from flask import Blueprint, jsonify, request, current_app, g import sqlite3 import datetime from dateutil.relativedelta import relativedelta import logging import random # 配置日志 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s') logger = logging.getLogger(__name__) bp = Blueprint('ph_data', __name__, url_prefix='/ph_data') # 数据缓存字典，格式: {time_range: (seed, cached_data)} ph_data_cache = {} def get_db(): """获取数据库连接""" if 'db' not in g: try: g.db = sqlite3.connect( current_app.config.get('DATABASE', 'agriculture.db'), check_same_thread=False, detect_types=sqlite3.PARSE_DECLTYPES | sqlite3.PARSE_COLNAMES ) g.db.row_factory = sqlite3.Row logger.info("数据库连接成功") except Exception as e: logger.error(f"数据库连接失败: {str(e)}") raise return g.db def close_db(e=None): """关闭数据库连接""" db = g.pop('db', None) if db is not None: db.close() logger.info("数据库连接已关闭") @bp.route('/get_time_ranges', methods=['GET']) def get_time_ranges(): """获取时间范围选项""" try: time_ranges = [ {'value': 'today', 'label': '今日'}, {'value': 'last_three_days', 'label': '前三天'}, {'value': 'next_two_days', 'label': '后两天'}, ] logger.info("成功返回时间范围选项") return jsonify({'time_ranges': time_ranges}) except Exception as e: logger.error(f"获取时间范围失败: {str(e)}") return jsonify({'error': '获取时间范围失败'}), 500 def increase_ph_fluctuation(data_list, time_range, amplitude=1.5): """ 增加PH值的波动幅度，使用固定随机种子确保相同时间范围生成相同波动数据 :param data_list: 包含PH值的数据列表 :param time_range: 时间范围参数 :param amplitude: 波动幅度（默认±1.5） :return: 修改后的列表 """ # 检查缓存 if time_range in ph_data_cache: logger.info(f"使用缓存的波动数据 for {time_range}") return ph_data_cache[time_range] # 为特定时间范围设置固定随机种子 seed = hash(time_range) random.seed(seed) logger.info(f"为时间范围 {time_range} 设置随机种子: {seed}") # 应用波动 modified_data = [] for item in data_list: original_ph = item.get('ph') or item.get('avg_ph') if original_ph is not None: # 随机波动（可正可负） fluctuation = random.uniform(-amplitude, amplitude) new_ph = original_ph + fluctuation # 确保PH值在合理范围（0-14） new_ph = max(0, min(14, new_ph)) # 更新数据 modified_item = item.copy() if 'ph' in modified_item: modified_item['ph'] = round(new_ph, 2) else: modified_item['avg_ph'] = round(new_ph, 2) modified_data.append(modified_item) # 缓存波动后的数据 ph_data_cache[time_range] = modified_data return modified_data @bp.route('/get_ph_data', methods=['GET']) def get_ph_data(): """获取指定时间范围的PH值数据（合并所有设备）""" time_range = request.args.get('time_range', 'today') sample_method = request.args.get('sample_method', 'fixed') # 采样方式：fixed(固定点)或hourly(每小时) logger.info(f"请求PH数据，时间范围: {time_range}，采样方式: {sample_method}") if time_range not in ['today', 'last_three_days', 'next_two_days', 'all']: logger.warning(f"无效的时间范围: {time_range}") return jsonify({'error': '无效的时间范围'}), 400 try: db = get_db() # 硬编码今日为2025-05-27 today = datetime.datetime(2025, 5, 27) today_str = today.strftime('%Y-%m-%d') result = [] if time_range == 'today': # 今日数据查询逻辑 start_date = today_str + ' 00:00:00' end_date = today_str + ' 23:59:59' if sample_method == 'hourly': # 每小时采样 for hour in range(0, 24): sample_time = f"{today_str} {hour:02d}:00:00" start_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S') - relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S') end_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S') + relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S') cursor = db.execute( '''SELECT AVG(ph) as avg_ph FROM temperature_data WHERE (timestamp BETWEEN ? AND ?) OR (DATE(timestamp) = DATE(?))''', (start_time, end_time, sample_time) ) row = cursor.fetchone() avg_ph = float(row['avg_ph']) if row and row['avg_ph'] is not None else 0 result.append({ 'timestamp': sample_time, 'ph': round(avg_ph, 2) }) else: # 固定点采样 cursor = db.execute( '''SELECT timestamp, AVG(ph) as avg_ph FROM temperature_data WHERE (timestamp BETWEEN ? AND ?) OR (DATE(timestamp) = DATE(?)) GROUP BY timestamp ORDER BY timestamp''', (start_date, end_date, today_str) ) data = cursor.fetchall() result = [{'timestamp': row['timestamp'], 'ph': float(row['avg_ph'])} for row in data] logger.info(f"查询到今日PH数据记录: {len(result)} 条") elif time_range == 'last_three_days': # 前三天数据查询 if sample_method == 'hourly': # 每小时采样 for i in range(3, 0, -1): date = today - relativedelta(days=i) date_str = date.strftime('%Y-%m-%d') for hour in range(0, 24): sample_time = f"{date_str} {hour:02d}:00:00" start_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S') - relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S') end_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S') + relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S') cursor = db.execute( '''SELECT AVG(ph) as avg_ph FROM temperature_data WHERE (timestamp BETWEEN ? AND ?) OR (DATE(timestamp) = DATE(?))''', (start_time, end_time, sample_time) ) row = cursor.fetchone() avg_ph = float(row['avg_ph']) if row and row['avg_ph'] is not None else 0 result.append({ 'timestamp': sample_time, 'ph': round(avg_ph, 2) }) else: # 固定点采样（每天6个点） sample_hours = [4, 8, 12, 16, 20, 23] for i in range(3, 0, -1): date = today - relativedelta(days=i) date_str = date.strftime('%Y-%m-%d') for hour in sample_hours: if hour == 23: sample_time = f"{date_str} {hour:02d}:00:00" else: sample_time = f"{date_str} {hour:02d}:00:00" start_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S') - relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S') end_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S') + relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S') cursor = db.execute( '''SELECT AVG(ph) as avg_ph FROM temperature_data WHERE (timestamp BETWEEN ? AND ?) OR (DATE(timestamp) = DATE(?))''', (start_time, end_time, sample_time) ) row = cursor.fetchone() avg_ph = float(row['avg_ph']) if row and row['avg_ph'] is not None else 0 result.append({ 'timestamp': sample_time, 'ph': round(avg_ph, 2) }) logger.info(f"查询到前三天PH数据记录: {len(result)} 条") elif time_range == 'next_two_days': # 后两天数据查询 if sample_method == 'hourly': for i in range(1, 3): date = today + relativedelta(days=i) date_str = date.strftime('%Y-%m-%d') for hour in range(0, 24): sample_time = f"{date_str} {hour:02d}:00:00" start_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S') - relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S') end_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S') + relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S') cursor = db.execute( '''SELECT AVG(ph) as avg_ph FROM temperature_data WHERE (timestamp BETWEEN ? AND ?) OR (DATE(timestamp) = DATE(?))''', (start_time, end_time, sample_time) ) row = cursor.fetchone() avg_ph = float(row['avg_ph']) if row and row['avg_ph'] is not None else 0 result.append({ 'timestamp': sample_time, 'ph': round(avg_ph, 2) }) else: sample_hours = [8, 12, 16, 20] for i in range(1, 3): date = today + relativedelta(days=i) date_str = date.strftime('%Y-%m-%d') for hour in sample_hours: sample_time = f"{date_str} {hour:02d}:00:00" start_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S') - relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S') end_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S') + relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S') cursor = db.execute( '''SELECT AVG(ph) as avg_ph FROM temperature_data WHERE (timestamp BETWEEN ? AND ?) OR (DATE(timestamp) = DATE(?))''', (start_time, end_time, sample_time) ) row = cursor.fetchone() avg_ph = float(row['avg_ph']) if row and row['avg_ph'] is not None else 0 result.append({ 'timestamp': sample_time, 'ph': round(avg_ph, 2) }) logger.info(f"查询到后两天PH数据记录: {len(result)} 条") elif time_range == 'all': # 查询所有PH数据 cursor = db.execute( '''SELECT timestamp, AVG(ph) as avg_ph FROM temperature_data WHERE ph IS NOT NULL GROUP BY timestamp ORDER BY timestamp''' ) data = cursor.fetchall() result = [{'timestamp': row['timestamp'], 'ph': float(row['avg_ph'])} for row in data] logger.info(f"查询到所有PH数据记录: {len(result)} 条") # 关键修改：使用带随机种子的波动函数，并缓存结果 result = increase_ph_fluctuation(result, time_range, amplitude=2.0) return jsonify({ 'time_range': time_range, 'sample_method': sample_method, 'data': result }) except sqlite3.Error as e: logger.error(f"数据库查询错误: {str(e)}") return jsonify({'error': '数据库查询错误'}), 500 except Exception as e: logger.error(f"获取PH数据异常: {str(e)}") return jsonify({'error': '服务器内部错误'}), 500 finally: close_db() @bp.route('/get_ph_data_by_date_range', methods=['GET']) def get_ph_data_by_date_range(): """获取指定日期范围内的PH值数据（合并所有设备）""" start_date_str = request.args.get('start_date') end_date_str = request.args.get('end_date') sample_method = request.args.get('sample_method', 'daily') # 采样方式：daily(每日)或hourly(每小时) # 验证日期格式 try: start_date = datetime.datetime.strptime(start_date_str, '%Y-%m-%d') end_date = datetime.datetime.strptime(end_date_str, '%Y-%m-%d') except ValueError: logger.warning(f"无效的日期格式，需要YYYY-MM-DD格式，实际传入: {start_date_str}, {end_date_str}") return jsonify({'error': '无效的日期格式，需要YYYY-MM-DD格式'}), 400 # 验证日期范围 if start_date > end_date: logger.warning(f"开始日期不能大于结束日期: {start_date_str} > {end_date_str}") return jsonify({'error': '开始日期不能大于结束日期'}), 400 logger.info(f"请求PH数据，日期范围: {start_date_str} 至 {end_date_str}，采样方式: {sample_method}") try: db = get_db() result = [] if sample_method == 'hourly': # 每小时采样 current_date = start_date while current_date <= end_date: date_str = current_date.strftime('%Y-%m-%d') for hour in range(0, 24): sample_time = f"{date_str} {hour:02d}:00:00" start_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S') - relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S') end_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S') + relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S') cursor = db.execute( '''SELECT AVG(ph) as avg_ph FROM temperature_data WHERE (timestamp BETWEEN ? AND ?) OR (DATE(timestamp) = DATE(?))''', (start_time, end_time, sample_time) ) row = cursor.fetchone() avg_ph = float(row['avg_ph']) if row and row['avg_ph'] is not None else 0 result.append({ 'timestamp': sample_time, 'ph': round(avg_ph, 2) }) current_date += relativedelta(days=1) else: # 每日采样 current_date = start_date while current_date <= end_date: date_str = current_date.strftime('%Y-%m-%d') cursor = db.execute( '''SELECT AVG(ph) as avg_ph FROM temperature_data WHERE DATE(timestamp) = ?''', (date_str,) ) row = cursor.fetchone() avg_ph = float(row['avg_ph']) if row and row['avg_ph'] is not None else 0 result.append({ 'date': date_str, 'avg_ph': round(avg_ph, 2) }) current_date += relativedelta(days=1) logger.info(f"查询到{start_date_str}至{end_date_str}的PH数据记录: {len(result)} 条") # 增加PH值的波动幅度，使用日期范围字符串作为种子 range_key = f"{start_date_str}_{end_date_str}" result = increase_ph_fluctuation(result, range_key, amplitude=2.0) return jsonify({ 'start_date': start_date_str, 'end_date': end_date_str, 'sample_method': sample_method, 'data': result }) except sqlite3.Error as e: logger.error(f"数据库查询错误: {str(e)}") return jsonify({'error': '数据库查询错误'}), 500 except Exception as e: logger.error(f"获取PH数据异常: {str(e)}") return jsonify({'error': '服务器内部错误'}), 500 finally: close_db() @bp.route('/get_ph_today', methods=['GET']) def get_ph_today(): """获取2025年5月27日设备1的所有PH值数据""" logger.info("请求获取2025年5月27日设备1的PH数据") try: db = get_db() target_date = datetime.datetime(2025, 5, 27) start = target_date.strftime('%Y-%m-%d 00:00:00') end = target_date.strftime('%Y-%m-%d 23:59:59') logger.info(f"查询范围: {start} ~ {end}，设备ID: 1") cursor = db.execute( '''SELECT timestamp, ph FROM temperature_data WHERE timestamp BETWEEN ? AND ? AND ph IS NOT NULL AND device_id = 1 -- 只查询设备1的数据 ORDER BY timestamp''', (start, end) ) data = cursor.fetchall() if not data: logger.warning("2025-05-27设备1无PH数据，查询最近10条调试") debug_cursor = db.execute(''' SELECT timestamp, ph, device_id FROM temperature_data ORDER BY timestamp DESC LIMIT 10 ''') recent = debug_cursor.fetchall() logger.info("数据库最近10条记录:") for record in recent: logger.info(f" timestamp: {record['timestamp']}, ph: {record['ph']}, device_id: {record['device_id']}") return jsonify({ 'date': '2025-05-27', 'device_id': 1, 'message': '未找到设备1的PH数据', 'data': [] }) result = [] for i, row in enumerate(data): try: # 提取原始数据 raw_ts = row['timestamp'] raw_ph = row['ph'] # 验证时间格式 if isinstance(raw_ts, datetime.datetime): dt = raw_ts else: dt = datetime.datetime.strptime(raw_ts, '%Y-%m-%d %H:%M:%S') # 验证PH值 if raw_ph is None: continue # 跳过空值 if isinstance(raw_ph, (float, int)): ph_value = raw_ph elif isinstance(raw_ph, str): ph_str = raw_ph.strip() if 'pH' in ph_str: ph_str = ph_str.replace('pH', '').strip() ph_value = float(ph_str) else: ph_value = float(raw_ph) result.append({ 'timestamp': raw_ts.strftime('%Y-%m-%d %H:%M:%S') if isinstance(raw_ts, datetime.datetime) else raw_ts, 'ph': round(ph_value, 2), 'formatted_time': dt.strftime('%H:%M') }) except ValueError as ve: logger.error(f"第 {i + 1} 条记录格式错误: {str(ve)}") logger.error(f" 原始数据: timestamp={raw_ts}, ph={raw_ph}") except TypeError as te: logger.error(f"第 {i + 1} 条记录类型错误: {str(te)}") logger.error(f" 原始数据: timestamp={raw_ts}, ph={raw_ph}") except Exception as e: logger.error(f"处理第 {i + 1} 条记录时未知错误: {str(e)}") if not result: logger.warning("设备1的所有记录处理后无有效数据") return jsonify({ 'date': '2025-05-27', 'device_id': 1, 'message': '数据格式错误，无有效PH值', 'data': [] }) logger.info(f"成功处理设备1的 {len(result)} 条有效数据") return jsonify({ 'date': '2025-05-27', 'device_id': 1, 'total_records': len(result), 'data': result }) except sqlite3.OperationalError as oe: logger.error(f"数据库操作错误: {str(oe)}", exc_info=True) return jsonify({ 'date': '2025-05-27', 'device_id': 1, 'error': f'数据库操作错误: {str(oe)}' }), 500 except sqlite3.Error as se: logger.error(f"数据库错误: {str(se)}", exc_info=True) return jsonify({ 'date': '2025-05-27', 'device_id': 1, 'error': f'数据库错误: {str(se)}' }), 500 except Exception as e: logger.error(f"未知异常: {str(e)}", exc_info=True) return jsonify({ 'date': '2025-05-27', 'device_id': 1, 'error': f'未知错误: {str(e)}' }), 500 finally: close_db()