Merge pull request #1 from Prabuddhraj88/main

LGTM
algocry · Nov 26, 2023 · 7837646 · 7837646
2 parents 9de37d6 + 2023fcd
commit 7837646
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Showing 6 changed files with 56 additions and 16 deletions.
diff --git a/Server/Trainer/collect.py b/Server/Trainer/collect.py
@@ -1,6 +1,7 @@
 import os
 import sys
 from rich.progress import track
+import json
 
 current_dir = os.path.dirname(os.path.abspath(__file__))
 parent_dir = os.path.dirname(current_dir)
@@ -25,4 +26,11 @@ def collect_data(longitude, latitude, initial_ts, days_count):
         periodic_aqi_data[period]["timestamp"] = int(initial_ts/1000)
         initial_ts -= CHECK_INTERVAL
 
-    return periodic_aqi_data
+        with open("db/mapped_data.json", "r+") as f:
+            data = json.load(f)
+            if sid not in list(data["data"].keys()):
+                data["data"][sid] = {}
+            data["data"][sid][str(days_count)] = periodic_aqi_data
+            f.seek(0)
+            json.dump(data, f, indent=2)
+            f.truncate()
diff --git a/Server/Trainer/train.py b/Server/Trainer/train.py
@@ -9,8 +9,21 @@
 warnings.simplefilter(action='ignore', category=FutureWarning)
 
 class Trainer:
-    def __init__(self, longitude, latitude, train_duration, from_date_timestamp, prediction_interval):
-        self.data = collect_data(longitude, latitude, from_date_timestamp, train_duration)
+    def __init__(self, longitude, latitude, train_duration, from_date_timestamp, prediction_interval, sid):
+        with open("db/mapped_data.json", "r") as f:
+            mdata = json.load(f)
+            if (sid not in list(mdata["data"].keys())):
+                collect_data(longitude, latitude, from_date_timestamp, train_duration)
+                self.__init__(longitude, latitude, train_duration, from_date_timestamp, prediction_interval, sid)
+                return
+            else:
+                print(str(train_duration), list(mdata["data"][sid].keys()), str(train_duration) not in list(mdata["data"][sid].keys()))
+                if (str(train_duration) not in list(mdata["data"][sid].keys())):
+                    collect_data(longitude, latitude, from_date_timestamp, train_duration)
+                    self.__init__(longitude, latitude, train_duration, from_date_timestamp, prediction_interval, sid)
+                    return                    
+                else:
+                    self.data = mdata["data"][sid][str(train_duration)]
         self.frame = pd.DataFrame.from_dict(self.data, orient="index")
         self.frame.replace("-", 0, inplace=True)
         self.prediction_interval = prediction_interval

diff --git a/Server/db/mapped.json b/Server/db/mapped.json
diff --git a/Server/db/mapped_data.json b/Server/db/mapped_data.json
@@ -0,0 +1,3 @@
+{
+  "data": {}
+}
diff --git a/Server/db/models.json b/Server/db/models.json
@@ -0,0 +1,3 @@
+{
+  "stations": {}
+}
diff --git a/Server/server.py b/Server/server.py
@@ -12,11 +12,18 @@
 yet_mapping_nsid = []
 
 def start_trainer(longitude, latitude, train_duration, from_date_timestamp, prediction_interval, sid):
-    trainer = Trainer(longitude, latitude, train_duration, from_date_timestamp, prediction_interval)
+    trainer = Trainer(longitude, latitude, train_duration, from_date_timestamp, prediction_interval, sid)
     forecasts = trainer.get_all_forecasts()
-    with open("db/mapped.json", "r+") as f:
+    with open("db/models.json", "r+") as f:
         data = json.load(f)
-        data["stations"][sid] = forecasts
+        if sid not in list(data["stations"].keys()):
+            data["stations"][sid] = {}
+
+        if str(prediction_interval) not in list(data["stations"][sid].keys()):
+            data["stations"][sid][str(prediction_interval)] = {}
+
+        data["stations"][sid][str(prediction_interval)]["train_duration"] = train_duration
+        data["stations"][sid][str(prediction_interval)]["forecasts"] = forecasts        
         f.seek(0)
         json.dump(data, f, indent=2)
         f.truncate()
@@ -46,13 +53,24 @@ def get_station_forecast():
 
     response = None
     nsid = client.get_nearest_station([longitude, latitude])
-    with open("db/mapped.json", "r") as f:
+    with open("db/models.json", "r") as f:
         data = json.load(f)
         if nsid in list(data["stations"].keys()):
-            response = {
-                "status": 101,
-                "data": data["stations"][nsid]
-            }
+            if (str(prediction_interval) in list(data["stations"][nsid].keys())) and (str(train_duration) == str(data["stations"][nsid][str(prediction_interval)]["train_duration"])):
+                response = {
+                    "status": 101,
+                    "data": data["stations"][nsid][str(prediction_interval)]["forecasts"]
+                }
+            else:
+                response = {
+                    "status": 102,
+                    "data": "Your area is not mapped for given interval. Mapping your area..."
+                }
+
+                if nsid not in yet_mapping_nsid:
+                    yet_mapping_nsid.append(nsid)
+                    t1 = threading.Thread(target=start_trainer, args=(longitude, latitude, train_duration, from_date_timestamp, prediction_interval, nsid))
+                    t1.start()
         else:
             response = {
                 "status": 102,