Create app.py

app.py

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+import numpy as np
+import streamlit as st
+import requests
+import pydeck as pdk
+import pandas as pd
+import geopandas as gpd
+import plotly.express as px
+import folium
+import webbrowser
+from shapely.geometry import Point
+from folium import plugins
+from streamlit_folium import st_folium
+
+def load_polygon(filepath):
+    return gpd.read_file(filepath)
+path='Z:/Shared/Axeria Shared/Pricing/Immopolis Pricing Review/DATA/'
+# Polygon1 = load_polygon(path + 'risk_zones.shp')
+# Polygon2 = load_polygon(path + 'Flooding/n_inondable_01_01for_s.shp')
+# Polygon3 = load_polygon(path + 'ZUS/ZUS_FRM_BDA09_L93.shp')
+#
+
+# Initialize polygons if not already in session state
+if 'polygons' not in st.session_state:
+    st.session_state.polygons = {
+        "Polygon1": load_polygon(path+'risk_zones.shp'),
+        "Polygon2": load_polygon(path+'Flooding/n_inondable_01_01for_s.shp'),
+        "Polygon3": load_polygon(path+'ZUS/ZUS_FRM_BDA09_L93.shp')
+    }
+
+if 'polygons'  in st.session_state:
+    st.session_state.polygons["Polygon1"]['geometry'] = st.session_state.polygons["Polygon1"]['geometry'].to_crs(epsg=4326)
+    st.session_state.polygons["Polygon2"]['geometry'] = st.session_state.polygons["Polygon2"]['geometry'].to_crs(epsg=4326)
+    st.session_state.polygons["Polygon3"]['geometry'] = st.session_state.polygons["Polygon3"]['geometry'].to_crs(epsg=4326)
+
+    #Polygon1['geometry'] = Polygon1['geometry'].to_crs(epsg=4326)
+    #Polygon2=load_polygon(path+'Flooding/n_inondable_01_01for_s.shp')
+    # Polygon1=load_polygon(path+'risk_zones.shp')
+    # Polygon1['geometry'] = Polygon1['geometry'].to_crs(epsg=4326)
+    # Polygon2=load_polygon(path+'Flooding/n_inondable_01_01for_s.shp')
+    # Polygon3=load_polygon(path+'ZUS/ZUS_FRM_BDA09_L93.shp')
+
+# # Function to plot an interactive histogram
+# # fig = px.histogram(polygon_gdf['poverty'], nbins=20)
+# # st.plotly_chart(fig)
+# fig = px.ecdf(polygon_gdf['poverty'])
+# fig.show()
+# # # #28% --> 5% of squares
+# # #
+# # #
+# fig = px.ecdf(polygon_gdf['densite'])
+#  # #9000 --> 5% of squares
+# fig.show()
+# #
+# #
+# #
+# # #Load geographical layers
+#
+
+# zus=gpd.read_file(path+'ZUS/ZUS_FRM_BDA09_L93.shp')
+# polygon_gdf = gpd.read_file(path+'Geo_metropole/Filosofi2017_carreaux_nivNaturel_met.shp')
+# polygon_gdf2 = gpd.read_file(path+'Filosofi2017_carreaux_1km_shp/Filosofi2017_carreaux_1km_met.shp')
+# polygon_gdf2['densite']=polygon_gdf2['Ind']
+# polygon_gdf2['poverty']=polygon_gdf2['Men_pauv']/polygon_gdf2['Men']
+# polygon_gdf['tmaille']=pd.to_numeric(polygon_gdf['tmaille'])
+# polygon_gdf['tmaillem2']=polygon_gdf['tmaille']**2
+# polygon_gdf['densite']=1000000*polygon_gdf['Ind']/polygon_gdf['tmaillem2']
+# polygon_gdf['poverty']=polygon_gdf['Men_pauv']/polygon_gdf['Men']
+
+
+# risk_zones2=polygon_gdf2[polygon_gdf2.poverty>=0.30]
+# risk_zones2=risk_zones2[risk_zones2.densite>=7000]
+#risk_zones2.to_file(filename=path+'risk_zones2.shp', driver='ESRI Shapefile')
+
+# risk_zones=gpd.read_file(filename=path+'risk_zones.shp')
+# flooding = gpd.read_file(path+'Flooding/n_inondable_01_01for_s.shp')
+#
+# #
+# #
+# # #FLooding zones
+#risk_zones=polygon_gdf[polygon_gdf.poverty>=0.28]
+# risk_zones=risk_zones[risk_zones.densite>=7000]
+#
+# risk_zones.to_file(filename=path+'risk_zones.shp', driver='ESRI Shapefile')
+#
+# # #
+# m =folium.Map(location = [48.885805,2.366191], zoom_start = 6)
+# folium.GeoJson(Polygon2[Polygon2.index<1000],color='blue').add_to(m)
+#folium.CircleMarker([48.885805, 2.366191],radius=1,color='red').add_to(m)
+# folium.GeoJson(flooding[flo,color='yellow').add_to(m)
+# #folium.GeoJson(risk_zones2,color='orange').add_to(m)
+# folium.GeoJson(zus).add_to(m)
+# #
+# #
+# # # m.save(path+"map2.html")
+# # # webbrowser.open_new_tab(path+"map2.html")
+# # #
+# # #
+# policies = pd.read_pickle(path+"DB_immoplus.pkl")
+# geometry = [Point(xy) for xy in zip(policies['longitude'], policies['latitude'])]
+# policies_geo = gpd.GeoDataFrame(policies, geometry=geometry,crs="EPSG:4326")
+# #
+# large_claims=policies_geo[policies_geo.Charge>20000]
+# large_claims=large_claims.dropna(subset=['latitude'])
+# # #
+# for arr in large_claims["geometry"]:
+#      lat=arr.y
+#      lon=arr.x
+#      folium.CircleMarker([lat, lon],radius=1,color='red').add_to(m)
+# m.save(path+"map2.html")
+# webbrowser.open_new_tab(path+"map2.html")
+#
+#
+# sum(risk_zones['tmaille'])/sum(polygon_gdf['tmaille'])*100
+# sum(risk_zones['Ind'])/sum(polygon_gdf['Ind'])*100
+
+# #
+# #
+# #
+# # flooding["zone_inond_freq"]=1
+# # zus['flag_ZUS']=1
+# # Function to get address suggestions from the Autocomplete API
+def create_geodataframe(longitude, latitude):
+    geometry = [Point(longitude, latitude)]
+    gdf = gpd.GeoDataFrame(geometry=geometry, crs="EPSG:4326")
+    return gdf
+
+def get_address_suggestions(query):
+    if not query:
+        return []
+
+    url = "https://api-adresse.data.gouv.fr/search/"
+    params = {'q': query, 'autocomplete': 1, 'limit': 5}
+    response = requests.get(url, params=params)
+
+    if response.status_code == 200:
+        data = response.json()
+        suggestions = [{'label': feature['properties']['label'], 'coordinates': feature['geometry']['coordinates']}
+                       for feature in data['features']]
+        return suggestions
+    else:
+        return []
+
+
+# Function to create a map
+def create_map(latitude, longitude):
+    map_data = pd.DataFrame({
+        'lat': [latitude],
+        'lon': [longitude]
+    })
+
+    st.pydeck_chart(pdk.Deck(
+        map_style='mapbox://styles/mapbox/light-v9',
+        initial_view_state=pdk.ViewState(
+            latitude=latitude,
+            longitude=longitude,
+            zoom=11,
+            pitch=50,
+        ),
+        layers=[
+            pdk.Layer(
+                'ScatterplotLayer',
+                data=map_data,
+                get_position='[lon, lat]',
+                get_color='[200, 30, 0, 160]',
+                get_radius=200,
+            ),
+        ],
+    ))
+
+
+# Streamlit app layout
+def main():
+    st.title("Immopolis Adress validation APP")
+
+    # Session state to store the current suggestions
+    if 'suggestions' not in st.session_state:
+        st.session_state.suggestions = []
+
+    # Text input for address with on_change callback
+    query = st.text_input("Enter your address", "", key="query")
+
+    # Update suggestions when query changes
+    st.session_state.suggestions = get_address_suggestions(query)
+
+    # Display autocomplete suggestions
+    if query:
+        selected_suggestion = st.selectbox("Did you mean:", [s['label'] for s in st.session_state.suggestions], index=0,
+                                           key="selected_suggestion")
+    else:
+        selected_suggestion = ""
+
+
+    if selected_suggestion:
+        selected_data = next((item for item in st.session_state.suggestions if item['label'] == selected_suggestion),
+                             None)
+        if selected_data and 'coordinates' in selected_data:
+            longitude, latitude = selected_data['coordinates']
+            st.write(f"Latitude: {latitude}, Longitude: {longitude}")
+            #m = folium.Map(location=[longitude, latitude], zoom_start=6)
+            gdf = create_geodataframe(longitude, latitude)
+            gdf['geometry'] = gdf['geometry'].to_crs(epsg=4326)
+            st.write(gdf)
+            #polygon_name1 = gdf.within(st.session_state.polygons["Polygon1"])
+            #st.write(polygon_name1[polygon_name1.isna()])
+            #polygon_name2 = gdf.within(st.session_state.polygons["Polygon2"])
+            polygon_name1=gpd.sjoin(gdf, st.session_state.polygons["Polygon1"], how="left", predicate="within")['index_right']
+            st.write(polygon_name1)
+            polygon_name2=gpd.sjoin(gdf, st.session_state.polygons["Polygon2"], how="left", predicate="within")['index_right']
+            st.write(polygon_name2)
+
+            polygon_name3=gpd.sjoin(gdf, st.session_state.polygons["Polygon3"], how="left", predicate="within")['index_right']
+            st.write(polygon_name3)
+
+            #st.write(polygon_name2)
+            #st.write(np.isnan(polygon_name2[0]))
+
+            #st.write(polygon_name2)
+            #latitude=48.885805
+            # longitude=2.366191
+            #polygon_name3 = gdf.within(st.session_state.polygons["Polygon3"])
+#           folium.GeoJson(risk_zones).add_to(m)
+            #gdf=policies_geo[1:1]
+            #m =folium.Map(location = [longitude, latitude], zoom_start = 10)
+            m=folium.Map([gdf['geometry'].y, gdf['geometry'].x],zoom_start = 15)
+            folium.CircleMarker([gdf['geometry'].y, gdf['geometry'].x], radius=1, color='red').add_to(m)
+            #folium.GeoJson(st.session_state.polygons["Polygon2"], color='blue').add_to(m)
+            folium.GeoJson(st.session_state.polygons["Polygon3"], color='orange').add_to(m)
+
+            if not np.isnan(polygon_name1[0]):
+                folium.GeoJson(st.session_state.polygons["Polygon1"][st.session_state.polygons["Polygon1"].index==polygon_name1[0]],color='yellow').add_to(m)
+            if not np.isnan(polygon_name2[0]):
+                folium.GeoJson(st.session_state.polygons["Polygon2"][st.session_state.polygons["Polygon2"].index==polygon_name2[0]],color='blue').add_to(m)
+            if not np.isnan(polygon_name3[0]):
+                folium.GeoJson(st.session_state.polygons["Polygon3"][st.session_state.polygons["Polygon3"].index==polygon_name3[0]],color='orange').add_to(m)
+
+            point = Point(longitude, latitude)
+            st_folium(m, width=700, height=500)
+
+
+            if not np.isnan(polygon_name1[0]):
+                st.markdown(f"Address is High risk zone", unsafe_allow_html=True)
+
+            if not np.isnan(polygon_name2[0]):
+                st.markdown(f"Address is in flooding area", unsafe_allow_html=True)
+
+            if not np.isnan(polygon_name3[0]):
+                st.markdown(f"Address is in sensitive area", unsafe_allow_html=True)
+
+            if np.isnan(polygon_name1[0]) and np.isnan(polygon_name2[0])  and np.isnan(polygon_name3[0]):
+                st.markdown(f"Risk check OK", unsafe_allow_html=True)
+
+
+# Run the app
+if __name__ == "__main__":
+    main()