import os import time import requests import folium import pandas as pd from datetime import datetime import streamlit as st from streamlit_folium import st_folium from utils import legend_macro from huggingface_hub import HfApi TOKEN = os.environ.get("HF_TOKEN", None) api = HfApi(token=TOKEN) st.set_page_config(layout="wide", initial_sidebar_state="collapsed") if "sleep_time" not in st.session_state: st.session_state.sleep_time = 2 if "auto_refresh" not in st.session_state: st.session_state.auto_refresh = False auto_refresh = st.sidebar.checkbox("Auto Refresh?", st.session_state.auto_refresh) if auto_refresh: number = st.sidebar.number_input("Refresh rate in seconds", value=st.session_state.sleep_time) st.session_state.sleep_time = number session = requests.Session() @st.cache_data(persist=True) def parse_latlng_from_link(url): try: # extract latitude and longitude from gmaps link if "@" not in url: # We first need to get the redirect URL resp = session.head(url, allow_redirects=True) url = resp.url latlng = url.split('@')[1].split(',')[0:2] return [float(latlng[0]), float(latlng[1])] except Exception as e: print(f"Error parsing latlng from link: {e}") return None def parse_gg_sheet_interventions(url): df = pd.read_csv(url) return df.assign(latlng=df.iloc[:, 3].apply(parse_latlng_from_link)) def parse_gg_sheet(url): url = url.replace("edit#gid=", "export?format=csv&gid=") df = pd.read_csv(url) # parse latlng (column 4) to [lat, lng] def parse_latlng(latlng): try: lat, lng = latlng.split(",") return [float(lat), float(lng)] except Exception as e: print(f"Error parsing latlng: {e}") return None return df.assign(latlng=df.iloc[:, 4].apply(parse_latlng)) df = parse_gg_sheet( "https://docs.google.com/spreadsheets/d/1gYoBBiBo1L18IVakHkf3t1fOGvHWb23loadyFZUeHJs/edit#gid=966953708" ) interventions_df = parse_gg_sheet_interventions( "https://docs.google.com/spreadsheets/d/1eXOTqunOWWP8FRdENPs4cU9ulISm4XZWYJJNR1-SrwY/gviz/tq?tqx=out:csv" ) # select requests headers_mapping = { "إغاثة": "Rescue/إغاثة", "مساعدة طبية": "Medical Assistance/مساعدة طبية", "مأوى": "Shelter/مأوى", "طعام وماء": "Food & Water/طعام وماء", "مخاطر (تسرب الغاز، تلف في الخدمات العامة...)": "Danger/مخاطر (تسرب الغاز، تلف في الخدمات العامة...)", } colors_mapping = { "إغاثة": "red", "مساعدة طبية": "orange", "مأوى": "beige", "طعام وماء": "blue", "مخاطر (تسرب الغاز، تلف في الخدمات العامة...)": "gray", } icon_mapping = { "إغاثة": "bell", # life ring icon for rescue "مساعدة طبية": "heart", # medical kit for medical assistance "مأوى": "home", # home icon for shelter "طعام وماء": "cutlery", # cutlery (fork and knife) for food & water "مخاطر (تسرب الغاز، تلف في الخدمات العامة...)": "Warning" # warning triangle for dangers } options = ["إغاثة", "مساعدة طبية", "مأوى", "طعام وماء", "مخاطر (تسرب الغاز، تلف في الخدمات العامة...)"] selected_options = [] st.markdown("👉 **Choose request type / اختر نوع الطلب**") col1, col2, col3, col4, col5 = st.columns([2, 3, 2, 3, 4]) cols = [col1, col2, col3, col4, col5] for i, option in enumerate(options): checked = cols[i].checkbox(headers_mapping[option], value=True) if checked: selected_options.append(headers_mapping[option]) arabic_options = [e.split("/")[1] for e in selected_options] df['id'] = df.index filtered_df = df[df['ما هي احتياجاتك؟ (أضفها إذا لم يتم ذكرها)'].isin(arabic_options)] selected_headers = [headers_mapping[request] for request in arabic_options] # select interventions st.markdown("👇 **View past or planned interventions / عرض عمليات المساعدة السابقة أو المخطط لها**") show_interventions = st.checkbox("Display Interventions عرض التدخلات", value=True) m = folium.Map( location=[31.228674, -7.992047], zoom_start=8.5, min_zoom=8.5, max_lat=35.628674, min_lat=29.628674, max_lon=-4.992047, min_lon=-10.992047, max_bounds=True, ) if show_interventions: for index, row in interventions_df.iterrows(): status = "Done ✅" if row[interventions_df.columns[5]]!="Intervention prévue dans le futur / Planned future intervention" else "Planned ⌛" color_mk = "green" if row[interventions_df.columns[5]]!="Intervention prévue dans le futur / Planned future intervention" else "pink" intervention_type = row[interventions_df.columns[6]].split("/")[0].strip() org = row[interventions_df.columns[1]] city = row[interventions_df.columns[9]] date = row[interventions_df.columns[4]] intervention_info = f"Status: {status}
Org: {org}
Intervention: {intervention_type}
📅 Date: {date}" if row["latlng"] is None: continue folium.Marker( location=row["latlng"], tooltip=city, popup=folium.Popup(intervention_info, max_width=300), icon=folium.Icon(color=color_mk) ).add_to(m) for index, row in filtered_df.iterrows(): request_type = row['ما هي احتياجاتك؟ (أضفها إذا لم يتم ذكرها)'] display_text = f"Request Type: {request_type}
Id: {row['id']}" icon_name = icon_mapping.get(request_type, 'info-sign') if row["latlng"] is None: continue folium.Marker( location=row["latlng"], tooltip=row[' لأي جماعة / قيادة / دوار تنتمون ؟'] if not pd.isna(row[' لأي جماعة / قيادة / دوار تنتمون ؟']) else None, popup=folium.Popup(display_text, max_width=300), icon=folium.Icon(color=colors_mapping.get(request_type, "blue"), icon=icon_name) ).add_to(m) # Macro to add legend m.get_root().add_child(legend_macro) st_data = st_folium(m, use_container_width=True) if auto_refresh: time.sleep(number) st.experimental_rerun()