Add influx api

InfluxDb Information.txt

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+UserName    tjwater
+Password    Tjwater@123456
+Organizatio TJWATEORG
+Bucket      TJWATERBUCKET
+
+API Token : xGDM5RZqRJAuzAGS-otXUdC2NFdY75qJAjRLqAB4p5WcIIAlIUpOpT8_yA16AOHmJWerwQ_08gwb84sy42jnZQ==
+
+
+
+influx config create --config-name onboarding `
+  --host-url "http://localhost:8086" `
+  --org "TJWATERORG" `
+  --token "p4Hq6DQ4xI6yA2tZQgo-VGzjWObylyWd4B45vMoiae0XJeNUlL87FdEUU5cJ63O87W7-nAhhGWl_0FGJiL801w==" `
+  --active

influxdb_api.py

@@ -0,0 +1,426 @@
+from influxdb_client import InfluxDBClient, BucketsApi, WriteApi, OrganizationsApi, Point, QueryApi
+from typing import List, Dict
+from datetime import datetime, timedelta, timezone
+from dateutil import parser
+
+# influxdb数据库连接信息
+url = "http://localhost:8086"  # 替换为你的InfluxDB实例地址
+token = "xGDM5RZqRJAuzAGS-otXUdC2NFdY75qJAjRLqAB4p5WcIIAlIUpOpT8_yA16AOHmJWerwQ_08gwb84sy42jnZQ=="  # 替换为你的InfluxDB Token
+org_name = "TJWATEORG"  # 替换为你的Organization名称
+client = InfluxDBClient(url=url, token=token, org=org_name)
+
+
+def create_and_initialize_buckets(client: InfluxDBClient, org_name: str) -> None:
+
+    bucket_api = BucketsApi(client)
+    write_api = client.write_api()
+    org_api = OrganizationsApi(client)
+
+    # 获取 org_id
+    org = next((o for o in org_api.find_organizations() if o.name == org_name), None)
+    if not org:
+        raise ValueError(f"Organization '{org_name}' not found.")
+    org_id = org.id
+    print(f"Using Organization ID: {org_id}")
+
+    # 定义 Buckets 信息
+    buckets = [
+        {"name": "SCADA_data", "retention_rules": []},
+        {"name": "realtime_data", "retention_rules": []},
+        {"name": "scheme_simulation", "retention_rules": []}
+    ]
+
+    # 创建 Buckets 并初始化数据
+    for bucket in buckets:
+        # 创建 Bucket
+        created_bucket = bucket_api.create_bucket(
+            bucket_name=bucket["name"],
+            retention_rules=bucket["retention_rules"],
+            org_id=org_id
+        )
+        print(f"Bucket '{bucket['name']}' created with ID: {created_bucket.id}")
+
+        # 根据 Bucket 初始化数据
+        if bucket["name"] == "SCADA_data":
+            point = Point("SCADA") \
+                .tag("date", None) \
+                .tag("type", None) \
+                .tag("device_ID", None) \
+                .field("monitored_value", 0.0) \
+                .field("datacleaning_value", 0.0) \
+                .field("simulation_value", 0.0) \
+                .time("2024-11-21T00:00:00Z")
+            write_api.write(bucket="SCADA_data", org=org_name, record=point)
+            print("Initialized SCADA_data with default structure.")
+
+        elif bucket["name"] == "realtime_data":
+            link_point = Point("link") \
+                .tag("date", None) \
+                .tag("ID", None) \
+                .field("flow", 0.0) \
+                .field("leakage", 0.0) \
+                .field("velocity", 0.0) \
+                .field("headloss", 0.0) \
+                .field("status", None) \
+                .field("setting", 0.0) \
+                .field("quality", 0.0) \
+                .time("2024-11-21T00:00:00Z")
+
+            node_point = Point("node") \
+                .tag("date", None) \
+                .tag("ID", None) \
+                .field("head", 0.0) \
+                .field("pressure", 0.0) \
+                .field("actualdemand", 0.0) \
+                .field("demanddeficit", 0.0) \
+                .field("totalExternalOutflow", 0.0) \
+                .field("quality", 0.0) \
+                .time("2024-11-21T00:00:00Z")
+
+            write_api.write(bucket="realtime_data", org=org_name, record=link_point)
+            write_api.write(bucket="realtime_data", org=org_name, record=node_point)
+            print("Initialized realtime_data with default structure.")
+
+        elif bucket["name"] == "scheme_simulation":
+            link_point = Point("link") \
+                .tag("date", None) \
+                .tag("ID", None) \
+                .tag("scheme_Type", None) \
+                .tag("scheme_Name", None) \
+                .field("flow", 0.0) \
+                .field("leakage", 0.0) \
+                .field("velocity", 0.0) \
+                .field("headloss", 0.0) \
+                .field("status", None) \
+                .field("setting", 0.0) \
+                .field("quality", 0.0) \
+                .time("2024-11-21T00:00:00Z")
+
+            node_point = Point("node") \
+                .tag("date", None) \
+                .tag("ID", None) \
+                .tag("scheme_Type", None) \
+                .tag("scheme_Name", None) \
+                .field("head", 0.0) \
+                .field("pressure", 0.0) \
+                .field("actualdemand", 0.0) \
+                .field("demanddeficit", 0.0) \
+                .field("totalExternalOutflow", 0.0) \
+                .field("quality", 0.0) \
+                .time("2024-11-21T00:00:00Z")
+
+            write_api.write(bucket="scheme_simulation", org=org_name, record=link_point)
+            write_api.write(bucket="scheme_simulation", org=org_name, record=node_point)
+            print("Initialized scheme_simulation with default structure.")
+
+
+    print("All buckets created and initialized successfully.")
+
+
+def store_realtime_data_to_influxdb(node_result_list: List[Dict[str, any]], link_result_list: List[Dict[str, any]],
+                                    result_start_time: str,
+                                    bucket: str = "realtime_data", client: InfluxDBClient = client):
+    """
+    将实时数据存储到 InfluxDB 的realtime_data这个bucket中。
+    :param node_result_list: (List[Dict[str, any]]): 包含节点和结果数据的字典列表。
+    :param link_result_list: (List[Dict[str, any]]): 包含连接和结果数据的字典列表。
+    :param result_start_time: (str): 计算结果的模拟开始时间。
+    :param bucket: (str): InfluxDB 的 bucket 名称，默认值为 "realtime_data"。
+    :param client: (InfluxDBClient): 已初始化的 InfluxDBClient 实例。
+    :return:
+    """
+
+    if client.ping():
+        print("Successfully connected to InfluxDB.")
+    else:
+        print("Failed to connect to InfluxDB.")
+
+    # 开始写入数据
+    try:
+        write_api = client.write_api()
+        date_str = result_start_time.split('T')[0]
+        time_beijing = datetime.strptime(result_start_time, '%Y-%m-%dT%H:%M:%S%z').isoformat()
+        for result in node_result_list:
+            # 提取节点信息和结果数据
+            node_id = result.get('node')
+            data_list = result.get('result', [])
+
+            for data in data_list:
+                # 构建 Point 数据，多个 field 存在于一个数据点中
+                node_point = Point("node") \
+                    .tag("date", date_str) \
+                    .tag("ID", node_id) \
+                    .field("head", data.get('head', 0.0)) \
+                    .field("pressure", data.get('pressure', 0.0)) \
+                    .field("actualdemand", data.get('demand', 0.0)) \
+                    .field("demanddeficit", None) \
+                    .field("totalExternalOutflow", None) \
+                    .field("quality", data.get('quality', 0.0)) \
+                    .time(time_beijing)
+
+                # 写入数据到 InfluxDB，多个 field 在同一个 point 中
+                write_api.write(bucket=bucket, org=org_name, record=node_point)
+        print(f"成功将 {len(node_result_list)} 条node数据写入 InfluxDB。")
+        for result in link_result_list:
+            link_id = result.get('link')
+            data_list = result.get('result', [])
+
+            for data in data_list:
+                link_point = Point("link") \
+                    .tag("date", date_str) \
+                    .tag("ID", link_id) \
+                    .field("flow", data.get('flow', 0.0)) \
+                    .field("velocity", data.get('velocity', 0.0)) \
+                    .field("headloss", data.get('headloss', 0.0)) \
+                    .field("quality", data.get('quality', 0.0)) \
+                    .field("status", data.get('status', "UNKNOWN")) \
+                    .field("setting", data.get('setting', 0.0)) \
+                    .field("reaction", data.get('reaction', 0.0)) \
+                    .field("friction", data.get('friction', 0.0)) \
+                    .time(time_beijing)
+                write_api.write(bucket=bucket, org=org_name, record=link_point)
+        print(f"成功将 {len(link_result_list)} 条link数据写入 InfluxDB。")
+
+    except Exception as e:
+        raise RuntimeError(f"数据写入 InfluxDB 时发生错误: {e}")
+
+
+def query_latest_record_by_ID(ID: str, type: str, bucket: str="realtime_data", client: InfluxDBClient=client) -> dict:
+    """
+    查询指定ID的最新的一条记录
+    :param ID: (str): 要查询的 ID。
+    :param type: (str): "node"或“link”
+    :param bucket: (str): 数据存储的 bucket 名称。
+    :param client: (InfluxDBClient): 已初始化的 InfluxDB 客户端实例。
+    :return: dict: 最新记录的数据，如果没有找到则返回 None。
+    """
+    if client.ping():
+        print("Successfully connected to InfluxDB.")
+    else:
+        print("Failed to connect to InfluxDB.")
+    query_api = client.query_api()
+    if type == "node":
+        flux_query = f'''
+        from(bucket: "{bucket}")
+          |> range(start: -30d)  // 查找最近一月的记录
+          |> filter(fn: (r) => r["_measurement"] == "node")
+          |> filter(fn: (r) => r["ID"] == "{ID}")
+          |> pivot(
+              rowKey:["_time"], 
+              columnKey:["_field"], 
+              valueColumn:"_value"
+          )      
+          |> sort(columns: ["_time"], desc: true)
+          |> limit(n: 1)
+        '''
+        tables = query_api.query(flux_query)
+        # 解析查询结果
+        for table in tables:
+            for record in table.records:
+
+                return {
+                    "time": record["_time"],
+                    "nodeID": ID,
+                    "head": record["head"],
+                    "pressure": record["pressure"],
+                    "actualdemand": record["actualdemand"],
+                    # "demanddeficit": record["demanddeficit"],
+                    # "totalExternalOutflow": record["totalExternalOutflow"],
+                    "quality": record["quality"]
+                }
+    elif type == "link":
+        flux_query = f'''
+        from(bucket: "{bucket}")
+          |> range(start: -30d)  // 查找最近一月的记录
+          |> filter(fn: (r) => r["_measurement"] == "link")
+          |> filter(fn: (r) => r["ID"] == "{ID}")
+          |> pivot(
+              rowKey:["_time"], 
+              columnKey:["_field"], 
+              valueColumn:"_value"
+          )      
+          |> sort(columns: ["_time"], desc: true)
+          |> limit(n: 1)
+        '''
+        tables = query_api.query(flux_query)
+        # 解析查询结果
+        for table in tables:
+            for record in table.records:
+                return {
+                    "time": record["_time"],
+                    "linkID": ID,
+                    "flow": record["flow"],
+                    "velocity": record["velocity"],
+                    "headloss": record["headloss"],
+                    "quality": record["quality"],
+                    "status": record["status"],
+                    "setting": record["setting"],
+                    "reaction": record["reaction"],
+                    "friction": record["friction"]
+                }
+    return None  # 如果没有找到记录
+
+
+def query_all_record_by_time(query_time: str, bucket: str="realtime_data", client: InfluxDBClient=client) -> tuple:
+    """
+    查询指定北京时间的所有记录，包括 'node' 和 'link' measurement，分别以指定格式返回。
+    :param query_time: (str): 输入的北京时间，格式为 '2024-11-24T17:30:00+08:00'。
+    :param bucket: (str): 数据存储的 bucket 名称。
+    :param client: (InfluxDBClient): 已初始化的 InfluxDBClient 实例。
+    :return: dict: tuple: (node_records, link_records)
+    """
+    if client.ping():
+        print("Successfully connected to InfluxDB.")
+    else:
+        print("Failed to connect to InfluxDB.")
+    query_api = client.query_api()
+    # 将北京时间转换为 UTC 时间
+    beijing_time = datetime.fromisoformat(query_time)
+    utc_time = beijing_time.astimezone(timezone.utc)
+    utc_start_time = utc_time - timedelta(seconds=1)
+    utc_stop_time = utc_time + timedelta(seconds=1)
+
+    # 构建 Flux 查询语句
+    flux_query = f'''
+    from(bucket: "{bucket}")
+      |> range(start: {utc_start_time.isoformat()}, stop: {utc_stop_time.isoformat()})
+      |> filter(fn: (r) => r["_measurement"] == "node" or r["_measurement"] == "link")
+      |> pivot(
+          rowKey:["_time"], 
+          columnKey:["_field"], 
+          valueColumn:"_value"
+      )           
+    '''
+
+    # 执行查询
+    tables = query_api.query(flux_query)
+    node_records = []
+    link_records = []
+    # 解析查询结果
+
+    for table in tables:
+        for record in table.records:
+            # print(record.values)  # 打印完整记录内容
+            measurement = record["_measurement"]
+            # 处理 node 数据
+            if measurement == "node":
+                node_records.append({
+                    "time": record["_time"],
+                    "ID": record["ID"],
+                    "head": record["head"],
+                    "pressure": record["pressure"],
+                    "actualdemand": record["actualdemand"],
+                    "quality": record["quality"]
+                })
+
+            # 处理 link 数据
+            elif measurement == "link":
+                link_records.append({
+                    "time": record["_time"],
+                    "linkID": record["ID"],
+                    "flow": record["flow"],
+                    "velocity": record["velocity"],
+                    "headloss": record["headloss"],
+                    "quality": record["quality"],
+                    "status": record["status"],
+                    "setting": record["setting"],
+                    "reaction": record["reaction"],
+                    "friction": record["friction"]
+                })
+
+    return node_records, link_records
+
+
+def query_curve_by_ID_property_daterange(ID: str, type: str, property: str, start_date: str, end_date: str, bucket: str="realtime_data", client: InfluxDBClient=client) -> list:
+    """
+     根据 type 查询对应的 measurement，根据 ID 和 date 查询对应的 tag，根据 property 查询对应的 field。
+    :param ID: (str): 要查询的 ID（tag）
+    :param type: (str): 查询的类型（决定 measurement）
+    :param property: (str): 查询的字段名称（field）
+    :param start_date: (str): 查询的开始日期，格式为 'YYYY-MM-DD'
+    :param end_date: (str): 查询的结束日期，格式为 'YYYY-MM-DD'
+    :param bucket: (str): 数据存储的 bucket 名称，默认值为 "realtime_data"
+    :param client: (InfluxDBClient): 已初始化的 InfluxDBClient 实例
+    :return: 查询结果的列表
+    """
+    if client.ping():
+        print("Successfully connected to InfluxDB.")
+    else:
+        print("Failed to connect to InfluxDB.")
+    query_api = client.query_api()
+    # 确定 measurement
+    if type == "node":
+        measurement = "node"
+    elif type == "link":
+        measurement = "link"
+    else:
+        raise ValueError(f"不支持的类型: {type}")
+
+    # 解析日期范围（当天的 UTC 开始和结束时间）
+    # previous_day = datetime.strptime(start_date, "%Y-%m-%d") - timedelta(days=1)
+    # start_time = previous_day.isoformat() + "T16:00:00Z"
+    # stop_time = datetime.strptime(end_date, "%Y-%m-%d").isoformat() + "T15:59:59Z"
+
+    # 将 start_date 的北京时间转换为 UTC 时间范围
+    start_time = (datetime.strptime(start_date, "%Y-%m-%d") - timedelta(days=1)).replace(hour=16, minute=0, second=0, tzinfo=timezone.utc).isoformat()
+    stop_time = datetime.strptime(end_date, "%Y-%m-%d").replace(hour=15, minute=59, second=59, tzinfo=timezone.utc).isoformat()
+
+    # 构建 Flux 查询语句
+    flux_query = f'''
+    from(bucket: "{bucket}")
+      |> range(start: {start_time}, stop: {stop_time})
+      |> filter(fn: (r) => r["_measurement"] == "{measurement}")
+      |> filter(fn: (r) => r["ID"] == "{ID}")
+      |> filter(fn: (r) => r["_field"] == "{property}")
+    '''
+
+    # 执行查询
+    tables = query_api.query(flux_query)
+
+    # 解析查询结果
+    results = []
+    for table in tables:
+        for record in table.records:
+            results.append({
+                "time": record["_time"],
+                "value": record["_value"]
+            })
+
+    return results
+
+# 示例调用
+if __name__ == "__main__":
+    url = "http://localhost:8086"  # 替换为你的InfluxDB实例地址
+    token = "Z4UZj9HuLwLlwoApywvT2nGVP3bwLy18y-sJQ7enzZlJd8YMzMWbBA6F-q4gBiZ-7-IqdxR5aR9LvicKiSNmnA=="           # 替换为你的InfluxDB Token
+    org_name = "beibei"   # 替换为你的Organization名称
+
+    # client = InfluxDBClient(url=url, token=token)
+
+    # # 检查连接状态
+    # try:
+    #     create_and_initialize_buckets(client, org_name)
+    # except Exception as e:
+    #     print(f"连接失败: {e}")
+    # finally:
+    #     client.close()
+    with InfluxDBClient(url=url, token=token, org=org_name) as client:
+
+        bucket_name = "realtime_data"  # 数据存储的 bucket 名称
+        node_id = "ZBBDTZDP000022"  # 查询的节点 ID
+        link_id = "ZBBGXSZW000002"
+    #
+    #     # latest_record = query_latest_record_by_ID(ID=node_id, type="node", bucket=bucket_name, client=client)
+    #     latest_record = query_latest_record_by_ID(ID=link_id, type="link", bucket=bucket_name, client=client)
+    #
+    #     if latest_record:
+    #         print("最新记录：", latest_record)
+    #     else:
+    #         print("未找到符合条件的记录。")
+
+        # node_records, link_records = query_all_record_by_time(query_time="2024-11-25T06:00:00+08:00")
+        # print("Node 数据：", node_records)
+        # print("Link 数据：", link_records)
+
+        curve_result = query_curve_by_ID_property_daterange(ID=node_id, type="node", property="head",
+                                                            start_date="2024-11-25", end_date="2024-11-25")
+        print(curve_result)