import streamlit as st 
import pandas as pd 
from App.class_input_box.input_box import *
from App.functions_rupture.functions_gestion import *
from App.utils.divers_function import *
from App.utils.filter_dataframe import *

from streamlit_extras.chart_container import chart_container


st.title("Gestion des ruptures ")

input_box = InputsBox()
data = input_box.get_data()

try:
    if data.shape[0] != 0 :
        st.header("Data")

        st.dataframe(data)

        "## Filters"

        col1, col2 = st.columns(2)

        with col1 :
            product_id = input_box.get_product_id()

        with col2 :
            class_id = input_box.get_class_id()

        col1, col2 = st.columns(2)

        with col1 :
            min_product_id = input_box.valid_produict_id()

        with col2 :
            vaind_class_id = input_box.valid_class_id()

        conditions = input_box.conditions()

        if st.button("RUN ", key="run_button"):
            data = valide_key(data, product_id, class_id, min_product_id, vaind_class_id )
            Country, merged = nouvelle_data(data, 
                                            str(product_id), 
                                            str(class_id))

            merged_final = finale_merged(merged, 
                                         Country, 
                                         product_id, 
                                         class_id)            

            if conditions["Show data with ratios"]:
                st.subheader("Show data with ratios")
                st.dataframe(merged_final)

                csv = convert_df(merged_final)
                st.download_button(label="Download data as CSV",
                                   data=csv,
                                   file_name='sample_df.csv',
                                   mime='text/csv',)

            data_countries_ratio = cond_pays_proportion(merged_final, 
                                                        conditions["Number of countries"], 
                                                        conditions["Proportion"], 
                                                        product_id)

            df = supprime_country(data_countries_ratio)
            csv = convert_df(df)

            """## The data below is filtered as follows: """
            "- Number of countries greater than or equal to ", conditions["Number of countries"]
            "- The proportion with the highest ", class_id ," is greater than or equal to ",conditions["Proportion"]

            finale_df = Merger(data,
                               df, 
                               product_id, 
                               class_id)
            
            tab1, tab2 = st.tabs(["Data without decision-making", "Data with proposed changes"])
            
            with tab1 :
                st.subheader("Data without decision-making")
                st.dataframe(df)
                st.download_button(label="Download data as CSV",
                                   data=csv,
                                   file_name='sample_df.csv',
                                   mime='text/csv',)
            
            with tab2 :
                st.subheader("Data with proposed changes")
                st.dataframe(finale_df)
                csv_f = convert_df(finale_df)
                st.download_button(label="Download data as CSV",
                                       data=csv_f,
                                       file_name='sample_df.csv',
                                       mime='text/csv',)
                
            "## Country priority "

            priority_data = cond_pays_priorite(merged_final, product_id)

            tab1, tab2 = st.tabs(["Data without decision-making", "Data with proposed changes"])

            with tab1 :
                st.subheader("Data without decision-making")
                st.dataframe(priority_data)
                csv_f = convert_df(priority_data)
                st.download_button(label="Download data as CSV",
                                       data=csv_f,
                                       file_name='sample_df.csv',
                                       mime='text/csv',)
                
            with tab2 :
                "to do"

except:
    pass
    st.write("An error occured. Please check your inputs.")