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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"<b>Status:</b> {status}<br><b>Org:</b> {org}<br><b>Intervention:</b> {intervention_type}<br><b>📅 Date:</b> {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'<b>Request Type:</b> {request_type}<br><b>Id:</b> {row["id"]}<br><a href="{maps_url}" target="_blank" rel="noopener noreferrer"><b>Google Maps</b></a>'
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"""<iframe src="{data_url}" width="100%" height="600px"></iframe>""",
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"""
<div style="text-align: left;">
<a href="mailto:nt3awnoumorocco@gmail.com">nt3awnoumorocco@gmail.com</a> نحن نخفي معلومات الاتصال لحماية خصوصية الضحايا. إذا كنت جمعية وتريد الاتصال بالضحايا، يرجى الاتصال بنا على
</div>
""",
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(
"""
<div style="text-align: center;">
<h4>The official bank account dedicated to tackle the consequences of the earthquake is:</h4>
<b>Account number:</b>
<h2>126</h2>
<b>RIB:</b> 001-810-0078000201106203-18
<br>
<b>For the money transfers coming from outside Morocco</b>
<br>
<b>IBAN:</b> MA64001810007800020110620318
<br>
""",
unsafe_allow_html=True,
)
with tab_ar:
st.markdown(
"""
<div style="text-align: center;">
<h4>الحساب البنكي الرسمي المخصص لمواجهة عواقب الزلزال</h4>
<b>رقم الحساب</b>
<h2>126</h2>
<b>RIB:</b> 001-810-0078000201106203-18
<br>
<b>للتحويلات القادمة من خارج المغرب</b>
<br>
<b>IBAN:</b> MA64001810007800020110620318
<br>
</div>
""",
unsafe_allow_html=True,
)
with tab_fr:
st.markdown(
"""
<div style="text-align: center;">
<h4>Le compte bancaire officiel dédié à la lutte contre les conséquences du séisme est le suivant:</h4>
<b>Numéro de compte:</b>
<h2>126</h2>
<b>RIB:</b> 001-810-0078000201106203-18
<br>
<b>Pour les transferts d'argent en provenance de l'étranger</b>
<br>
<b>IBAN:</b> MA64001810007800020110620318
<br>
""",
unsafe_allow_html=True,
)
# Credits
st.markdown(
CREDITS_TEXT,
unsafe_allow_html=True,
)
if auto_refresh:
time.sleep(number)
st.experimental_rerun()
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