531 lines
22 KiB
Python
531 lines
22 KiB
Python
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from flask import Blueprint, jsonify, request, current_app, g
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import sqlite3
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import datetime
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from dateutil.relativedelta import relativedelta
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import logging
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import random
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# 配置日志
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
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logger = logging.getLogger(__name__)
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bp = Blueprint('ph_data', __name__, url_prefix='/ph_data')
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# 数据缓存字典，格式: {time_range: (seed, cached_data)}
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ph_data_cache = {}
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def get_db():
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"""获取数据库连接"""
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if 'db' not in g:
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try:
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g.db = sqlite3.connect(
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current_app.config.get('DATABASE', 'agriculture.db'),
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check_same_thread=False,
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detect_types=sqlite3.PARSE_DECLTYPES | sqlite3.PARSE_COLNAMES
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)
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g.db.row_factory = sqlite3.Row
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logger.info("数据库连接成功")
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except Exception as e:
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logger.error(f"数据库连接失败: {str(e)}")
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raise
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return g.db
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def close_db(e=None):
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"""关闭数据库连接"""
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db = g.pop('db', None)
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if db is not None:
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db.close()
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logger.info("数据库连接已关闭")
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@bp.route('/get_time_ranges', methods=['GET'])
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def get_time_ranges():
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"""获取时间范围选项"""
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try:
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time_ranges = [
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{'value': 'today', 'label': '今日'},
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{'value': 'last_three_days', 'label': '前三天'},
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{'value': 'next_two_days', 'label': '后两天'},
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]
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logger.info("成功返回时间范围选项")
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return jsonify({'time_ranges': time_ranges})
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except Exception as e:
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logger.error(f"获取时间范围失败: {str(e)}")
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return jsonify({'error': '获取时间范围失败'}), 500
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def increase_ph_fluctuation(data_list, time_range, amplitude=1.5):
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"""
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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
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:param data_list: 包含PH值的数据列表
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:param time_range: 时间范围参数
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:param amplitude: 波动幅度（默认±1.5）
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:return: 修改后的列表
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"""
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# 检查缓存
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if time_range in ph_data_cache:
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logger.info(f"使用缓存的波动数据 for {time_range}")
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return ph_data_cache[time_range]
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# 为特定时间范围设置固定随机种子
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seed = hash(time_range)
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random.seed(seed)
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logger.info(f"为时间范围 {time_range} 设置随机种子: {seed}")
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# 应用波动
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modified_data = []
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for item in data_list:
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original_ph = item.get('ph') or item.get('avg_ph')
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if original_ph is not None:
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# 随机波动（可正可负）
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fluctuation = random.uniform(-amplitude, amplitude)
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new_ph = original_ph + fluctuation
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# 确保PH值在合理范围（0-14）
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new_ph = max(0, min(14, new_ph))
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# 更新数据
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modified_item = item.copy()
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if 'ph' in modified_item:
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modified_item['ph'] = round(new_ph, 2)
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else:
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modified_item['avg_ph'] = round(new_ph, 2)
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modified_data.append(modified_item)
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# 缓存波动后的数据
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ph_data_cache[time_range] = modified_data
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return modified_data
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@bp.route('/get_ph_data', methods=['GET'])
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def get_ph_data():
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"""获取指定时间范围的PH值数据（合并所有设备）"""
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time_range = request.args.get('time_range', 'today')
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sample_method = request.args.get('sample_method', 'fixed') # 采样方式：fixed(固定点)或hourly(每小时)
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logger.info(f"请求PH数据，时间范围: {time_range}，采样方式: {sample_method}")
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if time_range not in ['today', 'last_three_days', 'next_two_days', 'all']:
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logger.warning(f"无效的时间范围: {time_range}")
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return jsonify({'error': '无效的时间范围'}), 400
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try:
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db = get_db()
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# 硬编码今日为2025-05-27
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today = datetime.datetime(2025, 5, 27)
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today_str = today.strftime('%Y-%m-%d')
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result = []
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if time_range == 'today':
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# 今日数据查询逻辑
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start_date = today_str + ' 00:00:00'
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end_date = today_str + ' 23:59:59'
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if sample_method == 'hourly':
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# 每小时采样
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for hour in range(0, 24):
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sample_time = f"{today_str} {hour:02d}:00:00"
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start_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S')
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- relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S')
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end_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S')
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+ relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S')
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cursor = db.execute(
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'''SELECT AVG(ph) as avg_ph
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FROM temperature_data
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WHERE (timestamp BETWEEN ? AND ?)
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OR (DATE(timestamp) = DATE(?))''',
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(start_time, end_time, sample_time)
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)
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row = cursor.fetchone()
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avg_ph = float(row['avg_ph']) if row and row['avg_ph'] is not None else 0
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result.append({
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'timestamp': sample_time,
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'ph': round(avg_ph, 2)
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})
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else:
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# 固定点采样
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cursor = db.execute(
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'''SELECT timestamp, AVG(ph) as avg_ph
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FROM temperature_data
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WHERE (timestamp BETWEEN ? AND ?)
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OR (DATE(timestamp) = DATE(?))
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GROUP BY timestamp
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ORDER BY timestamp''',
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(start_date, end_date, today_str)
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)
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data = cursor.fetchall()
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result = [{'timestamp': row['timestamp'], 'ph': float(row['avg_ph'])} for row in data]
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logger.info(f"查询到今日PH数据记录: {len(result)} 条")
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elif time_range == 'last_three_days':
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# 前三天数据查询
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if sample_method == 'hourly':
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# 每小时采样
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for i in range(3, 0, -1):
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date = today - relativedelta(days=i)
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date_str = date.strftime('%Y-%m-%d')
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for hour in range(0, 24):
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sample_time = f"{date_str} {hour:02d}:00:00"
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start_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S')
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- relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S')
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end_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S')
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+ relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S')
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cursor = db.execute(
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'''SELECT AVG(ph) as avg_ph
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FROM temperature_data
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WHERE (timestamp BETWEEN ? AND ?)
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OR (DATE(timestamp) = DATE(?))''',
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(start_time, end_time, sample_time)
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)
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row = cursor.fetchone()
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avg_ph = float(row['avg_ph']) if row and row['avg_ph'] is not None else 0
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result.append({
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'timestamp': sample_time,
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'ph': round(avg_ph, 2)
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})
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else:
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# 固定点采样（每天6个点）
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sample_hours = [4, 8, 12, 16, 20, 23]
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for i in range(3, 0, -1):
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date = today - relativedelta(days=i)
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date_str = date.strftime('%Y-%m-%d')
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for hour in sample_hours:
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if hour == 23:
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sample_time = f"{date_str} {hour:02d}:00:00"
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else:
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sample_time = f"{date_str} {hour:02d}:00:00"
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start_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S')
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- relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S')
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end_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S')
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+ relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S')
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cursor = db.execute(
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'''SELECT AVG(ph) as avg_ph
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FROM temperature_data
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WHERE (timestamp BETWEEN ? AND ?)
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OR (DATE(timestamp) = DATE(?))''',
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(start_time, end_time, sample_time)
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)
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row = cursor.fetchone()
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avg_ph = float(row['avg_ph']) if row and row['avg_ph'] is not None else 0
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result.append({
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'timestamp': sample_time,
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'ph': round(avg_ph, 2)
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})
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logger.info(f"查询到前三天PH数据记录: {len(result)} 条")
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elif time_range == 'next_two_days':
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# 后两天数据查询
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if sample_method == 'hourly':
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for i in range(1, 3):
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date = today + relativedelta(days=i)
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date_str = date.strftime('%Y-%m-%d')
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for hour in range(0, 24):
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sample_time = f"{date_str} {hour:02d}:00:00"
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start_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S')
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- relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S')
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end_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S')
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+ relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S')
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cursor = db.execute(
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'''SELECT AVG(ph) as avg_ph
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FROM temperature_data
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WHERE (timestamp BETWEEN ? AND ?)
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OR (DATE(timestamp) = DATE(?))''',
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(start_time, end_time, sample_time)
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)
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row = cursor.fetchone()
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avg_ph = float(row['avg_ph']) if row and row['avg_ph'] is not None else 0
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result.append({
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'timestamp': sample_time,
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'ph': round(avg_ph, 2)
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})
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else:
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sample_hours = [8, 12, 16, 20]
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for i in range(1, 3):
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date = today + relativedelta(days=i)
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date_str = date.strftime('%Y-%m-%d')
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for hour in sample_hours:
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sample_time = f"{date_str} {hour:02d}:00:00"
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start_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S')
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|||
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- relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S')
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end_time = (datetime.datetime.strptime(sample_time, '%Y-%m-%d %H:%M:%S')
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+ relativedelta(minutes=30)).strftime('%Y-%m-%d %H:%M:%S')
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|||
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cursor = db.execute(
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'''SELECT AVG(ph) as avg_ph
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FROM temperature_data
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WHERE (timestamp BETWEEN ? AND ?)
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OR (DATE(timestamp) = DATE(?))''',
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(start_time, end_time, sample_time)
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)
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row = cursor.fetchone()
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|||
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avg_ph = float(row['avg_ph']) if row and row['avg_ph'] is not None else 0
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|||
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result.append({
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'timestamp': sample_time,
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'ph': round(avg_ph, 2)
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})
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|||
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|||
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logger.info(f"查询到后两天PH数据记录: {len(result)} 条")
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|||
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|
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|||
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elif time_range == 'all':
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|||
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# 查询所有PH数据
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|||
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cursor = db.execute(
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|||
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'''SELECT timestamp, AVG(ph) as avg_ph
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FROM temperature_data
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WHERE ph IS NOT NULL
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GROUP BY timestamp
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|||
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ORDER BY timestamp'''
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|||
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)
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|||
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data = cursor.fetchall()
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|||
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result = [{'timestamp': row['timestamp'], 'ph': float(row['avg_ph'])} for row in data]
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logger.info(f"查询到所有PH数据记录: {len(result)} 条")
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|||
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# 关键修改：使用带随机种子的波动函数，并缓存结果
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|||
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result = increase_ph_fluctuation(result, time_range, amplitude=2.0)
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|||
|
|
|
|||
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return jsonify({
|
|||
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'time_range': time_range,
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|||
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'sample_method': sample_method,
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|||
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'data': result
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|||
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})
|
|||
|
|
|
|||
|
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except sqlite3.Error as e:
|
|||
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logger.error(f"数据库查询错误: {str(e)}")
|
|||
|
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return jsonify({'error': '数据库查询错误'}), 500
|
|||
|
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except Exception as e:
|
|||
|
|
logger.error(f"获取PH数据异常: {str(e)}")
|
|||
|
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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()
|