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[6]] != "Intervention prévue dans le futur / Planned future intervention"
            else "Planned ⌛"
        )
        color_mk = (
            "green"
            if row[interventions_df.columns[6]] != "Intervention prévue dans le futur / Planned future intervention"
            else "pink"
        )
        intervention_type = row[interventions_df.columns[7]].split("/")[0].strip()
        org = row[interventions_df.columns[1]]
        city = row[interventions_df.columns[10]]
        date = row[interventions_df.columns[5]]
        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**"
    )
    # if we want to check hidden contact information
    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)

# Interventions table
st.divider()
st.subheader("📝 **Table of interventions / جدول التدخلات**")
display_dataframe(
    interventions_df,
    # ["Informations de Contact | Contact Information"],
    [], # We show NGOs contact information
    INTERVENTIONS_URL,
    search_id=False,
    status=True,
)

# Submit an id for review
st.divider()
id_review_submission()


# Credits
st.markdown(
    CREDITS_TEXT,
    unsafe_allow_html=True,
)
if auto_refresh:
    time.sleep(number)
    st.experimental_rerun()