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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)
show_interventions = 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"<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)
for index, row in filtered_df.iterrows():
request_type = row['ما هي احتياجاتك؟ (أضفها إذا لم يتم ذكرها)']
display_text = f"<b>Request Type:</b> {request_type}<br><b>Id:</b> {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() |