import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

from openbb import obb
import warnings
warnings.filterwarnings("ignore")
obb.user.preferences.output_type = "dataframe"

import os
import math

import plotly.graph_objects as go
from dash import Dash, dcc, html

FILEPATH = "c:/Users/steve/Downloads/"
SP500_MONTHLY_FILENAME = 'sp500_monthly_historical.csv'

# ## Graph the long-term S&P 500 and Shiller P/E

# ### Monthly prices of S&P 500

# yfinance data only goes back to 1985, so read in a file with monthly S&P 500 prices since 1950
historical_sp500_monthly = pd.read_csv(FILEPATH + SP500_MONTHLY_FILENAME,index_col='date')
historical_sp500_monthly.index = pd.to_datetime(historical_sp500_monthly.index)

# Read monthly data since 2005 from yfinance
sp500mo_current = obb.index.price.historical(symbol='^GSPC', start_date='2005-01-01',
                                     provider='yfinance', interval='1M')
sp500mo_current.index = pd.to_datetime(sp500mo_current.index)

# Splice the two dataframes together
# Remove any overlapping data
sp500mo_current.loc[sp500mo_current.index > historical_sp500_monthly.index[-1]]
# Append the new data to the old
sp500mo = pd.concat([historical_sp500_monthly, sp500mo_current])


# ### Monthly Shiller P/E ratios

shiller = obb.index.sp500_multiples(series_name='shiller_pe_month',
                                    provider='multpl',
                                   start_date='1950-01-01')

# Calculate the 30-year average of the Shiller P/E
shiller['30_yr_avg'] = shiller['value'].rolling(360).mean()

# ### Produce graphs

# Graph the S&P 500 with a log scale
monthly_fig = go.Figure(data=[go.Candlestick(
    x=sp500mo.index,
    open=sp500mo['open'],
    high=sp500mo['high'],
    low=sp500mo['low'],
    close=sp500mo['close'],
    name="Price"
)])

monthly_fig.update_yaxes(type="log")

monthly_fig.update_layout(
    title=f"S&P 500 monthly",
    xaxis_rangeslider_visible=False,
    # template="plotly_dark",
    height=600, width=1075
)


# Graph the Shiller P/E
shiller_fig = go.Figure()
shiller_fig.add_trace(go.Scatter(x=shiller.index,
                             y=shiller['value'],
                             line=dict(color="blue"),
                             name="Shiller P/E"
                            )
                 )
# Add moving averages
shiller_fig.add_trace(go.Scatter(x=shiller.index, y=shiller['30_yr_avg'], line=dict(color='orange'), name = '30-year avg'))

shiller_fig.update_layout(title="Shiller P/E",
                      #template="plotly_dark",
                      height=600, width=1075)