Add API queryallschemeallrecords

influxdb_api.py

@@ -333,12 +333,13 @@ def store_realtime_SCADA_data_to_influxdb(get_real_value_time: str, bucket: str
     if client.ping():
         pass
     else:
-        print("{} -- Failed to connect to InfluxDB.".format(
-            datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
+        print("{} -- Failed to connect to InfluxDB.".format( datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
+
     write_options = WriteOptions(
         jitter_interval=200,     # 添加抖动以避免同时写入
         max_retry_delay=30000    # 最大重试延迟（毫秒）
     )
+
     write_api = client.write_api(write_options=write_options)
     # 创建一个临时存储点数据的列表
     points_to_write = []
@@ -2594,6 +2595,7 @@ def query_scheme_all_record(scheme_Type: str, scheme_Name: str, query_date: str,
 
 
 # 2025/03/04
+# burst_Analysis
 def query_scheme_all_record_property(scheme_Type: str, scheme_Name: str, query_date: str, type: str, property: str,
                                      bucket: str="scheme_simulation_result", client: InfluxDBClient=client) -> list:
     """

main.py

@@ -2258,6 +2258,27 @@ async def fastapi_query_all_scada_records_by_date(querydate: str):
 
     return result_dict
 
+# DingZQ, 2025-03-15
+# Scheme
+@app.get("/queryallschemeallrecords/")
+async def fastapi_query_all_scheme_all_records(schemetype: str, schemename: str, querydate: str) -> tuple:
+    # 缓存查询结果提高性能
+    global redis_client
+    cache_key = f"{queryallschemeallrecords}_{schemetype}_{schemename}_{querydate}"
+    data = redis_client.get(cache_key)
+    if data:
+        # 使用自定义的反序列化函数
+        loaded_dict = msgpack.unpackb(data, object_hook=object_hook)
+        return loaded_dict
+
+    results = influxdb_api.query_scheme_all_record(scheme_Type==schemetype, scheme_Name=schemename, query_date=querydate, client=influx_client)
+    packed = msgpack.packb(results, default=default_encoder)  
+    redis_client.set(cache_key, packed)
+
+    return results
+
+
+
 
 @app.post("/clearredis/")
 async def fastapi_clear_redis(key: str):