import os import time from datetime import datetime import folium import pandas as pd import streamlit as st from huggingface_hub import HfApi from streamlit_folium import st_folium from src.utils import add_latlng_col from src.text_content import ( COLOR_MAPPING, CREDITS_TEXT, HEADERS_MAPPING, ICON_MAPPING, INTRO_TEXT_AR, INTRO_TEXT_EN, INTRO_TEXT_FR, LOGO, REVIEW_TEXT, SLOGAN, ) from src.utils import init_map, parse_gg_sheet TOKEN = os.environ.get("HF_TOKEN", None) REQUESTS_URL = "https://docs.google.com/spreadsheets/d/1gYoBBiBo1L18IVakHkf3t1fOGvHWb23loadyFZUeHJs/edit#gid=966953708" INTERVENTIONS_URL = ( "https://docs.google.com/spreadsheets/d/1eXOTqunOWWP8FRdENPs4cU9ulISm4XZWYJJNR1-SrwY/edit#gid=2089222765" ) api = HfApi(TOKEN) # Initialize Streamlit Config st.set_page_config(layout="wide", initial_sidebar_state="collapsed", page_icon="🤝", page_title="Nt3awnou نتعاونو") # Initialize States 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 # Streamlit functions def display_interventions(interventions_df, m): """Display NGO interventions on the map""" 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) def show_requests(filtered_df, m): """Display victim requests on the map""" for index, row in filtered_df.iterrows(): request_type = row["ما هي احتياجاتك؟ (أضفها إذا لم يتم ذكرها)"] long_lat = row[ "هل يمكنك تقديم الإحداثيات الدقيقة للموقع؟ (ادا كنت لا توجد بعين المكان) متلاً \n31.01837503440344, -6.781405948842175" ] maps_url = f"https://maps.google.com/?q={long_lat}" display_text = f'Request Type: {request_type}
Id: {row["id"]}
Google Maps' 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=COLOR_MAPPING.get(request_type, "blue"), icon=icon_name), ).add_to(m) def display_google_sheet_tables(data_url): """Display the google sheet tables for requests and interventions""" st.markdown( f"""""", unsafe_allow_html=True, ) def display_dataframe(df, drop_cols, data_url, search_id=True, status=False, for_help_requests=False): """Display the dataframe in a table""" col_1, col_2 = st.columns([1, 1]) with col_1: query = st.text_input( "🔍 Search for information / بحث عن المعلومات", key=f"search_requests_{int(search_id)}", ) with col_2: if search_id: id_number = st.number_input( "🔍 Search for an id / بحث عن رقم", min_value=0, max_value=len(filtered_df), value=0, step=1, ) if status: selected_status = st.selectbox( "🗓️ Status / حالة", ["all / الكل", "Done / تم", "Planned / مخطط لها"], key="status", ) if query: # Filtering the dataframe based on the query mask = df.apply(lambda row: row.astype(str).str.contains(query).any(), axis=1) display_df = df[mask] else: display_df = df display_df = display_df.drop(drop_cols, axis=1) if search_id and id_number: display_df = display_df[display_df["id"] == id_number] if status: target = "Pouvez-vous nous préciser si vous êtes déjà intervenus ou si vous prévoyez de le faire | Tell us if you already made the intervention, or if you're planning to do it" if selected_status == "Done / تم": display_df = display_df[display_df[target] == "Intervention déjà passée / Past intevention"] elif selected_status == "Planned / مخطط لها": display_df = display_df[display_df[target] != "Intervention déjà passée / Past intevention"] st.dataframe(display_df, height=500) st.markdown( f"To view the full Google Sheet for advanced filtering go to: {data_url} **لعرض الورقة كاملة، اذهب إلى**" ) # if we want to check hidden contact information if for_help_requests: st.markdown( f"We are hiding contact information to protect the privacy of the victims. If you are an NGO and want to contact the victims, please contact us at nt3awnoumorocco@gmail.com", ) # arabic needs rtl st.markdown( f"""
nt3awnoumorocco@gmail.com نحن نخفي معلومات الاتصال لحماية خصوصية الضحايا. إذا كنت جمعية وتريد الاتصال بالضحايا، يرجى الاتصال بنا على
""", unsafe_allow_html=True, ) def id_review_submission(): """Id review submission form""" st.subheader("🔍 Review of requests") st.markdown(REVIEW_TEXT) id_to_review = st.number_input("Enter id / أدخل الرقم", min_value=0, max_value=len(df), value=0, step=1) reason_for_review = st.text_area("Explain why / أدخل سبب المراجعة") if st.button("Submit / أرسل"): if reason_for_review == "": st.error("Please enter a reason / الرجاء إدخال سبب") else: filename = f"review_id_{id_to_review}_{datetime.now().strftime('%Y-%m-%d_%H-%M-%S')}.txt" with open(filename, "w") as f: f.write(f"id: {id_to_review}, explanation: {reason_for_review}\n") api.upload_file( path_or_fileobj=filename, path_in_repo=filename, repo_id="nt3awnou/review_requests", repo_type="dataset", ) st.success("Submitted at https://huggingface.co/datasets/nt3awnou/review_requests/ تم الإرسال") # Logo and Title st.markdown(LOGO, unsafe_allow_html=True) # st.title("Nt3awnou نتعاونو") st.markdown(SLOGAN, unsafe_allow_html=True) # Load data and initialize map with plugins df = parse_gg_sheet(REQUESTS_URL) df = add_latlng_col(df, process_column=15) interventions_df = parse_gg_sheet(INTERVENTIONS_URL) interventions_df = add_latlng_col(interventions_df, process_column=12) m = init_map() # Selection of requests options = [ "إغاثة", "مساعدة طبية", "مأوى", "طعام وماء", "مخاطر (تسرب الغاز، تلف في الخدمات العامة...)", ] selected_options = [] # with tab_en: # st.markdown("👉 **Choose request type**") # with tab_ar: # st.markdown("👉 **اختر نوع الطلب**") # with tab_fr: # st.markdown("👉 **Choisissez le type de demande**") st.markdown("👉 **Choose request type | Choissisez le type de demande | 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(option) df["id"] = df.index filtered_df = df[df["ما هي احتياجاتك؟ (أضفها إذا لم يتم ذكرها)"].isin(selected_options)] selected_headers = [HEADERS_MAPPING[request] for request in selected_options] # Selection of interventions show_interventions = st.checkbox( "Display Interventions | عرض عمليات المساعدة | Afficher les interventions", value=True, ) if show_interventions: # print(interventions_df.columns) display_interventions(interventions_df, m) # Show requests show_requests(filtered_df, m) st_data = st_folium(m, use_container_width=True) tab_ar, tab_en, tab_fr = st.tabs(["العربية", "English", "Français"]) with tab_en: st.markdown(INTRO_TEXT_EN, unsafe_allow_html=True) with tab_ar: st.markdown(INTRO_TEXT_AR, unsafe_allow_html=True) with tab_fr: st.markdown(INTRO_TEXT_FR, unsafe_allow_html=True) # Requests table st.divider() st.subheader("📝 **Table of requests / جدول الطلبات**") drop_cols = [ "(عند الامكان) رقم هاتف شخص موجود في عين المكان", "الرجاء الضغط على الرابط التالي لمعرفة موقعك إذا كان متاحا", "GeoStamp", "GeoCode", "GeoAddress", "Status", ] display_dataframe(filtered_df, drop_cols, REQUESTS_URL, search_id=True, for_help_requests=True) # Interventions table st.divider() st.subheader("📝 **Table of interventions / جدول التدخلات**") display_dataframe( interventions_df, [], # We show NGOs contact information INTERVENTIONS_URL, search_id=False, status=True, for_help_requests=False, ) # Submit an id for review st.divider() id_review_submission() # Donations can be made to the gouvernmental fund under the name st.divider() st.subheader("📝 **Donations / التبرعات / Dons**") tab_ar, tab_en, tab_fr = st.tabs(["العربية", "English", "Français"]) with tab_en: st.markdown( """

The official bank account dedicated to tackle the consequences of the earthquake is:

Account number:

126

RIB: 001-810-0078000201106203-18
For the money transfers coming from outside Morocco
IBAN: MA64001810007800020110620318
""", unsafe_allow_html=True, ) with tab_ar: st.markdown( """

الحساب البنكي الرسمي المخصص لمواجهة عواقب الزلزال

رقم الحساب

126

RIB: 001-810-0078000201106203-18
للتحويلات القادمة من خارج المغرب
IBAN: MA64001810007800020110620318
""", unsafe_allow_html=True, ) with tab_fr: st.markdown( """

Le compte bancaire officiel dédié à la lutte contre les conséquences du séisme est le suivant:

Numéro de compte:

126

RIB: 001-810-0078000201106203-18
Pour les transferts d'argent en provenance de l'étranger
IBAN: MA64001810007800020110620318
""", unsafe_allow_html=True, ) # Credits st.markdown( CREDITS_TEXT, unsafe_allow_html=True, ) if auto_refresh: time.sleep(number) st.experimental_rerun()