flightAware.py

from os import getenv
import requests
import pandas as pd
import polars as polars
from influxdb_client_3  import InfluxDBClient3
from datetime import datetime,timezone
import secret
import time
import os


db = "flightawaredata"
org="827f64a0472b70d8"
url= "https://us-east-1-1.aws.cloud2.influxdata.com/"

# this os.getenv is for the token and apikey, you should still use the secret.py file
token = os.getenv("TOKEN", default = secret.tokenflightaware)
apikey = os.getenv("APIKEY", default = secret.apikey)

#token and org are stored in secret.py - please create this file for yourself 
influxdbClient = InfluxDBClient3(host=url, token=token, org=org)

apiUrl = "https://aeroapi.flightaware.com/aeroapi"

auth_header = {'x-apikey':apikey}
# these params are the bound box region, and limit us to two pages
# create your own http://bboxfinder.com/
# Las Vegas 36.011106 -115.446909 36.249025 -114.889010
# Denver 39.368093 -105.478063 40.186033 -104.258580
params = {
    "query": '-latlong "36.011106 -115.446909 36.249025 -114.889010"',
    'max_pages': 2
}

# it is easier to work with UTC in influxdb and grafana
def convert_to_utc(timestamp):
    if timestamp is not None:
        return str(datetime.now(timezone.utc))
    else:
        return "null"

flight_data=[]


while True:
    try:
        result = requests.get(apiUrl + "/flights/search", params=params, headers=auth_header)
        result.raise_for_status()  # Raise an exception for HTTP errors
        if result.status_code == 200:
            print(result.json()["flights"])
            flight_data = []
            for flight in result.json()["flights"]:
                # smaller planes and private jets dont have to declare their destination, for a first run im removing these
                if flight['destination'] is not None:
                    print(convert_to_utc(flight['last_position']['timestamp']))
                    flight_data.append({
                        "ident": flight['ident'],
                        "fa_flight_id": flight['fa_flight_id'],
                        "takeoff_time": convert_to_utc(flight['actual_off']),
                        "landing_time": convert_to_utc(flight['actual_on']),
                        "first_position_time": convert_to_utc(flight['first_position_time']),
                        # we are setting this one for the time value, which is required
                        "last_position": convert_to_utc(flight['last_position']['timestamp']),
                        "altitude": flight['last_position']['altitude'],
                        "altitude_change": flight['last_position']['altitude_change'],
                        "groundspeed": flight['last_position']['groundspeed'],
                        "latitude": flight['last_position']['latitude'],
                        "longitude": flight['last_position']['longitude'],
                        "aircraft_type": flight['aircraft_type']
                    })
                    #we want every value in the origin and destination - in the future im going to reduce this down to less codes and such
                    for key,value in flight['origin'].items():
                        flight_data.append({f"origin_{key}": value})
                    else:
                        flight_data.append({})

                    for key,value in flight['destination'].items():
                        flight_data.append({f"destination_{key}": value})
                    else:
                        flight_data.append({})

                # this is the break up of the waypoints first and last. Its not impossible to store them all, I just dont know a good way yet.
                    waypoints = flight['waypoints']
                    waypoints = list(zip(waypoints[::2], waypoints[1::2]))

                    if waypoints:
                        first_waypoint = waypoints[0]
                        last_waypoint = waypoints[-1]
                        flight_data.append({"first_waypoint": {"Latitude": first_waypoint[0], "Longitude": first_waypoint[1]}})
                        flight_data.append({"last_waypoint": {"Latitude": last_waypoint[0], "Longitude": last_waypoint[1]}})
                    
                    # this is for me to look at in the console later!
                    print(flight_data)
                    # Merge all dictionaries into one
                    merged_data = {}
                    for d in flight_data:
                        merged_data.update(d)
                    flight_df = pd.DataFrame([merged_data])
                    flight_df['timestamp'] = flight_df['last_position']
                    influxdbClient._write_api.write(bucket=db, record=flight_df, data_frame_measurement_name='flight', data_frame_tag_columns=['ident', 'fa_flight_id'], data_frame_timestamp_column='timestamp')
            else:
                # I dont save planes without a destination
                print("small plane")
    except requests.RequestException as e:
        print(f"An error occurred: {e}")
    except Exception as e:
        print(f"An unexpected error occurred: {e}")
    finally:
        # Sleep for 5 minutes before making the next request
        time.sleep(300)