Spaces:
Running
on
CPU Upgrade
Running
on
CPU Upgrade
File size: 10,780 Bytes
549a2cc 5c8a315 b10dbaa 5c8a315 549a2cc a04f639 5c8a315 b10dbaa 5c8a315 549a2cc 5c8a315 a8969c3 b10dbaa 5c8a315 01defef b10dbaa 01defef 1df563c b10dbaa 5c8a315 b10dbaa 5c8a315 b10dbaa 5c8a315 5f1dd3f 5c8a315 a472331 01defef 5c8a315 ebc2ece 5c8a315 ebc2ece 5c8a315 ebc2ece 5c8a315 6d4d03f 86f908d 5c8a315 6d4d03f b10dbaa 5c8a315 bfa9224 5c8a315 bfa9224 5c8a315 bfa9224 5c8a315 bfa9224 5c8a315 5f1dd3f 5c8a315 8a8cff3 5f1dd3f a472331 8a8cff3 5c8a315 8a8cff3 5f1dd3f 8a8cff3 5c8a315 b10dbaa 5c8a315 391cfe9 886bf76 6d4d03f 5c8a315 4482a4e 5c8a315 ebc2ece b10dbaa bfa9224 549a2cc 5c8a315 01defef 49d14ca 5c8a315 49d14ca b10dbaa 5c8a315 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 |
import os
import time
from datetime import datetime
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,
REVIEW_TEXT_2,
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:
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(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):
"""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**"
)
def id_review_submission():
"""Id review submission form"""
st.subheader("🔍 Review of requests")
st.markdown(REVIEW_TEXT)
st.markdown(REVIEW_TEXT_2)
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)
st.subheader("📝 **Table of requests / جدول الطلبات**")
# Requests table
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)
# Interventions table
st.subheader("📝 **Table of interventions / جدول التدخلات**")
display_dataframe(
interventions_df,
["Informations de Contact | Contact Information"],
INTERVENTIONS_URL,
search_id=False,
status=True,
)
# 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()
|