""" Modified data_service.py module for fetching and processing mining data. """ import logging import re import time import json from datetime import datetime, timedelta from zoneinfo import ZoneInfo from concurrent.futures import ThreadPoolExecutor import requests from bs4 import BeautifulSoup from models import OceanData, WorkerData, convert_to_ths from ocean_scraper import OceanScraper # Import the new scraper class MiningDashboardService: """Service for fetching and processing mining dashboard data.""" def __init__(self, power_cost, power_usage, wallet): """ Initialize the mining dashboard service. Args: power_cost (float): Cost of power in $ per kWh power_usage (float): Power usage in watts wallet (str): Bitcoin wallet address for Ocean.xyz """ self.power_cost = power_cost self.power_usage = power_usage self.wallet = wallet self.cache = {} self.sats_per_btc = 100_000_000 self.previous_values = {} self.session = requests.Session() # Initialize the Ocean scraper self.ocean_scraper = OceanScraper(wallet) def fetch_metrics(self): """ Fetch metrics from Ocean.xyz and other sources. Returns: dict: Mining metrics data """ # Add execution time tracking start_time = time.time() try: with ThreadPoolExecutor(max_workers=2) as executor: future_ocean = executor.submit(self.get_ocean_data) future_btc = executor.submit(self.get_bitcoin_stats) try: ocean_data = future_ocean.result(timeout=15) btc_stats = future_btc.result(timeout=15) except Exception as e: logging.error(f"Error fetching metrics concurrently: {e}") return None if ocean_data is None: logging.error("Failed to retrieve Ocean data") return None difficulty, network_hashrate, btc_price, block_count = btc_stats # If we failed to get network hashrate, use a reasonable default to prevent division by zero if network_hashrate is None: logging.warning("Using default network hashrate") network_hashrate = 500e18 # ~500 EH/s as a reasonable fallback # If we failed to get BTC price, use a reasonable default if btc_price is None: logging.warning("Using default BTC price") btc_price = 75000 # $75,000 as a reasonable fallback # Convert hashrates to a common unit (TH/s) for consistency hr3 = ocean_data.hashrate_3hr or 0 hr3_unit = (ocean_data.hashrate_3hr_unit or 'th/s').lower() local_hashrate = convert_to_ths(hr3, hr3_unit) * 1e12 # Convert to H/s for calculation hash_proportion = local_hashrate / network_hashrate if network_hashrate else 0 block_reward = 3.125 blocks_per_day = 86400 / 600 daily_btc_gross = hash_proportion * block_reward * blocks_per_day daily_btc_net = daily_btc_gross * (1 - 0.02 - 0.028) daily_revenue = round(daily_btc_net * btc_price, 2) if btc_price is not None else None daily_power_cost = round((self.power_usage / 1000) * self.power_cost * 24, 2) daily_profit_usd = round(daily_revenue - daily_power_cost, 2) if daily_revenue is not None else None monthly_profit_usd = round(daily_profit_usd * 30, 2) if daily_profit_usd is not None else None daily_mined_sats = int(round(daily_btc_net * self.sats_per_btc)) monthly_mined_sats = daily_mined_sats * 30 # Use default 0 for earnings if scraping returned None. estimated_earnings_per_day = ocean_data.estimated_earnings_per_day if ocean_data.estimated_earnings_per_day is not None else 0 estimated_earnings_next_block = ocean_data.estimated_earnings_next_block if ocean_data.estimated_earnings_next_block is not None else 0 estimated_rewards_in_window = ocean_data.estimated_rewards_in_window if ocean_data.estimated_rewards_in_window is not None else 0 metrics = { 'pool_total_hashrate': ocean_data.pool_total_hashrate, 'pool_total_hashrate_unit': ocean_data.pool_total_hashrate_unit, 'hashrate_24hr': ocean_data.hashrate_24hr, 'hashrate_24hr_unit': ocean_data.hashrate_24hr_unit, 'hashrate_3hr': ocean_data.hashrate_3hr, 'hashrate_3hr_unit': ocean_data.hashrate_3hr_unit, 'hashrate_10min': ocean_data.hashrate_10min, 'hashrate_10min_unit': ocean_data.hashrate_10min_unit, 'hashrate_5min': ocean_data.hashrate_5min, 'hashrate_5min_unit': ocean_data.hashrate_5min_unit, 'hashrate_60sec': ocean_data.hashrate_60sec, 'hashrate_60sec_unit': ocean_data.hashrate_60sec_unit, 'workers_hashing': ocean_data.workers_hashing, 'btc_price': btc_price, 'block_number': block_count, 'network_hashrate': (network_hashrate / 1e18) if network_hashrate else None, 'difficulty': difficulty, 'daily_btc_net': daily_btc_net, 'estimated_earnings_per_day': estimated_earnings_per_day, 'daily_revenue': daily_revenue, 'daily_power_cost': daily_power_cost, 'daily_profit_usd': daily_profit_usd, 'monthly_profit_usd': monthly_profit_usd, 'daily_mined_sats': daily_mined_sats, 'monthly_mined_sats': monthly_mined_sats, 'estimated_earnings_next_block': estimated_earnings_next_block, 'estimated_rewards_in_window': estimated_rewards_in_window, 'unpaid_earnings': ocean_data.unpaid_earnings, 'est_time_to_payout': ocean_data.est_time_to_payout, 'last_block_height': ocean_data.last_block_height, 'last_block_time': ocean_data.last_block_time, 'total_last_share': ocean_data.total_last_share, 'blocks_found': ocean_data.blocks_found or "0", 'last_block_earnings': ocean_data.last_block_earnings } # Ensure estimated_earnings_per_day_sats is calculated correctly metrics['estimated_earnings_per_day_sats'] = int(round(estimated_earnings_per_day * self.sats_per_btc)) metrics['estimated_earnings_next_block_sats'] = int(round(estimated_earnings_next_block * self.sats_per_btc)) metrics['estimated_rewards_in_window_sats'] = int(round(estimated_rewards_in_window * self.sats_per_btc)) # --- Add server timestamps to the response in Los Angeles Time --- metrics["server_timestamp"] = datetime.now(ZoneInfo("America/Los_Angeles")).isoformat() metrics["server_start_time"] = datetime.now(ZoneInfo("America/Los_Angeles")).isoformat() # Log execution time execution_time = time.time() - start_time metrics["execution_time"] = execution_time if execution_time > 10: logging.warning(f"Metrics fetch took {execution_time:.2f} seconds") else: logging.info(f"Metrics fetch completed in {execution_time:.2f} seconds") return metrics except Exception as e: logging.error(f"Unexpected error in fetch_metrics: {e}") return None def get_ocean_data(self): """ Get mining data from Ocean.xyz using the enhanced scraper. Returns: OceanData: Ocean.xyz mining data """ try: # Use the new scraper to get all data data = self.ocean_scraper.get_ocean_data() if data: logging.info("Successfully retrieved data using the enhanced scraper") # Validate critical fields if data.last_block_height == "N/A" or not data.last_block_height: logging.warning("Last block height is missing") if data.est_time_to_payout == "N/A" or not data.est_time_to_payout: logging.warning("Estimated time to payout is missing") if data.blocks_found == "0" or not data.blocks_found: logging.warning("Blocks found is missing") return data except Exception as e: logging.error(f"Error using enhanced scraper: {e}") # Fall back to the original method as a last resort logging.warning("Enhanced scraper failed, falling back to original method") return self.get_ocean_data_original() # Keep the original web scraping method as fallback def get_ocean_data_original(self): """ Original method to get mining data from Ocean.xyz via web scraping. Used as a final fallback. Returns: OceanData: Ocean.xyz mining data """ base_url = "https://ocean.xyz" stats_url = f"{base_url}/stats/{self.wallet}" headers = { 'User-Agent': 'Mozilla/5.0', 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', 'Cache-Control': 'no-cache' } # Create an empty data object to populate data = OceanData() try: response = self.session.get(stats_url, headers=headers, timeout=10) if not response.ok: logging.error(f"Error fetching ocean data: status code {response.status_code}") return None soup = BeautifulSoup(response.text, 'html.parser') # Safely extract pool status information try: pool_status = soup.find("p", id="pool-status-item") if pool_status: text = pool_status.get_text(strip=True) m_total = re.search(r'HASHRATE:\s*([\d\.]+)\s*(\w+/s)', text, re.IGNORECASE) if m_total: raw_val = float(m_total.group(1)) unit = m_total.group(2) data.pool_total_hashrate = raw_val data.pool_total_hashrate_unit = unit span = pool_status.find("span", class_="pool-status-newline") if span: last_block_text = span.get_text(strip=True) m_block = re.search(r'LAST BLOCK:\s*(\d+\s*\(.*\))', last_block_text, re.IGNORECASE) if m_block: full_last_block = m_block.group(1) data.last_block = full_last_block match = re.match(r'(\d+)\s*\((.*?)\)', full_last_block) if match: data.last_block_height = match.group(1) data.last_block_time = match.group(2) else: data.last_block_height = full_last_block data.last_block_time = "" except Exception as e: logging.error(f"Error parsing pool status: {e}") # Parse the earnings value from the earnings table and convert to sats. try: earnings_table = soup.find('tbody', id='earnings-tablerows') if earnings_table: latest_row = earnings_table.find('tr', class_='table-row') if latest_row: cells = latest_row.find_all('td', class_='table-cell') if len(cells) >= 3: earnings_text = cells[2].get_text(strip=True) earnings_value = earnings_text.replace('BTC', '').strip() try: btc_earnings = float(earnings_value) sats = int(round(btc_earnings * 100000000)) data.last_block_earnings = str(sats) except Exception: data.last_block_earnings = earnings_value except Exception as e: logging.error(f"Error parsing earnings data: {e}") # Parse hashrate data from the hashrates table try: time_mapping = { '24 hrs': ('hashrate_24hr', 'hashrate_24hr_unit'), '3 hrs': ('hashrate_3hr', 'hashrate_3hr_unit'), '10 min': ('hashrate_10min', 'hashrate_10min_unit'), '5 min': ('hashrate_5min', 'hashrate_5min_unit'), '60 sec': ('hashrate_60sec', 'hashrate_60sec_unit') } hashrate_table = soup.find('tbody', id='hashrates-tablerows') if hashrate_table: for row in hashrate_table.find_all('tr', class_='table-row'): cells = row.find_all('td', class_='table-cell') if len(cells) >= 2: period_text = cells[0].get_text(strip=True).lower() hashrate_str = cells[1].get_text(strip=True).lower() try: parts = hashrate_str.split() hashrate_val = float(parts[0]) unit = parts[1] if len(parts) > 1 else 'th/s' for key, (attr, unit_attr) in time_mapping.items(): if key.lower() in period_text: setattr(data, attr, hashrate_val) setattr(data, unit_attr, unit) break except Exception as e: logging.error(f"Error parsing hashrate '{hashrate_str}': {e}") except Exception as e: logging.error(f"Error parsing hashrate table: {e}") # Parse lifetime stats data try: lifetime_snap = soup.find('div', id='lifetimesnap-statcards') if lifetime_snap: for container in lifetime_snap.find_all('div', class_='blocks dashboard-container'): label_div = container.find('div', class_='blocks-label') if label_div: label_text = label_div.get_text(strip=True).lower() earnings_span = label_div.find_next('span', class_=lambda x: x != 'tooltiptext') if earnings_span: span_text = earnings_span.get_text(strip=True) try: earnings_value = float(span_text.split()[0].replace(',', '')) if "earnings" in label_text and "day" in label_text: data.estimated_earnings_per_day = earnings_value except Exception: pass except Exception as e: logging.error(f"Error parsing lifetime stats: {e}") # Parse payout stats data try: payout_snap = soup.find('div', id='payoutsnap-statcards') if payout_snap: for container in payout_snap.find_all('div', class_='blocks dashboard-container'): label_div = container.find('div', class_='blocks-label') if label_div: label_text = label_div.get_text(strip=True).lower() earnings_span = label_div.find_next('span', class_=lambda x: x != 'tooltiptext') if earnings_span: span_text = earnings_span.get_text(strip=True) try: earnings_value = float(span_text.split()[0].replace(',', '')) if "earnings" in label_text and "block" in label_text: data.estimated_earnings_next_block = earnings_value elif "rewards" in label_text and "window" in label_text: data.estimated_rewards_in_window = earnings_value except Exception: pass except Exception as e: logging.error(f"Error parsing payout stats: {e}") # Parse user stats data try: usersnap = soup.find('div', id='usersnap-statcards') if usersnap: for container in usersnap.find_all('div', class_='blocks dashboard-container'): label_div = container.find('div', class_='blocks-label') if label_div: label_text = label_div.get_text(strip=True).lower() value_span = label_div.find_next('span', class_=lambda x: x != 'tooltiptext') if value_span: span_text = value_span.get_text(strip=True) if "workers currently hashing" in label_text: try: data.workers_hashing = int(span_text.replace(",", "")) except Exception: pass elif "unpaid earnings" in label_text and "btc" in span_text.lower(): try: data.unpaid_earnings = float(span_text.split()[0].replace(',', '')) except Exception: pass elif "estimated time until minimum payout" in label_text: data.est_time_to_payout = span_text except Exception as e: logging.error(f"Error parsing user stats: {e}") # Parse blocks found data try: blocks_container = soup.find(lambda tag: tag.name == "div" and "blocks found" in tag.get_text(strip=True).lower()) if blocks_container: span = blocks_container.find_next_sibling("span") if span: num_match = re.search(r'(\d+)', span.get_text(strip=True)) if num_match: data.blocks_found = num_match.group(1) except Exception as e: logging.error(f"Error parsing blocks found: {e}") # Parse last share time data try: workers_table = soup.find("tbody", id="workers-tablerows") if workers_table: for row in workers_table.find_all("tr", class_="table-row"): cells = row.find_all("td") if cells and cells[0].get_text(strip=True).lower().startswith("total"): last_share_str = cells[2].get_text(strip=True) try: naive_dt = datetime.strptime(last_share_str, "%Y-%m-%d %H:%M") utc_dt = naive_dt.replace(tzinfo=ZoneInfo("UTC")) la_dt = utc_dt.astimezone(ZoneInfo("America/Los_Angeles")) data.total_last_share = la_dt.strftime("%Y-%m-%d %I:%M %p") except Exception as e: logging.error(f"Error converting last share time '{last_share_str}': {e}") data.total_last_share = last_share_str break except Exception as e: logging.error(f"Error parsing last share time: {e}") return data except Exception as e: logging.error(f"Error fetching Ocean data: {e}") return None def get_worker_data(self): """ Get worker data from Ocean.xyz using the enhanced scraper. Returns: dict: Worker data dictionary with stats and list of workers """ try: # Use the new scraper to get worker data workers_data = self.ocean_scraper.get_workers_data() if workers_data: logging.info("Successfully retrieved worker data using the enhanced scraper") return workers_data except Exception as e: logging.error(f"Error getting worker data using enhanced scraper: {e}") # Fall back to the original methods if the enhanced scraper fails logging.warning("Enhanced worker data fetch failed, trying original methods") # Try the alternative method first as in the original code result = self.get_worker_data_alternative() # Check if alternative method succeeded and found workers with valid names if result and result.get('workers') and len(result['workers']) > 0: # Validate workers - check for invalid names has_valid_workers = False for worker in result['workers']: name = worker.get('name', '').lower() if name and name not in ['online', 'offline', 'total', 'worker', 'status']: has_valid_workers = True break if has_valid_workers: logging.info(f"Alternative worker data method successful: {len(result['workers'])} workers with valid names") return result else: logging.warning("Alternative method found workers but with invalid names") # If alternative method failed or found workers with invalid names, try the original method logging.info("Trying original worker data method") result = self.get_worker_data_original() # Check if original method succeeded and found workers with valid names if result and result.get('workers') and len(result['workers']) > 0: # Validate workers - check for invalid names has_valid_workers = False for worker in result['workers']: name = worker.get('name', '').lower() if name and name not in ['online', 'offline', 'total', 'worker', 'status']: has_valid_workers = True break if has_valid_workers: logging.info(f"Original worker data method successful: {len(result['workers'])} workers with valid names") return result else: logging.warning("Original method found workers but with invalid names") # If both methods failed or found workers with invalid names, use fallback data logging.warning("All worker data fetch methods failed, returning None") return None # Keep the existing worker data methods for fallback def get_bitcoin_stats(self): """ Fetch Bitcoin network statistics with improved error handling and caching. Returns: tuple: (difficulty, network_hashrate, btc_price, block_count) """ urls = { "difficulty": "https://blockchain.info/q/getdifficulty", "hashrate": "https://blockchain.info/q/hashrate", "ticker": "https://blockchain.info/ticker", "blockcount": "https://blockchain.info/q/getblockcount" } # Use previous cached values as defaults if available difficulty = self.cache.get("difficulty") network_hashrate = self.cache.get("network_hashrate") btc_price = self.cache.get("btc_price") block_count = self.cache.get("block_count") try: with ThreadPoolExecutor(max_workers=4) as executor: futures = {key: executor.submit(self.fetch_url, url) for key, url in urls.items()} responses = {key: futures[key].result(timeout=5) for key in futures} # Process each response individually with error handling if responses["difficulty"] and responses["difficulty"].ok: try: difficulty = float(responses["difficulty"].text) self.cache["difficulty"] = difficulty except (ValueError, TypeError) as e: logging.error(f"Error parsing difficulty: {e}") if responses["hashrate"] and responses["hashrate"].ok: try: network_hashrate = float(responses["hashrate"].text) * 1e9 self.cache["network_hashrate"] = network_hashrate except (ValueError, TypeError) as e: logging.error(f"Error parsing network hashrate: {e}") if responses["ticker"] and responses["ticker"].ok: try: ticker_data = responses["ticker"].json() btc_price = float(ticker_data.get("USD", {}).get("last", btc_price)) self.cache["btc_price"] = btc_price except (ValueError, TypeError, json.JSONDecodeError) as e: logging.error(f"Error parsing BTC price: {e}") if responses["blockcount"] and responses["blockcount"].ok: try: block_count = int(responses["blockcount"].text) self.cache["block_count"] = block_count except (ValueError, TypeError) as e: logging.error(f"Error parsing block count: {e}") except Exception as e: logging.error(f"Error fetching Bitcoin stats: {e}") return difficulty, network_hashrate, btc_price, block_count def fetch_url(self, url: str, timeout: int = 5): """ Fetch URL with error handling. Args: url (str): URL to fetch timeout (int): Timeout in seconds Returns: Response: Request response or None if failed """ try: return self.session.get(url, timeout=timeout) except Exception as e: logging.error(f"Error fetching {url}: {e}") return None # Rename the original method to get_worker_data_original def get_worker_data_original(self): """ Original implementation to get worker data from Ocean.xyz. Returns: dict: Worker data dictionary with stats and list of workers """ base_url = "https://ocean.xyz" stats_url = f"{base_url}/stats/{self.wallet}" headers = { 'User-Agent': 'Mozilla/5.0', 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', 'Cache-Control': 'no-cache' } try: logging.info(f"Fetching worker data from {stats_url}") response = self.session.get(stats_url, headers=headers, timeout=15) if not response.ok: logging.error(f"Error fetching ocean worker data: status code {response.status_code}") return None soup = BeautifulSoup(response.text, 'html.parser') # Parse worker data from the workers table workers = [] total_hashrate = 0 total_earnings = 0 workers_table = soup.find('tbody', id='workers-tablerows') if not workers_table: logging.error("Workers table not found in Ocean.xyz page") return None # Debug: Dump table structure to help diagnose parsing issues self.debug_dump_table(workers_table) # Find total worker counts workers_online = 0 workers_offline = 0 avg_acceptance_rate = 95.0 # Default value # Iterate through worker rows in the table for row in workers_table.find_all('tr', class_='table-row'): cells = row.find_all('td', class_='table-cell') # Skip rows that don't have enough cells for basic info if len(cells) < 3: logging.warning(f"Worker row has too few cells: {len(cells)}") continue try: # Extract worker name from the first cell name_cell = cells[0] name_text = name_cell.get_text(strip=True) # Skip the total row if name_text.lower() == 'total': logging.debug("Skipping total row") continue logging.debug(f"Processing worker: {name_text}") # Create worker object with safer extraction worker = { "name": name_text.strip(), "status": "offline", # Default to offline "type": "ASIC", # Default type "model": "Unknown", "hashrate_60sec": 0, "hashrate_60sec_unit": "TH/s", "hashrate_3hr": 0, "hashrate_3hr_unit": "TH/s", "efficiency": 90.0, # Default efficiency "last_share": "N/A", "earnings": 0, "acceptance_rate": 95.0, # Default acceptance rate "power_consumption": 0, "temperature": 0 } # Parse status from second cell if available if len(cells) > 1: status_cell = cells[1] status_text = status_cell.get_text(strip=True).lower() worker["status"] = "online" if "online" in status_text else "offline" # Update counter based on status if worker["status"] == "online": workers_online += 1 else: workers_offline += 1 # Parse last share time if len(cells) > 2: last_share_cell = cells[2] worker["last_share"] = last_share_cell.get_text(strip=True) # Parse 60sec hashrate if available if len(cells) > 3: hashrate_60s_cell = cells[3] hashrate_60s_text = hashrate_60s_cell.get_text(strip=True) # Parse hashrate_60sec and unit with more robust handling try: parts = hashrate_60s_text.split() if parts and len(parts) > 0: # First part should be the number try: numeric_value = float(parts[0]) worker["hashrate_60sec"] = numeric_value # Second part should be the unit if it exists if len(parts) > 1 and 'btc' not in parts[1].lower(): worker["hashrate_60sec_unit"] = parts[1] except ValueError: # If we can't convert to float, it might be a non-numeric value logging.warning(f"Could not parse 60s hashrate value: {parts[0]}") except Exception as e: logging.error(f"Error parsing 60s hashrate '{hashrate_60s_text}': {e}") # Parse 3hr hashrate if available if len(cells) > 4: hashrate_3hr_cell = cells[4] hashrate_3hr_text = hashrate_3hr_cell.get_text(strip=True) # Parse hashrate_3hr and unit with more robust handling try: parts = hashrate_3hr_text.split() if parts and len(parts) > 0: # First part should be the number try: numeric_value = float(parts[0]) worker["hashrate_3hr"] = numeric_value # Second part should be the unit if it exists if len(parts) > 1 and 'btc' not in parts[1].lower(): worker["hashrate_3hr_unit"] = parts[1] # Add to total hashrate (normalized to TH/s for consistency) total_hashrate += convert_to_ths(worker["hashrate_3hr"], worker["hashrate_3hr_unit"]) except ValueError: # If we can't convert to float, it might be a non-numeric value logging.warning(f"Could not parse 3hr hashrate value: {parts[0]}") except Exception as e: logging.error(f"Error parsing 3hr hashrate '{hashrate_3hr_text}': {e}") # Parse earnings if available if len(cells) > 5: earnings_cell = cells[5] earnings_text = earnings_cell.get_text(strip=True) # Parse earnings with more robust handling try: # Remove BTC or other text, keep only the number earnings_value = earnings_text.replace('BTC', '').strip() try: worker["earnings"] = float(earnings_value) total_earnings += worker["earnings"] except ValueError: logging.warning(f"Could not parse earnings value: {earnings_value}") except Exception as e: logging.error(f"Error parsing earnings '{earnings_text}': {e}") # Set worker type based on name (if it can be inferred) lower_name = worker["name"].lower() if 'antminer' in lower_name: worker["type"] = 'ASIC' worker["model"] = 'Bitmain Antminer' elif 'whatsminer' in lower_name: worker["type"] = 'ASIC' worker["model"] = 'MicroBT Whatsminer' elif 'bitaxe' in lower_name or 'nerdqaxe' in lower_name: worker["type"] = 'Bitaxe' worker["model"] = 'BitAxe Gamma 601' workers.append(worker) except Exception as e: logging.error(f"Error parsing worker row: {e}") continue # Get daily sats from the ocean data daily_sats = 0 try: # Try to get this from the payoutsnap card payout_snap = soup.find('div', id='payoutsnap-statcards') if payout_snap: for container in payout_snap.find_all('div', class_='blocks dashboard-container'): label_div = container.find('div', class_='blocks-label') if label_div and "earnings per day" in label_div.get_text(strip=True).lower(): value_span = label_div.find_next('span') if value_span: value_text = value_span.get_text(strip=True) try: btc_per_day = float(value_text.split()[0]) daily_sats = int(btc_per_day * self.sats_per_btc) except (ValueError, IndexError): pass except Exception as e: logging.error(f"Error parsing daily sats: {e}") # Check if we found any workers if not workers: logging.warning("No workers found in the table, possibly a parsing issue") return None # Return worker stats dictionary result = { 'workers': workers, 'total_hashrate': total_hashrate, 'hashrate_unit': 'TH/s', # Always use TH/s for consistent display 'workers_total': len(workers), 'workers_online': workers_online, 'workers_offline': workers_offline, 'total_earnings': total_earnings, 'avg_acceptance_rate': avg_acceptance_rate, 'daily_sats': daily_sats, 'timestamp': datetime.now(ZoneInfo("America/Los_Angeles")).isoformat() } logging.info(f"Successfully retrieved worker data: {len(workers)} workers") return result except Exception as e: logging.error(f"Error fetching Ocean worker data: {e}") import traceback logging.error(traceback.format_exc()) return None def get_worker_data_alternative(self): """ Alternative implementation to get worker data from Ocean.xyz. This version consolidates worker rows from all pages using the wpage parameter. Returns: dict: Worker data dictionary with stats and list of workers. """ try: logging.info("Fetching worker data across multiple pages (alternative method)") # Get all worker rows from every page rows = self.get_all_worker_rows() if not rows: logging.error("No worker rows found across any pages") return None workers = [] total_hashrate = 0 total_earnings = 0 workers_online = 0 workers_offline = 0 invalid_names = ['online', 'offline', 'status', 'worker', 'total'] # Process each row from all pages for row_idx, row in enumerate(rows): cells = row.find_all(['td', 'th']) if not cells or len(cells) < 3: continue first_cell_text = cells[0].get_text(strip=True) if first_cell_text.lower() in invalid_names: continue try: worker_name = first_cell_text or f"Worker_{row_idx+1}" worker = { "name": worker_name, "status": "online", # Default assumption "type": "ASIC", "model": "Unknown", "hashrate_60sec": 0, "hashrate_60sec_unit": "TH/s", "hashrate_3hr": 0, "hashrate_3hr_unit": "TH/s", "efficiency": 90.0, "last_share": "N/A", "earnings": 0, "acceptance_rate": 95.0, "power_consumption": 0, "temperature": 0 } # Extract status from second cell if available if len(cells) > 1: status_text = cells[1].get_text(strip=True).lower() worker["status"] = "online" if "online" in status_text else "offline" if worker["status"] == "online": workers_online += 1 else: workers_offline += 1 # Parse last share from third cell if available if len(cells) > 2: worker["last_share"] = cells[2].get_text(strip=True) # Parse 60sec hashrate from fourth cell if available if len(cells) > 3: hashrate_60s_text = cells[3].get_text(strip=True) try: parts = hashrate_60s_text.split() if parts: worker["hashrate_60sec"] = float(parts[0]) if len(parts) > 1: worker["hashrate_60sec_unit"] = parts[1] except ValueError: logging.warning(f"Could not parse 60-sec hashrate: {hashrate_60s_text}") # Parse 3hr hashrate from fifth cell if available if len(cells) > 4: hashrate_3hr_text = cells[4].get_text(strip=True) try: parts = hashrate_3hr_text.split() if parts: worker["hashrate_3hr"] = float(parts[0]) if len(parts) > 1: worker["hashrate_3hr_unit"] = parts[1] # Normalize and add to total hashrate (using your convert_to_ths helper) total_hashrate += convert_to_ths(worker["hashrate_3hr"], worker["hashrate_3hr_unit"]) except ValueError: logging.warning(f"Could not parse 3hr hashrate: {hashrate_3hr_text}") # Look for earnings in any cell containing 'btc' for cell in cells: cell_text = cell.get_text(strip=True) if "btc" in cell_text.lower(): try: earnings_match = re.search(r'([\d\.]+)', cell_text) if earnings_match: worker["earnings"] = float(earnings_match.group(1)) total_earnings += worker["earnings"] except Exception: pass # Set worker type based on name lower_name = worker["name"].lower() if 'antminer' in lower_name: worker["type"] = 'ASIC' worker["model"] = 'Bitmain Antminer' elif 'whatsminer' in lower_name: worker["type"] = 'ASIC' worker["model"] = 'MicroBT Whatsminer' elif 'bitaxe' in lower_name or 'nerdqaxe' in lower_name: worker["type"] = 'Bitaxe' worker["model"] = 'BitAxe Gamma 601' if worker["name"].lower() not in invalid_names: workers.append(worker) except Exception as e: logging.error(f"Error parsing worker row: {e}") continue if not workers: logging.error("No valid worker data parsed") return None result = { 'workers': workers, 'total_hashrate': total_hashrate, 'hashrate_unit': 'TH/s', 'workers_total': len(workers), 'workers_online': workers_online, 'workers_offline': workers_offline, 'total_earnings': total_earnings, 'avg_acceptance_rate': 99.0, 'timestamp': datetime.now(ZoneInfo("America/Los_Angeles")).isoformat() } logging.info(f"Successfully retrieved {len(workers)} workers across multiple pages") return result except Exception as e: logging.error(f"Error in alternative worker data fetch: {e}") return None