#!/usr/bin/env python3 import os import pytz import math import requests import warnings from datetime import datetime, timedelta from geopy.geocoders import Nominatim from timezonefinder import TimezoneFinder from skyfield.api import load, wgs84 from skyfield import almanac from skyfield.framelib import itrs from geopy.exc import GeocoderUnavailable, GeocoderTimedOut, GeocoderServiceError from requests.exceptions import RequestsDependencyWarning warnings.filterwarnings("ignore", category=RequestsDependencyWarning) # ============================================================================== # --- SANKALPA INSCRIPTION (THE SACRED DECREE) --- # Carve your will here. The script will obey this Hukm (Command) without question. # ============================================================================== LOCATION_MODE = "" #"AUTO" CITY = "Moscow" STATE = "Idaho" COUNTRY = "USA" LATITUDE = "" #28.6139 LONGITUDE = "" #77.2090 PRAYER_METHOD_ANGLES = {"fajr": 18.0, "isha": 18.0} MADHAB = "hanafi" # --- allow overriding via environment variables (so wrappers like try.php can pass values) def _env_or(orig, name): v = os.environ.get(name) if v is None: return orig # preserve empty-string override (explicit) return v LOCATION_MODE = (_env_or(LOCATION_MODE, 'LOCATION_MODE') or "").strip().upper() CITY = _env_or(CITY, 'CITY') STATE = _env_or(STATE, 'STATE') COUNTRY = _env_or(COUNTRY, 'COUNTRY') LATITUDE = _env_or(LATITUDE, 'LATITUDE') LONGITUDE = _env_or(LONGITUDE, 'LONGITUDE') MADHAB = _env_or(MADHAB, 'MADHAB') or MADHAB # PRAYER_METHOD_ANGLES can be partially overridden via env e.g. PRAYER_FAJR, PRAYER_ISHA try: fajr_env = os.environ.get('PRAYER_METHOD_ANGLES_FAJR') isha_env = os.environ.get('PRAYER_METHOD_ANGLES_ISHA') if fajr_env is not None and fajr_env != '': PRAYER_METHOD_ANGLES['fajr'] = float(fajr_env) if isha_env is not None and isha_env != '': PRAYER_METHOD_ANGLES['isha'] = float(isha_env) except Exception: pass MADHAB = _env_or(MADHAB, 'MADHAB') or MADHAB # capture GEOIP debug info if provided by wrappers GEOIP_DETECTED_IP = os.environ.get('GEOIP_DETECTED_IP', '') GEOIP_NOTE = os.environ.get('GEOIP_NOTE', '') # ============================================================================== # --- FOR OFFLINE USE --- # 1. Download 'de421.bsp': Place this file in the same directory as the script. # You can get it from: https://ssd.jpl.nasa.gov/ftp/eph/planets/bsp/de421.bsp # 2. Set Location Manually: Set LOCATION_MODE to "ADDRESS" or "COORDS" and # provide the city/country or latitude/longitude above. This will prevent # any internet lookups for your location. # ============================================================================== # ============================================================================== # --- Expanded City Database with Population --- # Format: (City, Country, Latitude, Longitude, Population) # ============================================================================== WORLD_CITIES = [ ("Tokyo", "Japan", 35.6895, 139.6917, 37435191), ("New Delhi", "India", 28.6139, 77.209, 29399141), ("Shanghai", "China", 31.2304, 121.4737, 26317104), ("São Paulo", "Brazil", -23.5505, -46.6333, 21846507), ("Mumbai", "India", 19.076, 72.8777, 20185064), ("Beijing", "China", 39.9042, 116.4074, 20035455), ("Cairo", "Egypt", 30.0444, 31.2357, 20484965), ("Dhaka", "Bangladesh", 23.8103, 90.4125, 20283552), ("Mexico City", "Mexico", 19.4326, -99.1332, 21671908), ("Osaka", "Japan", 34.6937, 135.5023, 19222665), ("Karachi", "Pakistan", 24.8607, 67.0011, 15741000), ("Chongqing", "China", 29.563, 106.5516, 15354000), ("Istanbul", "Turkey", 41.0082, 28.9784, 15029231), ("Buenos Aires", "Argentina", -34.6037, -58.3816, 15057000), ("Kolkata", "India", 22.5726, 88.3639, 14755000), ("Kinshasa", "Congo", -4.4419, 15.2663, 13932000), ("Lagos", "Nigeria", 6.5244, 3.3792, 13904000), ("Manila", "Philippines", 14.5995, 120.9842, 13699000), ("Tianjin", "China", 39.3434, 117.3616, 13396000), ("Rio de Janeiro", "Brazil", -22.9068, -43.1729, 13374275), ("Guangzhou", "China", 23.1291, 113.2644, 13081000), ("Moscow", "Russia", 55.7558, 37.6176, 12615279), ("Shenzhen", "China", 22.5431, 114.0579, 12356000), ("Lahore", "Pakistan", 31.5204, 74.3587, 12188000), ("Bangalore", "India", 12.9716, 77.5946, 11883000), ("Paris", "France", 48.8566, 2.3522, 11017000), ("Bogota", "Colombia", 4.711, -74.0721, 10778000), ("Jakarta", "Indonesia", -6.2088, 106.8456, 10770487), ("Chennai", "India", 13.0827, 80.2707, 10729000), ("Lima", "Peru", -12.0464, -77.0428, 10555000), ("Bangkok", "Thailand", 13.7563, 100.5018, 10389000), ("New York", "USA", 40.7128, -74.006, 8398748), ("London", "UK", 51.5074, -0.1278, 8982000), ("Seoul", "South Korea", 37.5665, 126.978, 9776000), ("Nagoya", "Japan", 35.1815, 136.9066, 9557000), ("Ho Chi Minh City", "Vietnam", 10.8231, 106.6297, 8993000), ("Tehran", "Iran", 35.6892, 51.389, 8847000), ("Hong Kong", "China", 22.3193, 114.1694, 7497000), ("Los Angeles", "USA", 34.0522, -118.2437, 3990456), ("Madrid", "Spain", 40.4168, -3.7038, 6642000), ("Singapore", "Singapore", 1.3521, 103.8198, 5850342), ("Santiago", "Chile", -33.4489, -70.6693, 6724000), ("Riyadh", "Saudi Arabia", 24.7136, 46.6753, 7009100), ("Saint Petersburg", "Russia", 59.9311, 30.3609, 5384342), ("Sydney", "Australia", -33.8688, 151.2093, 5312163), ("Melbourne", "Australia", -37.8136, 144.9631, 5078193), ("Baghdad", "Iraq", 33.3152, 44.3661, 7144000), ("Toronto", "Canada", 43.6532, -79.3832, 2930000), ("Berlin", "Germany", 52.52, 13.405, 3645000), ("Rome", "Italy", 41.9028, 12.4964, 2872800), ("Chicago", "USA", 41.8781, -87.6298, 2705994), ("Houston", "USA", 29.7604, -95.3698, 2325502), ("Phoenix", "USA", 33.4484, -112.074, 1660272), ("Philadelphia", "USA", 39.9526, -75.1652, 1584138), ("Dallas", "USA", 32.7767, -96.797, 1345047), ("San Francisco", "USA", 37.7749, -122.4194, 883305), ("Boston", "USA", 42.3601, -71.0589, 694583), ("Washington, D.C.", "USA", 38.9072, -77.0369, 705749), ("Miami", "USA", 25.7617, -80.1918, 470914), ("Atlanta", "USA", 33.749, -84.388, 506811), ("Seattle", "USA", 47.6062, -122.3321, 744955), ("Denver", "USA", 39.7392, -104.9903, 716492), ("Vancouver", "Canada", 49.2827, -123.1207, 675218), ("Montreal", "Canada", 45.5017, -73.5673, 1780000), ("Calgary", "Canada", 51.0447, -114.0719, 1285711), ("Ottawa", "Canada", 45.4215, -75.6972, 994837), ("Johannesburg", "South Africa", -26.2041, 28.0473, 5635000), ("Cape Town", "South Africa", -33.9249, 18.4241, 4488545), ("Nairobi", "Kenya", -1.2921, 36.8219, 4397073), ("Addis Ababa", "Ethiopia", 9.03, 38.74, 3384569), ("Casablanca", "Morocco", 33.5731, -7.5898, 3359818), ("Accra", "Ghana", 5.6037, -0.187, 2291352), ("Algiers", "Algeria", 36.775, 3.0589, 2712944), ("Tunis", "Tunisia", 36.8065, 10.1815, 638845), ("Auckland", "New Zealand", -36.8485, 174.7633, 1657000), ("Wellington", "New Zealand", -41.2865, 174.7762, 212700), ("Perth", "Australia", -31.9505, 115.8605, 2059484), ("Brisbane", "Australia", -27.4698, 153.0251, 2280000), ("Adelaide", "Australia", -34.9285, 138.6007, 1345777), ("Canberra", "Australia", -35.2809, 149.13, 426704), ("Honolulu", "USA", 21.3069, -157.8583, 351792), ("Reykjavik", "Iceland", 64.1466, -21.9426, 131345), ("Helsinki", "Finland", 60.1699, 24.9384, 650058), ("Oslo", "Norway", 59.9139, 10.7522, 693494), ("Stockholm", "Sweden", 59.3293, 18.0686, 975904), ("Copenhagen", "Denmark", 55.6761, 12.5683, 623404), ("Dublin", "Ireland", 53.3498, -6.2603, 544107), ("Amsterdam", "Netherlands", 52.3676, 4.9041, 862965), ("Brussels", "Belgium", 50.8503, 4.3517, 1209000), ("Vienna", "Austria", 48.2082, 16.3738, 1897000), ("Prague", "Czech Republic", 50.0755, 14.4378, 1309000), ("Warsaw", "Poland", 50.0497, 19.9445, 1790658), ("Budapest", "Hungary", 47.4979, 19.0402, 1752286), ("Kiev", "Ukraine", 50.4501, 30.5234, 2962180), ("Bucharest", "Romania", 44.4268, 26.1025, 1836000), ("Athens", "Greece", 37.9838, 23.7275, 664046), ("Lisbon", "Portugal", 38.7223, -9.1393, 504718), ("Geneva", "Switzerland", 46.2044, 6.1432, 201818), ("Frankfurt", "Germany", 50.1109, 8.6821, 753056), ("Munich", "Germany", 48.1351, 11.582, 1472000), ("Barcelona", "Spain", 41.3851, 2.1734, 1620343), ("Abu Dhabi", "UAE", 24.4539, 54.3773, 1483000), ("Abuja", "Nigeria", 9.0765, 7.3986, 1235880), ("Amman", "Jordan", 31.9539, 35.9106, 4007526), ("Ankara", "Turkey", 39.9334, 32.8597, 5445026), ("Antananarivo", "Madagascar", -18.8792, 47.5079, 1275207), ("Asuncion", "Paraguay", -25.2637, -57.5759, 525252), ("Baku", "Azerbaijan", 40.4093, 49.8671, 2293100), ("Bamako", "Mali", 12.6392, -8.0029, 2713000), ("Bangui", "Central African Republic", 4.3947, 18.5582, 794000), ("Beirut", "Lebanon", 33.8938, 35.5018, 2000000), ("Belgrade", "Serbia", 44.7866, 20.4489, 1166763), ("Bern", "Switzerland", 46.948, 7.4474, 133883), ("Bratislava", "Slovakia", 48.1486, 17.1077, 437725), ("Brazzaville", "Congo", -4.2634, 15.2429, 1827000), ("Chisinau", "Moldova", 47.0105, 28.8638, 532513), ("Dakar", "Senegal", 14.7167, -17.4677, 1146052), ("Damascus", "Syria", 33.5138, 36.2765, 1711000), ("Dar es Salaam", "Tanzania", -6.7924, 39.2083, 4364541), ("Dili", "Timor-Leste", -8.5586, 125.5739, 222323), ("Djibouti", "Djibouti", 11.589, 43.145, 562000), ("Doha", "Qatar", 25.277, 51.52, 2382000), ("Dubai", "UAE", 25.2048, 55.2708, 3137000), ("Dushanbe", "Tajikistan", 38.5598, 68.787, 846400), ("Edinburgh", "UK", 55.9533, -3.1883, 488050), ("Freetown", "Sierra Leone", 8.4844, -13.2299, 1055964), ("Fortaleza", "Brazil", -3.7319, -38.5267, 2669342),("Gaborone", "Botswana", -24.6282, 25.9231, 231592), ("Georgetown", "Guyana", 6.8013, -58.1551, 118369), ("Guatemala City", "Guatemala", 14.6349, -90.5069, 994938), ("Hanoi", "Vietnam", 21.0278, 105.8342, 7785000), ("Harare", "Zimbabwe", -17.8252, 31.0335, 1485231), ("Havana", "Cuba", 23.1136, -82.3666, 2117625), ("Juba", "South Sudan", 4.8594, 31.5713, 525953), ("Kabul", "Afghanistan", 34.5553, 69.2075, 4222000), ("Kampala", "Uganda", 0.3476, 32.5825, 1680800), ("Kathmandu", "Nepal", 27.7172, 85.324, 1424000), ("Khartoum", "Sudan", 15.5007, 32.5599, 5274321), ("Kigali", "Rwanda", -1.9441, 30.0619, 859332), ("Kingston", "Jamaica", 17.9712, -76.793, 662433), ("Kuwait City", "Kuwait", 29.3759, 47.9774, 2989000), ("La Paz", "Bolivia", -16.4897, -68.1193, 757184), ("Libreville", "Gabon", 0.4162, 9.4673, 703904), ("Lilongwe", "Malawi", -13.9626, 33.7741, 989318), ("Ljubljana", "Slovenia", 46.0569, 14.5058, 284355), ("Lome", "Togo", 6.1319, 1.2228, 837437), ("Luanda", "Angola", -8.8399, 13.2894, 2571861), ("Lusaka", "Zambia", -15.3875, 28.3228, 1747152), ("Luxembourg", "Luxembourg", 49.6116, 6.1319, 122273), ("Malabo", "Equatorial Guinea", 3.7523, 8.7741, 297000), ("Male", "Maldives", 4.1755, 73.5093, 133412), ("Managua", "Nicaragua", 12.115, -86.2362, 1055247), ("Manama", "Bahrain", 26.2285, 50.586, 157474), ("Maputo", "Mozambique", -25.9692, 32.5732, 1088449), ("Maseru", "Lesotho", -29.3157, 27.4849, 330760), ("Mbabane", "Eswatini", -26.3054, 31.1367, 68000), ("Mecca", "Saudi Arabia", 21.3891, 39.8579, 2042000), ("Minsk", "Belarus", 53.9045, 27.5615, 2020600), ("Mogadishu", "Somalia", 2.0469, 45.3182, 2388000), ("Monaco", "Monaco", 43.7384, 7.4246, 38682), ("Monrovia", "Liberia", 6.3007, -10.7958, 1021762), ("Montevideo", "Uruguay", -34.9011, -56.1645, 1319108), ("Moroni", "Comoros", -11.7022, 43.2541, 62351), ("Muscat", "Oman", 23.5859, 58.3829, 1421409), ("N'Djamena", "Chad", 12.1348, 15.0557, 993492), ("Nassau", "Bahamas", 25.047, -77.3554, 274400), ("Naypyidaw", "Myanmar", 19.7633, 96.0785, 924608), ("Niamey", "Niger", 13.5116, 2.1254, 1292000), ("Nicosia", "Cyprus", 35.1856, 33.3823, 310355), ("Nouakchott", "Mauritania", 18.0735, -15.9582, 958199), ("Nuku'alofa", "Tonga", -21.1393, -175.2048, 23221), ("Nur-Sultan", "Kazakhstan", 51.1694, 71.4491, 1136008), ("Ouagadougou", "Burkina Faso", 12.3714, -1.5197, 2453498), ("Panama City", "Panama", 8.9824, -79.5199, 880691), ("Paramaribo", "Suriname", 5.852, -55.2038, 240924), ("Phnom Penh", "Cambodia", 11.5564, 104.9282, 2129371), ("Podgorica", "Montenegro", 42.4304, 19.2594, 150977), ("Port Louis", "Mauritius", -20.1609, 57.5012, 148108), ("Port Moresby", "Papua New Guinea", -9.4431, 147.1803, 364125), ("Port-au-Prince", "Haiti", 18.5392, -72.3364, 987311), ("Port of Spain", "Trinidad and Tobago", 10.6548, -61.5097, 18036), ("Porto-Novo", "Benin", 6.4969, 2.6285, 264320), ("Praia", "Cabo Verde", 14.933, -23.5133, 130271), ("Pretoria", "South Africa", -25.7479, 28.2293, 741652), ("Pyongyang", "North Korea", 39.0392, 125.7625, 2870000), ("Quito", "Ecuador", -0.1807, -78.4678, 1607734), ("Rabat", "Morocco", 34.0209, -6.8416, 577827), ("Riga", "Latvia", 56.9496, 24.1052, 632614), ("Roseau", "Dominica", 15.3013, -61.3882, 14741), ("San Jose", "Costa Rica", 9.9281, -84.0907, 333980), ("San Juan", "Puerto Rico", 18.4663, -66.1057, 342259), ("San Marino", "San Marino", 43.9424, 12.4578, 4211), ("San Salvador", "El Salvador", 13.6929, -89.2182, 258754), ("Sana'a", "Yemen", 15.3694, 44.191, 2545000), ("Santo Domingo", "Dominican Republic", 18.4861, -69.9312, 965040), ("Sao Tome", "Sao Tome and Principe", 0.3365, 6.7277, 71868), ("Sarajevo", "Bosnia and Herzegovina", 43.8563, 18.4131, 275524), ("Skopje", "North Macedonia", 41.9981, 21.4254, 506926), ("Sofia", "Bulgaria", 42.6977, 23.3219, 1241675), ("Sri Jayawardenepura Kotte", "Sri Lanka", 6.9023, 79.859, 115826), ("Sucre", "Bolivia", -19.0196, -65.2619, 237480), ("Suva", "Fiji", -18.1416, 178.4419, 88271), ("Taipei", "Taiwan", 25.033, 121.5654, 2646204), ("Tallinn", "Estonia", 59.437, 24.7536, 434562), ("Tashkent", "Uzbekistan", 41.2995, 69.2401, 2485900), ("Tbilisi", "Georgia", 41.7151, 44.8271, 1118035), ("Tegucigalpa", "Honduras", 14.0723, -87.1921, 990660), ("Thimphu", "Bhutan", 27.4728, 89.639, 114551), ("Tirana", "Albania", 41.3275, 19.8187, 418495), ("Tiraspol", "Moldova", 46.8403, 29.6105, 133807), ("Tripoli", "Libya", 32.8872, 13.1913, 1126000), ("Ulaanbaatar", "Mongolia", 47.9179, 106.8833, 1540000), ("Vaduz", "Liechtenstein", 47.141, 9.5215, 5696), ("Valletta", "Malta", 35.8989, 14.5146, 6444), ("Victoria", "Seychelles", -4.6236, 55.452, 26450), ("Vientiane", "Laos", 17.9748, 102.6309, 820000), ("Vilnius", "Lithuania", 54.6872, 25.2797, 539043), ("Windhoek", "Namibia", -22.5594, 17.0832, 268132), ("Yamoussoukro", "Côte d'Ivoire", 6.8206, -5.2768, 212670), ("Yaounde", "Cameroon", 3.848, 11.5021, 2765000), ("Yerevan", "Armenia", 40.1792, 44.4991, 1075800), ("Zagreb", "Croatia", 45.815, 15.9819, 806341) ] CITIES = {f"{c[0]}, {c[1]}": (c[2], c[3]) for c in WORLD_CITIES} def haversine_km(lat1, lon1, lat2, lon2): """Calculates the distance between two points on Earth.""" R = 6371.0; phi1, phi2 = math.radians(lat1), math.radians(lat2) a = math.sin(math.radians(lat2 - lat1)/2)**2 + math.cos(phi1)*math.cos(phi2)*math.sin(math.radians(lon2 - lon1)/2)**2 return 2 * R * math.asin(math.sqrt(a)) class LocalPrayerCalculator: """Calculates prayer times from first principles.""" def __init__(self, latitude, longitude, timezone_str, madhab, fajr_angle, isha_angle): self.lat, self.lon, self.tz_str = latitude, longitude, timezone_str self.madhab, self.fajr_angle, self.isha_angle = madhab, fajr_angle, isha_angle def _get_julian_date(self, dt): return (dt - datetime(2000, 1, 1, 12, 0, 0, tzinfo=pytz.utc)).total_seconds() / 86400.0 def _calculate_sun_position(self, julian_date): mean_solar_anomaly = (357.5291 + 0.98560028 * julian_date) % 360 mean_longitude = (280.459 + 0.98564736 * julian_date) % 360 ecliptic_longitude = (mean_longitude + 1.915 * math.sin(math.radians(mean_solar_anomaly)) + 0.020 * math.sin(math.radians(2 * mean_solar_anomaly))) % 360 obliquity = 23.439 - 0.00000036 * julian_date right_ascension = math.degrees(math.atan2(math.cos(math.radians(obliquity)) * math.sin(math.radians(ecliptic_longitude)), math.cos(math.radians(ecliptic_longitude)))) declination = math.degrees(math.asin(math.sin(math.radians(obliquity)) * math.sin(math.radians(ecliptic_longitude)))) equation_of_time = (mean_longitude / 15.0) - (right_ascension / 15.0) if (mean_longitude / 15.0) > 20 and (right_ascension / 15.0) < 4: equation_of_time += 24 return declination, equation_of_time def _calculate_time_from_angle(self, angle, declination, eot, is_sunrise=False): lat_rad, dec_rad, angle_rad = math.radians(self.lat), math.radians(declination), math.radians(angle) try: hour_angle = math.degrees(math.acos((math.sin(angle_rad) - math.sin(lat_rad) * math.sin(dec_rad)) / (math.cos(lat_rad) * math.cos(dec_rad)))) except ValueError: return None if is_sunrise: hour_angle = -hour_angle transit = 12 - (self.lon / 15.0) - eot return transit + (hour_angle / 15.0) def calculate_times_for_date(self, dt_local): dt_utc = dt_local.astimezone(pytz.utc) def to_local(utc_hour): if utc_hour is None: return None return (dt_utc.replace(hour=0, minute=0, second=0) + timedelta(hours=utc_hour)).astimezone(pytz.timezone(self.tz_str)) declination, eot = self._calculate_sun_position(self._get_julian_date(dt_utc)) shadow_length = 2 if self.madhab == 'hanafi' else 1 asr_angle = math.degrees(math.atan(1 / (shadow_length + math.tan(abs(math.radians(self.lat - declination)))))) return { "fajr": to_local(self._calculate_time_from_angle(-self.fajr_angle, declination, eot, is_sunrise=True)), "sunrise": to_local(self._calculate_time_from_angle(-0.833, declination, eot, is_sunrise=True)), "dhuhr": to_local(12 - (self.lon / 15.0) - eot), "asr": to_local(self._calculate_time_from_angle(asr_angle, declination, eot)), "maghrib": to_local(self._calculate_time_from_angle(-0.833, declination, eot)), "isha": to_local(self._calculate_time_from_angle(-self.isha_angle, declination, eot)), } def get_location_by_ip(): try: data = requests.get('https://ipinfo.io/json', timeout=5).json() lat, lon = map(float, data['loc'].split(',')) tf = TimezoneFinder() return {"latitude": lat, "longitude": lon, "timezone": tf.timezone_at(lng=lon, lat=lat), "address": f"Current Location ({data.get('city', 'Unknown')})"} except (requests.exceptions.ConnectionError, Exception): return None def get_location_by_address(city, state, country): city_key = f"{city}, {country}" if city_key in CITIES: lat, lon = CITIES[city_key] tf = TimezoneFinder() return {"latitude": lat, "longitude": lon, "timezone": tf.timezone_at(lng=lon, lat=lat), "address": city_key} try: geolocator = Nominatim(user_agent="cosmic_compass") loc = geolocator.geocode(f"{city}, {state}, {country}", timeout=5) if loc: tf = TimezoneFinder() return {"latitude": loc.latitude, "longitude": loc.longitude, "timezone": tf.timezone_at(lng=loc.longitude, lat=loc.latitude), "address": loc.address} except (GeocoderServiceError, Exception): return None def get_location_by_coords(lat, lon): if not all((lat, lon, str(lat).strip(), str(lon).strip())): return None try: lat_f, lon_f = float(lat), float(lon) tf = TimezoneFinder() tz_str = tf.timezone_at(lng=lon_f, lat=lat_f) if tz_str: return {"latitude": lat_f, "longitude": lon_f, "timezone": tz_str, "address": f"Coordinates ({lat_f}, {lon_f})"} except Exception: return None def calculate_moon_mysteries(eph, observer, ts, t0, tz): now_dt, day_start = t0.astimezone(tz), t0.astimezone(tz).replace(hour=0, minute=0, second=0, microsecond=0) search_start_ts, search_end_ts = ts.from_datetime(day_start - timedelta(days=2)), ts.from_datetime(day_start + timedelta(days=2)) def _to_dt(t): return t.utc_datetime().replace(tzinfo=pytz.utc).astimezone(tz) moon_times = {"rise": None, "transit": None, "set": None, "ascent_45": None, "descent_45": None} try: def choose_best(events, start_day_dt): if not events: return None end_day_dt = start_day_dt + timedelta(days=1) for e in events: if start_day_dt <= e < end_day_dt: return e return min(events, key=lambda x: abs(x - (start_day_dt + timedelta(hours=12)))) t_rise, y_rise = almanac.find_discrete(search_start_ts, search_end_ts, almanac.risings_and_settings(eph, eph['moon'], observer)) moon_times['rise'], moon_times['set'] = choose_best([_to_dt(t) for t, y in zip(t_rise, y_rise) if y], day_start), choose_best([_to_dt(t) for t, y in zip(t_rise, y_rise) if not y], day_start) t_transit, _ = almanac.find_discrete(search_start_ts, search_end_ts, almanac.meridian_transits(eph, eph['moon'], observer)) if t_transit: highest_transit = max(t_transit, key=lambda t: (eph['earth'] + observer).at(t).observe(eph['moon']).apparent().altaz()[0].degrees) moon_times['transit'] = _to_dt(highest_transit) def moon_above_45(t): return (eph['earth'] + observer).at(t).observe(eph['moon']).apparent().altaz()[0].degrees > 45.0 moon_above_45.step_days = 0.05 t_45, y_45 = almanac.find_discrete(search_start_ts, search_end_ts, moon_above_45) if moon_times['rise']: moon_times['ascent_45'] = next((_to_dt(t) for t, y in zip(t_45, y_45) if y and _to_dt(t) > moon_times['rise']), None) if moon_times['transit']: moon_times['descent_45'] = next((_to_dt(t) for t, y in zip(t_45, y_45) if not y and _to_dt(t) > moon_times['transit']), None) except Exception: pass return moon_times def calculate_inland_tides(eph, observer, ts, target_date, tz): day_start = datetime(target_date.year, target_date.month, target_date.day, tzinfo=tz) # Widen search window to be >2 lunar days (~49.7h) to ensure we find enough high tides for interpolation. search_start_ts, search_end_ts = ts.from_datetime(day_start - timedelta(days=1)), ts.from_datetime(day_start + timedelta(days=2)) def _to_dt(t): return t.utc_datetime().replace(tzinfo=pytz.utc).astimezone(tz) tides = [] try: t_transits, _ = almanac.find_discrete(search_start_ts, search_end_ts, almanac.meridian_transits(eph, eph['moon'], observer)) high_tides = sorted([_to_dt(t) for t in t_transits]) # Combine all high tides and interpolated low tides into a single list all_events = [] for ht in high_tides: all_events.append({'name': 'High Tide', 'time': ht}) for i in range(len(high_tides) - 1): low_tide_time = high_tides[i] + (high_tides[i+1] - high_tides[i]) / 2 all_events.append({'name': 'Low Tide', 'time': low_tide_time}) tides = all_events except Exception: pass return sorted([t for t in tides if day_start <= t['time'] < day_start + timedelta(days=2)], key=lambda x: x['time']) def format_time(dt_object): return dt_object.strftime('%I:%M %p') if dt_object else "Does not occur" def subpoint_of_body(eph, body, t): try: lat, lon, _ = eph['earth'].at(t).observe(eph[body]).apparent().frame_latlon(itrs) lon_deg = lon.degrees - 360 if lon.degrees > 180 else lon.degrees return lat.degrees, lon_deg except Exception: return None, None def analyze_sub_point_locations(target_lat, target_lon, eph, ts, body_name): t0 = ts.now() visible_cities = [] for city_data in WORLD_CITIES: city_obs = wgs84.latlon(city_data[2], city_data[3]) alt, _, _ = (eph['earth'] + city_obs).at(t0).observe(eph[body_name]).apparent().altaz() if alt.degrees > 0: visible_cities.append(city_data) if not visible_cities: visible_cities = WORLD_CITIES closest = min(visible_cities, key=lambda c: haversine_km(target_lat, target_lon, c[2], c[3])) northern, southern = [c for c in visible_cities if c[2] > 0], [c for c in visible_cities if c[2] < 0] def get_influence_score(city, t_lat, t_lon): dist = haversine_km(t_lat, t_lon, city[2], city[3]) return city[4] / (dist**2) if dist > 1 else float('inf') def find_most_influenced(candidates, t_lat, t_lon, exclude=None): if exclude: candidates = [c for c in candidates if c[0] != exclude[0]] if not candidates: return None return max(candidates, key=lambda c: get_influence_score(c, t_lat, t_lon)) pop_n = find_most_influenced(northern, target_lat, target_lon) if pop_n and pop_n[0] == closest[0]: # De-duplicate pop_n = find_most_influenced(northern, target_lat, target_lon, exclude=pop_n) pop_s = find_most_influenced(southern, target_lat, target_lon) if pop_s and pop_s[0] == closest[0]: # De-duplicate pop_s = find_most_influenced(southern, target_lat, target_lon, exclude=pop_s) def format_city(city_data, t_lat, t_lon): if not city_data: return "N/A" dist = haversine_km(t_lat, t_lon, city_data[2], city_data[3]) return f"{city_data[0]}, {city_data[1]} (~{int(dist)} km)" return {'nearest': format_city(closest, target_lat, target_lon), 'most_influenced_north': format_city(pop_n, target_lat, target_lon), 'most_influenced_south': format_city(pop_s, target_lat, target_lon)} def find_global_tide_locations(eph, ts): t0 = ts.now() moon_lat, moon_lon = subpoint_of_body(eph, 'moon', t0) sun_lat, sun_lon = subpoint_of_body(eph, 'sun', t0) antipode_lon = (moon_lon + 180) % 360 - 180 high_tide_points = [(moon_lat, moon_lon), (-moon_lat, antipode_lon), (sun_lat, sun_lon)] low_tide_points = [(0, (moon_lon + 90) % 360 - 180), (0, (moon_lon - 90) % 360 - 180)] def find_nearest_city_for_point(p_lat, p_lon): if p_lat is None: return None closest = min(WORLD_CITIES, key=lambda c: haversine_km(p_lat, p_lon, c[2], c[3])) return f"{closest[0]}, {closest[1]}" return { 'high': list(filter(None, {find_nearest_city_for_point(lat, lon) for lat, lon in high_tide_points})), 'low': list(filter(None, {find_nearest_city_for_point(lat, lon) for lat, lon in low_tide_points})) } if __name__ == "__main__": mode = (LOCATION_MODE or "").strip().upper() # Prefer explicit environment-provided coordinates if present (even if LOCATION_MODE differs) location = None location_source = None if LATITUDE is not None and LONGITUDE is not None and (str(LATITUDE).strip() != '' or str(LONGITUDE).strip() != ''): coords_loc = get_location_by_coords(LATITUDE, LONGITUDE) if coords_loc: location = coords_loc location_source = 'ENV_COORDS' if not location: if mode == "AUTO": location = get_location_by_ip() or get_location_by_address(CITY, STATE, COUNTRY) location_source = 'GEOIP' if location and mode == 'AUTO' else 'ADDRESS' else: location = get_location_by_coords(LATITUDE, LONGITUDE) or get_location_by_address(CITY, STATE, COUNTRY) location_source = 'COORDS' if location and (LATITUDE or LONGITUDE) else 'ADDRESS' if not location: print("The cosmos remains veiled. Location could not be determined.") else: ts, eph = load.timescale(), None try: eph = load('de421.bsp') except Exception: print("Local de421.bsp not found. Attempting to download for future offline use...") try: eph = load('de421.bsp') except Exception as e: print(f"Warning: Could not download ephemeris ({e}). Moon and Tide data will be skipped.") observer = wgs84.latlon(location['latitude'], location['longitude']) tz = pytz.timezone(location['timezone']); now = datetime.now(tz) t0 = ts.from_datetime(now) print(f"\n--- Qibla-Numa Report for: {location['address']} at {now.strftime('%I:%M %p')} ---") # provenance line: where the location came from (ENV coords, GEOIP, ADDRESS, etc.) try: prov = location_source if 'location_source' in locals() and location_source else 'UNKNOWN' except Exception: prov = 'UNKNOWN' prov_parts = [f"source={prov}"] if GEOIP_DETECTED_IP: prov_parts.append(f"geoip_ip={GEOIP_DETECTED_IP}") if GEOIP_NOTE: prov_parts.append(f"geoip_note={GEOIP_NOTE}") print("[" + ", ".join(prov_parts) + "]") sun_times = LocalPrayerCalculator( latitude=location['latitude'], longitude=location['longitude'], timezone_str=location['timezone'], madhab=MADHAB, fajr_angle=PRAYER_METHOD_ANGLES['fajr'], isha_angle=PRAYER_METHOD_ANGLES['isha'] ).calculate_times_for_date(now) prayer_events = [{'name': label, 'time': sun_times[key]} for key, label in {'fajr': 'Fajr', 'sunrise': 'Sunrise', 'dhuhr': 'Dhuhr', 'asr': 'Asr', 'maghrib': 'Maghrib', 'isha': 'Isha'}.items() if sun_times.get(key)] moon_events, all_tide_events = [], [] if eph: moon_times = calculate_moon_mysteries(eph, observer, ts, t0, tz) moon_events = [{'name': label, 'time': moon_times[key]} for key, label in {'rise': 'Moonrise', 'ascent_45': 'Ascent 45°', 'transit': 'Zenith', 'descent_45': 'Descent 45°', 'set': 'Moonset'}.items() if moon_times.get(key)] all_tide_events = calculate_inland_tides(eph, observer, ts, now.date(), tz) def get_next_event(events, now_time): future = sorted([e for e in events if e['time'] > now_time], key=lambda x: x['time']) return future[0] if future else None next_prayer_event = get_next_event(prayer_events, now) next_moon_event = get_next_event(moon_events, now) next_tide_event = get_next_event(all_tide_events, now) print("\n☀️ The Sun's Decree (Prayer Times)") for event in prayer_events: print(f" {'* ' if next_prayer_event and event['time'] == next_prayer_event['time'] else ' '}{event['name']:<10}: {format_time(event['time'])}") if eph: print("\n🌙 The Moon's Mysteries (Local Time)") for event in moon_events: print(f" {'* ' if next_moon_event and event['time'] == next_moon_event['time'] else ' '}{event['name']:<12}: {format_time(event['time'])}") day_start = now.replace(hour=0, minute=0, second=0, microsecond=0) tide_events = [t for t in all_tide_events if t['time'] < day_start + timedelta(days=1)] if tide_events: last_tide = max([t for t in tide_events if t['time'] <= now], key=lambda x: x['time'], default=None) current_state = "Rising" if last_tide and last_tide['name'] == 'Low Tide' else "Falling" print(f"\n🌊 Inland Tide (Theoretical) - Currently {current_state}") for tide in tide_events: print(f" {'* ' if next_tide_event and tide['time'] == next_tide_event['time'] else ' '}{tide['name']:<12}: {format_time(tide['time'])}") if len(tide_events) <= 3: first_next_tide = next((t for t in all_tide_events if t['time'] >= day_start + timedelta(days=1)), None) if first_next_tide: print(f" {first_next_tide['name']:<12}: {format_time(first_next_tide['time'])} (Tomorrow)") def _to_dt(t): return t.utc_datetime().replace(tzinfo=pytz.utc).astimezone(tz) phase_times, phase_vals = almanac.find_discrete(t0, ts.from_datetime(now + timedelta(days=35)), almanac.moon_phases(eph)) unique_phases = sorted(list({almanac.MOON_PHASES[pv]: _to_dt(pt) for pt, pv in zip(phase_times, phase_vals)}.items()), key=lambda item: item[1]) print('\n Upcoming Primary Phases:') if unique_phases: for i, (name, date) in enumerate(unique_phases[:4]): print(f" {'* ' if i == 0 else ' '}{name:<15}: {date.strftime('%b %d, %Y, %I:%M %p')}") print('\nSub-point & Global Tide Summary:') sun_lat, sun_lon = subpoint_of_body(eph, 'sun', t0) moon_lat, moon_lon = subpoint_of_body(eph, 'moon', t0) sun_cities = analyze_sub_point_locations(sun_lat, sun_lon, eph, ts, 'sun') if sun_lat is not None else None moon_cities = analyze_sub_point_locations(moon_lat, moon_lon, eph, ts, 'moon') if moon_lat is not None else None global_tides = find_global_tide_locations(eph, ts) if sun_cities: print(f" Sun Zenith: {sun_lat:.2f}, {sun_lon:.2f} | Nearest: {sun_cities['nearest']}") print(f" > Most Influenced (North): {sun_cities['most_influenced_north']}") print(f" > Most Influenced (South): {sun_cities['most_influenced_south']}") if moon_cities: print(f"\n Moon Zenith: {moon_lat:.2f}, {moon_lon:.2f} | Nearest: {moon_cities['nearest']}") print(f" > Most Influenced (North): {moon_cities['most_influenced_north']}") print(f" > Most Influenced (South): {moon_cities['most_influenced_south']}") print("\n Global High Tides Near: " + ", ".join(global_tides['high'])) print(" Global Low Tides Near: " + ", ".join(global_tides['low'])) else: print("\n🌙 Moon and Tide data unavailable (ephemeris file not found).") print("-" * 45)