| '''Copyright 2024 Ashok Kumar |
| |
| Licensed under the Apache License, Version 2.0 (the "License"); |
| you may not use this file except in compliance with the License. |
| You may obtain a copy of the License at |
| |
| http://www.apache.org/licenses/LICENSE-2.0 |
| |
| Unless required by applicable law or agreed to in writing, software |
| distributed under the License is distributed on an "AS IS" BASIS, |
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| See the License for the specific language governing permissions and |
| limitations under the License.''' |
|
|
|
|
| import requests |
| import json |
| import pandas as pd |
| import geopandas as gpd |
| import contextily as ctx |
| import tzlocal |
| import pytz |
| from PIL import Image |
| from datetime import datetime |
| import matplotlib.pyplot as plt |
| from geopy.exc import GeocoderTimedOut |
| from geopy.geocoders import Nominatim |
| import warnings |
| warnings.filterwarnings('ignore') |
| from plotly.graph_objs import Marker |
| import plotly.express as px |
|
|
| def flight_data(flight_view_level, country, local_time_zone, flight_info, airport): |
| geolocator = Nominatim(user_agent="flight_tracker") |
| loc = geolocator.geocode(country) |
| loc_box = loc[1] |
| extend_left =+12*flight_view_level |
| extend_right =+10*flight_view_level |
| extend_top =+10*flight_view_level |
| extend_bottom =+ 18*flight_view_level |
| lat_min, lat_max = (loc_box[0] - extend_left), loc_box[0]+extend_right |
| lon_min, lon_max = (loc_box[1] - extend_bottom), loc_box[1]+extend_top |
|
|
| tile_zoom = 8 |
| figsize = (15, 15) |
| columns = ["icao24","callsign","origin_country","time_position","last_contact","longitude","latitude", |
| "baro_altitude","on_ground","velocity","true_track","vertical_rate","sensors","geo_altitude", |
| "squawk","spi","position_source",] |
| data_url = "https://raw.githubusercontent.com/ashok2216-A/ashok_airport-data/main/data/airports.dat" |
| column_names = ["Airport ID", "Name", "City", "Country", "IATA/FAA", "ICAO", "Latitude", "Longitude", |
| "Altitude", "Timezone", "DST", "Tz database time zone", "Type", "Source"] |
| airport_df = pd.read_csv(data_url, header=None, names=column_names) |
| airport_locations = airport_df[["Name", "City", "Country", "IATA/FAA", "Latitude", "Longitude"]] |
| airport_country_loc = airport_locations[airport_locations['Country'] == str(loc)] |
| airport_country_loc = airport_country_loc[(airport_country_loc['Country'] == str(loc)) & (airport_country_loc['Latitude'] >= lat_min) & |
| (airport_country_loc['Latitude'] <= lat_max) & (airport_country_loc['Longitude'] >= lon_min) & |
| (airport_country_loc['Longitude'] <= lon_max)] |
|
|
| url_data = ( |
| f"https://@opensky-network.org/api/states/all?" |
| f"lamin={str(lat_min)}" |
| f"&lomin={str(lon_min)}" |
| f"&lamax={str(lat_max)}" |
| f"&lomax={str(lon_max)}") |
| json_dict = requests.get(url_data).json() |
|
|
| unix_timestamp = int(json_dict["time"]) |
| local_timezone = pytz.timezone(local_time_zone) |
| local_time = datetime.fromtimestamp(unix_timestamp, local_timezone).strftime('%Y-%m-%d %H:%M:%S') |
| time = [] |
| for i in range(len(json_dict['states'])): |
| time.append(local_time) |
| df_time = pd.DataFrame(time,columns=['time']) |
| state_df = pd.DataFrame(json_dict["states"],columns=columns) |
| state_df['time'] = df_time |
| gdf = gpd.GeoDataFrame( |
| state_df, |
| geometry=gpd.points_from_xy(state_df.longitude, state_df.latitude), |
| crs={"init": "epsg:4326"}, |
| ) |
| return gdf |
| |
|
|
