[server]: Add transient_data function

server/src/functions/transient_data/requirements.txt

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+xmltodict
+requests
+boto3

server/src/functions/transient_data/transient_data.py

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+import json
+import csv
+import xmltodict
+import requests
+import os
+import boto3
+import time
+
+dynamodb = boto3.resource("dynamodb")
+timestamp = str(int(time.time()))
+
+# API URLs
+irishrail_url = "http://api.irishrail.ie/realtime/realtime.asmx/"
+
+
+# function to fetch Irish Rail train data
+def fetch_trains():
+    print("Fetching Irish Rail data.")
+    api_function = "getCurrentTrainsXML_WithTrainType?TrainType="
+    train_types = ["M", "S", "D"]
+    trains = []
+
+    for train_type in train_types:
+        response = requests.get(irishrail_url + api_function + train_type)
+        response.raise_for_status()
+
+        trains_xml = response.text
+        trains_json = json.loads(json.dumps(xmltodict.parse(trains_xml)))
+
+        for train in trains_json["ArrayOfObjTrainPositions"]["objTrainPositions"]:
+            trains.append({
+                "objectID": "IrishRailTrain-" + train["TrainCode"],
+                "objectType": "IrishRailTrain",
+                "timestamp": timestamp,
+                "latitude": str(train["TrainLatitude"]),
+                "longitude": str(train["TrainLongitude"]),
+
+                "trainCode": str(train["TrainCode"]),
+                "trainType": train_type,
+                "trainStatus": train["TrainStatus"],
+                "trainDate": str(train["TrainDate"]),
+                "trainPublicMessage": train["PublicMessage"],
+                "trainDirection": train["Direction"]
+            })
+
+    return trains
+
+# function to fetch Luas stops data and the forecasted trams associated with each stop
+def fetch_luas():
+    print("Fetching Luas data.")
+    stops = []
+
+    stops_tsv = requests.get("https://data.tii.ie/Datasets/Luas/StopLocations/luas-stops.txt").content.decode('utf-8-sig')
+    tsv_reader = csv.DictReader(stops_tsv.splitlines(), delimiter="\t")
+    stops_json = [row for row in tsv_reader]
+
+    for stop in stops_json:
+        response = requests.get("https://luasforecasts.rpa.ie/xml/get.ashx?action=forecast&stop=" + stop["Abbreviation"] + "&encrypt=false")
+        response.raise_for_status()
+
+        trams_xml = response.text
+        trams_json = json.loads(json.dumps(xmltodict.parse(trams_xml)))
+
+        stops.append({
+            "objectID": "LuasStop-" + stop["Abbreviation"],
+            "objectType": "LuasStop",
+            "timestamp": timestamp,
+            "latitude": str(stop["Latitude"]),
+            "longitude": str(stop["Longitude"]),
+
+            "luasStopName": stop["Name"],
+            "luasStopIrishName": stop["IrishName"],
+            "luasStopID": str(stop["StopID"]),
+            "luasStopCode": stop["Abbreviation"],
+            "luasStopLineID": str(stop["LineID"]),
+            "luasStopSortOrder": str(stop["SortOrder"]),
+            "luasStopIsEnabled": str(stop["IsEnabled"]),
+            "luasStopIsParkAndRide": str(stop["IsParkAndRide"]),
+            "luasStopIsCycleAndRide": str(stop["IsCycleAndRide"]),
+            "luasStopZoneCountA": str(stop["ZoneCountA"]),
+            "luasStopZoneCountB": str(stop["ZoneCountB"]),
+            "luasStopMessage": str(trams_json["stopInfo"]["message"]),
+            "luasStopTrams": str(trams_json["stopInfo"]["direction"])
+        })
+
+    return stops
+
+
+# function to fetch bus data
+def fetch_buses():
+    print("Fetching bus data.")
+    buses = []
+    api_url = "https://api.nationaltransport.ie/gtfsr/v2/Vehicles?format=json"
+    headers = {
+        "Cache-Control": "no-cache",
+        "x-api-key": os.getenv("GTFS_KEY")
+    }
+
+    response = requests.get(api_url, headers=headers)
+    response.raise_for_status()
+    buses_json = response.json()
+
+    for bus in buses_json["entity"]:
+        buses.append({
+            "objectID": "Bus-" + bus["id"],
+            "objectType": "Bus",
+            "timestamp": timestamp,
+            "latitude": str(bus["vehicle"]["position"]["latitude"]),
+            "longitude": str(bus["vehicle"]["position"]["longitude"]),
+
+            "busID": str(bus["id"]),
+
+            "busTripID": str(bus["vehicle"]["trip"]["trip_id"]),
+            "busStartTime": str(bus["vehicle"]["trip"]["start_time"]),
+            "busStartDate": str(bus["vehicle"]["trip"]["start_date"]),
+            "busScheduleRelationship": str(bus["vehicle"]["trip"]["schedule_relationship"]),
+            "busRoute": str(bus["vehicle"]["trip"]["route_id"]),
+            "busDirection": str(bus["vehicle"]["trip"]["direction_id"]),
+        })
+
+    return buses
+
+def lambda_handler(event, context):
+    print("Lambda handler triggered; fetching data.")
+    data = fetch_trains() + fetch_buses()
+    print("Data retrieved successfully.")
+
+    table_name = os.environ.get("DYNAMODB_TABLE", "transient_data")
+    table = dynamodb.Table(table_name)
+
+    print("Attempting to batch upload retrieved data to DynamoDB.")
+
+    try:
+        with table.batch_writer() as batch:
+            for record in data:
+                batch.put_item(Item=record)
+
+        print("Completed data upload.")
+
+        return {
+            'statusCode': 200,
+            'body': json.dumps({'message': 'Data inserted successfully!'})
+        }
+    except Exception as e:
+        return {"statusCode": 500, "error": str(e)}
+
+lambda_handler("event", "context")