeCrosshairMove(onMeasureMove);
+            });
 
             setInterval(() => {
-                const selectedIntervalSeconds = parseInt(timeframeSelect.value, 10) * 60;
+                const selectedIntervalSeconds = currentTimeframeMinutes * 60;
                 const now = new Date().getTime() / 1000;
                 const secondsRemaining = Math.floor(selectedIntervalSeconds - (now % selectedIntervalSeconds));
                 const minutes = Math.floor(secondsRemaining / 60);