# set path
import glob, os, sys; 
sys.path.append('../utils')

#import needed libraries
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import streamlit as st
from st_aggrid import AgGrid
import logging
logger = logging.getLogger(__name__)
from io import BytesIO
import xlsxwriter
import plotly.express as px
from pandas.api.types import (
    is_categorical_dtype,
    is_datetime64_any_dtype,
    is_numeric_dtype,
    is_object_dtype,
    is_list_like)


           
            
def targets():
    if 'key1' in st.session_state:
        df = st.session_state['key1'].copy()
        idx = df['NetzeroLabel_Score'].idxmax()
        netzero_placeholder = df.loc[idx, 'text']
        df = df.drop(df.filter(regex='Score').columns, axis=1)
        df = df[df.TargetLabel==True].reset_index(drop=True)
        df['keep'] = True
        st.session_state['target_hits'] = df
        st.session_state['netzero'] = netzero_placeholder
    
def target_display():
    if 'key1' in st.session_state:
        st.caption(""" **{}** is splitted into **{}** paragraphs/text chunks."""\
                          .format(os.path.basename(st.session_state['filename']),
                                 len(st.session_state['key0'])))   
        
        hits  = st.session_state['target_hits']
        if len(hits) !=0:
            # collecting some statistics
            count_target = sum(hits['TargetLabel'] == True)
            count_ghg = sum(hits['GHGLabel'] == True)
            count_netzero = sum(hits['NetzeroLabel'] == True)
            count_nonghg = sum(hits['NonGHGLabel'] == True)
            count_Mitigation = sum(hits['MitigationLabel'] == True)
            count_Adaptation = sum(hits['MitigationLabel'] == True)
            

            c1, c2 = st.columns([1,1])
            with c1:
                st.write('**Target Related Paragraphs**: `{}`'.format(count_target))
                st.write('**Netzero Related Paragraphs**: `{}`'.format(count_netzero))
            with c2:
                st.write('**GHG Target Related Paragraphs**: `{}`'.format(count_ghg))
                st.write('**NonGHG Target Related Paragraphs**: `{}`'.format(count_nonghg))
            st.write('----------------')

            if count_netzero !=0:
                st.write("NetZero Target:",st.session_state['netzero'])
            else:
                st.info("🤔 No Netzero paragraph found")
            #st.dataframe(hits[['keep','text','Parameter','page']])

            st.dataframe(st.session_state['target_hits'])
        else:
            st.info("🤔 No Targets Found")