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61b4af1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 | import pandas as pd
import requests
import difflib
import logging
from io import StringIO
# from weather_collector import DistrictService # Not strictly needed if we copy overrides
# Configure logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
# Combined Manual Overrides (Original + 22 Recovered + 7 New Reported)
# Keys are Lowercase for easier matching
MANUAL_FIXES = {
# Original from weather_collector.py
'banka': {'lat': 24.88, 'lon': 86.92},
'bargarh': {'lat': 21.33, 'lon': 83.62},
'birbhum': {'lat': 23.91, 'lon': 87.52},
'hamirpur': {'lat': 25.95, 'lon': 80.15},
'kullu': {'lat': 31.95, 'lon': 77.10},
'mandi': {'lat': 31.58, 'lon': 76.91},
'maharajganj': {'lat': 27.14, 'lon': 83.56},
'paschim bardhaman': {'lat': 23.68, 'lon': 86.98},
'pratapgarh': {'lat': 25.93, 'lon': 81.60},
'hooghly': {'lat': 22.90, 'lon': 88.39},
'keonjhar': {'lat': 21.63, 'lon': 85.58},
'khandwa': {'lat': 21.83, 'lon': 76.35},
'khargone': {'lat': 21.83, 'lon': 75.61},
'mewat': {'lat': 28.10, 'lon': 77.00},
'nawanshahr': {'lat': 31.12, 'lon': 76.12},
'badaun': {'lat': 28.03, 'lon': 79.13},
'bulandshahar': {'lat': 28.40, 'lon': 77.85},
'coochbehar': {'lat': 26.32, 'lon': 89.45},
'davangere': {'lat': 14.46, 'lon': 75.92},
'delhi': {'lat': 28.61, 'lon': 77.20},
'janjgir': {'lat': 22.01, 'lon': 82.57},
'kanpur': {'lat': 26.44, 'lon': 80.33},
'khurda': {'lat': 20.18, 'lon': 85.62},
'mumbai': {'lat': 19.07, 'lon': 72.87},
'palakad': {'lat': 10.78, 'lon': 76.65},
'sholapur': {'lat': 17.65, 'lon': 75.90},
'the nilgiris': {'lat': 11.41, 'lon': 76.69},
'thiruchirappalli': {'lat': 10.79, 'lon': 78.70},
'thirunelveli': {'lat': 8.71, 'lon': 77.75},
'thiruvannamalai': {'lat': 12.22, 'lon': 79.07},
'thiruvarur': {'lat': 10.76, 'lon': 79.63},
'villupuram': {'lat': 11.94, 'lon': 79.48},
'amarawati': {'lat': 20.93, 'lon': 77.75},
'ambedkarnagar': {'lat': 26.41, 'lon': 82.39},
'anupur': {'lat': 23.10, 'lon': 81.69},
'bangalore': {'lat': 12.97, 'lon': 77.59},
# The 22 Manual Recovered
"bhadradri kothagudem": {"lat": 17.55, "lon": 80.62},
"chattrapati sambhajinagar": {"lat": 19.88, "lon": 75.32},
"chhota udaipur": {"lat": 22.31, "lon": 74.01},
"cuddapah": {"lat": 14.48, "lon": 78.82},
"deedwana kuchaman": {"lat": 27.40, "lon": 74.58},
"dharashiv(usmanabad)": {"lat": 18.19, "lon": 76.04},
"east jaintia hills": {"lat": 25.36, "lon": 92.37},
"gir somnath": {"lat": 20.91, "lon": 70.37},
"gopalgang": {"lat": 26.47, "lon": 84.43},
"jhunjhunu": {"lat": 28.13, "lon": 75.40},
"kotputli- behror": {"lat": 27.70, "lon": 76.20},
"madikeri(kodagu)": {"lat": 12.43, "lon": 75.75},
"mansa": {"lat": 29.99, "lon": 75.38},
"neem ka thana": {"lat": 27.74, "lon": 75.78},
"nongpoh (r-bhoi)": {"lat": 25.87, "lon": 91.83},
"purba bardhaman": {"lat": 23.26, "lon": 87.86},
"south west garo hills": {"lat": 25.47, "lon": 89.93},
"south west khasi hills": {"lat": 25.32, "lon": 91.29},
"tsemenyu": {"lat": 26.05, "lon": 94.27},
"tuticorin": {"lat": 8.76, "lon": 78.13},
"unokoti": {"lat": 24.33, "lon": 92.00},
"west chambaran": {"lat": 27.15, "lon": 84.35},
# New Fixes for Reported 0.0s
'bhojpur': {'lat': 25.47, 'lon': 84.54},
'bilaspur': {'lat': 22.08, 'lon': 82.15}, # CG
'banda': {'lat': 25.49, 'lon': 80.34},
'fatehpur': {'lat': 25.92, 'lon': 80.81},
'lalitpur': {'lat': 24.69, 'lon': 78.42},
'vaishali': {'lat': 25.75, 'lon': 85.42},
'hassan': {'lat': 13.01, 'lon': 76.10}
}
def generate_all_coordinates():
# 1. Download Master List for fuzzy matching
url = "https://raw.githubusercontent.com/recurze/IndianCities/master/india_places.csv"
logger.info(f"Downloading master list from {url}...")
try:
response = requests.get(url)
response.raise_for_status()
master_df = pd.read_csv(StringIO(response.text))
master_df.columns = [c.lower() for c in master_df.columns]
master_df['latitude'] = pd.to_numeric(master_df['latitude'], errors='coerce')
master_df['longitude'] = pd.to_numeric(master_df['longitude'], errors='coerce')
master_df = master_df.dropna(subset=['latitude', 'longitude'])
place_map = {}
def add_to_map(name, row):
if not isinstance(name, str): return
n = name.strip().lower()
if n not in place_map:
place_map[n] = {'lat': row['latitude'], 'lon': row['longitude']}
for _, row in master_df.iterrows():
if 'district' in row: add_to_map(row['district'], row)
if 'city' in row: add_to_map(row['city'], row)
possible_names = list(place_map.keys())
logger.info(f"Loaded {len(place_map)} names for fuzzy matching.")
except Exception as e:
logger.error(f"Failed to load master list: {e}")
return
# 2. Load Targets
districts_file = 'districts.txt'
with open(districts_file, 'r') as f:
lines = [l.strip() for l in f if l.strip()]
if lines and lines[0].lower() == 'district_name':
targets = lines[1:]
else:
targets = lines
logger.info(f"Loaded {len(targets)} target districts.")
final_list = []
for district in targets:
d_lower = district.lower().strip()
lat, lon = None, None
# A. Manual Fixes
if d_lower in MANUAL_FIXES:
coords = MANUAL_FIXES[d_lower]
lat, lon = coords['lat'], coords['lon']
# logger.info(f"Manual override: {district}")
# B. Exact Match in Place Map
elif d_lower in place_map:
lat = place_map[d_lower]['lat']
lon = place_map[d_lower]['lon']
# C. Fuzzy Match
else:
matches = difflib.get_close_matches(d_lower, possible_names, n=1, cutoff=0.6)
if matches:
best = matches[0]
lat = place_map[best]['lat']
lon = place_map[best]['lon']
logger.info(f"Fuzzy match: {district} -> {best}")
if lat is not None and lon is not None:
if lat == 0.0 and lon == 0.0:
logger.warning(f"Found 0.0, 0.0 for {district}. Please verify.")
final_list.append({'district': district, 'lat': lat, 'lon': lon})
else:
logger.error(f"FAILED to find coordinates for: {district}")
# 4. Save
out_df = pd.DataFrame(final_list)
out_file = 'alldistrictsCoordinates.csv'
out_df.to_csv(out_file, index=False)
logger.info(f"Saved {len(final_list)} coordinates to {out_file}")
if len(final_list) == len(targets):
logger.info("SUCCESS: 100% Coverage.")
else:
logger.warning(f"WARNING: Coverage {len(final_list)}/{len(targets)}")
if __name__ == "__main__":
generate_all_coordinates()
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