loubnabnl's picture
loubnabnl HF staff
Update app.py
bb85d5e
raw
history blame
8.39 kB
import os
import time
import folium
import pandas as pd
import requests
import streamlit as st
from folium import plugins
from huggingface_hub import HfApi
from streamlit_folium import st_folium
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")
# 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
# Session for Requests
session = requests.Session()
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
# Utility functions
@st.cache_data(persist=True)
def parse_latlng_from_link(url):
try:
# extract latitude and longitude from gmaps link
if "@" not in 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):
url = url.replace("edit#gid=", "export?format=csv&gid=")
print(url)
df = pd.read_csv(url, on_bad_lines="skip")
return df.assign(latlng=df.iloc[:, 3].apply(parse_latlng_from_link))
# 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():
"""Display the google sheet tables for requests and interventions"""
st.subheader("📝 **Table of requests / جدول الطلبات**")
st.markdown(
f"""<iframe src="{REQUESTS_URL}" width="100%" height="600px"></iframe>""",
unsafe_allow_html=True,
)
st.subheader("📝 **Table of interventions / جدول التدخلات**")
st.markdown(
f"""<iframe src="{INTERVENTIONS_URL}" width="100%" height="600px"></iframe>""",
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)
# Language tabs
st.sidebar.title("Language / اللغة")
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)
# Load data and initialize map with plugins
df = parse_gg_sheet(REQUESTS_URL)
interventions_df = parse_gg_sheet_interventions(INTERVENTIONS_URL)
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**")
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:
display_interventions(interventions_df, m)
# Show requests
show_requests(filtered_df, m)
st_data = st_folium(m, use_container_width=True)
# Google Sheet Tables
display_google_sheet_tables()
# Submit an id for review
id_review_submission()
# Credits
st.markdown(
CREDITS_TEXT,
unsafe_allow_html=True,
)
if auto_refresh:
time.sleep(number)
st.experimental_rerun()