# author sridhar iyer

from datetime import date
from datetime import datetime
import re

import numpy as np  
import pandas as pd 
from PIL import Image
import plotly.express as px  
import plotly.graph_objects as go
import streamlit as st  
import time

from plotly.subplots import make_subplots

# Read CSV file into pandas and extract timestamp data
dfSentiment = pd.read_csv('sentiment_data.csv')### YOUR LINE OF CODE HERE
dfSentiment['timestamp'] = [datetime.strptime(dt, '%Y-%m-%d') for dt in dfSentiment['timestamp'].tolist()]

# Multi-select columns to build chart
col_list = dfSentiment.columns.values.tolist()### YOUR LINE OF CODE HERE #### Extract columns into a list

r_sentiment = re.compile(".*sentiment")
sentiment_cols = list(filter(r_sentiment.match, col_list))### YOUR LINE OF CODE HERE

r_post = re.compile(".*post")
post_list = list(filter(r_post.match, col_list))### YOUR LINE OF CODE HERE

r_perc= re.compile(".*perc")
perc_list = list(filter(r_perc.match, col_list))

r_close = re.compile(".*close")
close_list = list(filter(r_close.match, col_list))

r_volume = re.compile(".*volume")
volume_list = list(filter(r_volume.match, col_list))

sentiment_cols = sentiment_cols + post_list
stocks_cols = close_list + volume_list ### YOUR LINE OF CODE HERE

# Config for page
st.set_page_config(
    page_title= 'TSLA Sentiment Analyzer Using Huggingface and StreamLit App',### YOUR LINE OF CODE HERE
    page_icon='✅',
    layout='wide',
)

with st.sidebar:
    # FourthBrain logo to sidebar
    fourthbrain_logo = Image.open('./images/fourthbrain_logo.png')
    st.image([fourthbrain_logo], width=300)

    # Date selection filters
    start_date_filter = st.date_input(
        ### YOUR LINE OF CODE HERE
        'Start Date',
        min(dfSentiment['timestamp']),
        min_value=min(dfSentiment['timestamp']),
        max_value=max(dfSentiment['timestamp'])
        )
        

    end_date_filter = st.date_input(
        'End Date',
        max(dfSentiment['timestamp']),
        min_value=min(dfSentiment['timestamp']),
        max_value=max(dfSentiment['timestamp'])
        )

    sentiment_select = st.selectbox('Select Sentiment Data', sentiment_cols) ### YOUR LINE OF CODE HERE
    stock_select = st.selectbox('Select Stock Data', stocks_cols) ### YOUR LINE OF CODE HERE

# Banner with TSLA and Reddit images
tsla_logo = Image.open('./images/tsla_logo.png')### YOUR LINE OF CODE HERE
reddit_logo = Image.open('./images/reddit_logo.png')
st.image([tsla_logo, reddit_logo], width=200)

# dashboard title
### YOUR LINE OF CODE HERE
st.title('TSLA Dashboard')

## dataframe filter
# start date
dfSentiment = dfSentiment[dfSentiment['timestamp'] >= datetime(start_date_filter.year, start_date_filter.month, start_date_filter.day)]
    
# end date
dfSentiment = dfSentiment[dfSentiment['timestamp'] <= datetime(end_date_filter.year, end_date_filter.month, end_date_filter.day)]
dfSentiment = dfSentiment.reset_index(drop=True)


# creating a single-element container
placeholder = st.empty()### YOUR LINE OF CODE HERE

# near real-time / live feed simulation
for i in range(1, len(dfSentiment)-1):

    # creating KPIs
    last_close =  dfSentiment['close'][i]
    last_close_lag1 = dfSentiment['close'][i-1]
    last_sentiment = dfSentiment['sentiment_score'][i] ### YOUR LINE OF CODE HERE
    last_sentiment_lag1 = dfSentiment['sentiment_score'][i-1]### YOUR LINE OF CODE HERE


    with placeholder.container():

        # create columns
        kpi1, kpi2 = st.columns(2)

        # fill in those three columns with respective metrics or KPIs
        kpi1.metric(
            label='Sentiment Score',
            value=round(last_sentiment, 3),
            delta=round(last_sentiment_lag1, 3),
        )
        
        kpi2.metric(
            label='Last Closing Price',
            ### YOUR LINE 1 OF CODE HERE
            ### YOUR LINE 2 OF CODE HERE
            value=round(last_close),
            delta=round(last_close - last_close_lag1)
        )
        

        # create two columns for charts
        fig_col1, fig_col2 = st.columns(2)
        
        with fig_col1:
            # Add traces
            fig=make_subplots(specs=[[{"secondary_y":True}]])


            fig.add_trace(                               
                go.Scatter(                          
                x=dfSentiment['timestamp'][0:i],
                y=dfSentiment[sentiment_select][0:i],
                name=sentiment_select,
                mode='lines',                            
                hoverinfo='none',                        
                )              
            )

            if sentiment_select.startswith('perc') == True:
                yaxis_label = '% Change Sentiment'

            elif sentiment_select in sentiment_cols:
                yaxis_label = 'Sentiment Score'

            elif sentiment_select in post_list:
                yaxis_label = 'Volume'

            fig.layout.yaxis.title=yaxis_label
                                          
            if stock_select.startswith('perc') == True:
                fig.add_trace(                               
                    go.Scatter(                          
                    x=dfSentiment['timestamp'][0:i],
                    y=dfSentiment[stock_select][0:i],
                    name=stock_select,
                    mode='lines',                            
                    hoverinfo='none', 
                    yaxis='y2',                    
                    ) 
                )
                fig.layout.yaxis2.title='% Change Stock Price ($US)'
            
            elif stock_select == 'volume':
                fig.add_trace(                               
                    go.Scatter(                          
                    x=dfSentiment['timestamp'][0:i],
                    y=dfSentiment[stock_select][0:i],
                    name=stock_select,
                    mode='lines',                            
                    hoverinfo='none', 
                    yaxis='y2',                    
                    ) 
                )
                
                fig.layout.yaxis2.title="Shares Traded"


            else:
                fig.add_trace(                               
                    go.Scatter(                          
                    x=dfSentiment['timestamp'][0:i],
                    y=dfSentiment[stock_select][0:i],
                    name=stock_select,
                    mode='lines',                            
                    hoverinfo='none', 
                    yaxis='y2',                    
                    ) 
                )

                fig.layout.yaxis2.title='Stock Price ($USD)'


            fig.layout.xaxis.title='Timestamp'

            # write the figure throught streamlit
            ### YOUR LINE OF CODE HERE
            st.write(fig)


        st.markdown('### Detailed Data View')
        st.dataframe(dfSentiment.iloc[:, 1:][0:i])
        time.sleep(1)