Update main.py

main.py

@@ -7,6 +7,8 @@ import pickle
 import rasterio
 import h5py
 from skimage.morphology import disk
+from geopy.extra.rate_limiter import RateLimiter
+from geopy.geocoders import Nominatim
 
 app = FastAPI()
 
@@ -16,9 +18,24 @@ app = FastAPI()
 @app.get("/")
 def root():
     return {"API": "Hail Docker Data"}
+    
+def geocode_address(address):
 
+    try:
+        address2 = address.replace(' ', '+').replace(',', '%2C')
+        df = pd.read_json(
+            f'https://geocoding.geo.census.gov/geocoder/locations/onelineaddress?address={address2}&benchmark=2020&format=json')
+        results = df.iloc[:1, 0][0][0]['coordinates']
+        lat, lon = results['y'], results['x']
+    except:
+        geolocator = Nominatim(user_agent='GTA Lookup')
+        geocode = RateLimiter(geolocator.geocode, min_delay_seconds=2)
+        location = geolocator.geocode(address)
+        lat, lon = location.latitude, location.longitude
+        
+    return lat, lon
 
-def get_hail_data(lat, lon, start_date, end_date, radius_miles, get_max):
+def get_hail_data(address, start_date, end_date, radius_miles, get_max):
 
     start_date = pd.Timestamp(str(start_date)).strftime('%Y%m%d')
     end_date = pd.Timestamp(str(end_date)).strftime('%Y%m%d')
@@ -28,9 +45,13 @@ def get_hail_data(lat, lon, start_date, end_date, radius_miles, get_max):
 
     if len(years) == 0:
         years = [pd.Timestamp(start_date).year]
-
+        
+    # Geocode Address
+    lat, lon= geocode_address(address)
+    
     # Convert Lat Lon to row & col on Array
     transform = pickle.load(open('Data/transform_mrms.pkl', 'rb'))
+    
     row, col = rasterio.transform.rowcol(transform, lon, lat)
 
     files = [
@@ -93,10 +114,10 @@ def get_hail_data(lat, lon, start_date, end_date, radius_miles, get_max):
 
 
 @app.get('/Hail_Docker_Data')
-async def predict(lat: float, lon: float, start_date: str, end_date: str, radius_miles: int, get_max: bool):
+async def predict(address: str, start_date: str, end_date: str, radius_miles: int, get_max: bool):
 
     try:
-        results = get_hail_data(lat, lon, start_date,
+        results = get_hail_data(address, start_date,
                                 end_date, radius_miles, get_max)
     except:
         results = pd.DataFrame({'Date': ['error'], 'Hail_max': ['error']})