import plost
import streamlit as st
import pandas as pd
import numpy as np
import jsonlines as jsl
import datetime
import altair as alt
from utils import *

trade_ibkr_dict = {
        'usd_cad':['USDCAD',False,'normal'],
        'usd_chf':['CHFUSD',True,'normal'],
        'usdt_chf':['CHFUSD',True,'normal'],
        'dai_usdt':['stable',False,'stable'],
        'eur_usd':['EURUSD',False,'normal'],
        'usdt_eur':['EURUSD',True,'normal'],
        'usdt_cad':['USDCAD',False,'normal'],
        'usdc_eur':['EURUSD',True,'normal'],
        'usdt_gbp':['GBPUSD',True,'normal'],
        'gbp_usd':['GBPUSD',False,'normal'],
        'eur_chf':['cross',False,'cross'],
        'aud_usd':['AUDUSD',False,'normal'],
        'dai_eur':['EURUSD',True,'normal'],
        'usdc_usdt':['stable',False,'stable'],
        'usdt_aud':['AUDUSD',True,'normal'],
        'dai_usd':['stable',False,'stable'],
        'eur_gbp':['cross',False,'cross'],
        'usdc_gbp':['GBPUSD',True,'normal'],
        'usdt_usd':['stable',False,'stable'],
        'usdc_usd':['stable',False,'stable'],
        'paxg_eur':['cross',False,'cross'],
        'usdc_aud':['AUDUSD',True,'normal'],
        'paxg_usd':['XAUUSD',False,'normal']
    }

balance_df,keys = get_balance_data()
st.title("Assets Changes")
options = st.multiselect(
     'Select Assets',
     list(keys),)
plost.line_chart(
  balance_df,
  x='timestamp',
  y=(options),
  # 👈 This is magic!
)
trade_df = get_trade_parquet()
ibkr_df = get_ibkr_parquet()





st.title('Trades')
st.markdown('**Premium**')
trade_opt = st.selectbox(
    'Select Trade Pair',
    list(trade_df.currency_pair.unique())
)

params = trade_ibkr_dict[trade_opt]
trade_for_vis = trade_df[trade_df.currency_pair==trade_opt]

if params[2] == 'normal':
    tmp_df = fx_pair(trade_df,ibkr_df,trade_opt,params[0],inv=params[1])
    min_y = tmp_df.premium.min()
    max_y = tmp_df.premium.max()
    c = alt.Chart(tmp_df).mark_circle().encode(
        x='time', y=alt.Y('premium', scale=alt.Scale(domain=[min_y, max_y])), 
        size='amount', color='side', tooltip=['time', 'premium', 'side','amount'])
    #st.altair_chart(c.interactive(), use_container_width=True)
    if params[1]:
        ibkr_tmp = 1/ibkr_df[ibkr_df.currency_pair==params[0]][['price']].resample('60s').agg('last')

    else:
        ibkr_tmp = ibkr_df[ibkr_df.currency_pair==params[0]][['price']].resample('60s').agg('last')
    ibkr_tmp['time'] = ibkr_tmp.index
    min_ibkr = ibkr_tmp.price.min()
    max_ibkr = ibkr_tmp.price.max()
    line = alt.Chart(ibkr_tmp).mark_line(stroke='#c95785').encode(
    alt.Y('price',
          axis=alt.Axis(title='Price', titleColor='#c95785'),scale=alt.Scale(domain=[min_ibkr, max_ibkr]))
,alt.X('time'))
    #st.altair_chart(line.interactive(),use_container_width=True)
    op = alt.layer(c, line).resolve_scale(
    y = 'independent'
)
    st.altair_chart(op.interactive(),use_container_width=True)
    
    
elif params[2] == 'stable':
    tmp_df = trade_df[trade_df.currency_pair==trade_opt]
    min_y = tmp_df.price.min()
    max_y = tmp_df.price.max()
    c = alt.Chart(tmp_df).mark_circle().encode(
        x='time', y=alt.Y('price', scale=alt.Scale(domain=[min_y, max_y])), 
        size='amount', color='side', tooltip=['time', 'price', 'side','amount'])
    st.altair_chart(c.interactive(), use_container_width=True)
elif params[2] == 'cross':
    composite = get_cross(trade_opt,ibkr_df)
    tmp_df = fx_pair(trade_df,ibkr_df,trade_opt,'cross',composite)
    min_y = tmp_df.premium.min()
    max_y = tmp_df.premium.max()
    c = alt.Chart(tmp_df).mark_circle().encode(
        x='time', y=alt.Y('premium', scale=alt.Scale(domain=[min_y, max_y])), 
        size='amount', color='side', tooltip=['time', 'premium', 'side','amount'])
    composite = composite.resample('60s').agg('last')
    min_fp = composite.fp.min()
    max_fp = composite.fp.max()
    line = alt.Chart(composite).mark_line(stroke='#c95785').encode(
    alt.Y('fp',
          axis=alt.Axis(title='Price', titleColor='#c95785'),scale=alt.Scale(domain=[min_fp, max_fp]))
,alt.X('time'))
    #st.altair_chart(line.interactive(),use_container_width=True)
    op = alt.layer(c, line).resolve_scale(
    y = 'independent'
)
    st.altair_chart(op.interactive(), use_container_width=True)
if params[2] != 'stable':
    st.markdown('**Price**')
    trade_for_vis = trade_for_vis.loc[str(ibkr_df.index[0]):str(ibkr_df.index[-1])]
    trade_min = trade_for_vis['price'].min()
    trade_max = trade_for_vis['price'].max()

    trade_sc = alt.Chart(trade_for_vis).mark_circle().encode(
        x='time', y=alt.Y('price', scale=alt.Scale(domain=[trade_min, trade_max])), 
            size='amount', color='side', tooltip=['time', 'price', 'side','amount']
    )
    layered = alt.layer(trade_sc,line)
    st.altair_chart(layered.interactive(),use_container_width=True)


#show_df = trade_df[trade_df.currency_pair==trade_opt]
# plost.scatter_chart(
#     data=show_df,
#     x='time',
#     y=show_df[['buy','sell']]['price'],
#     size='amount',
#     )








st.title('Prediction Data')


resample_rate = st.slider('Set Resample Rate(In Minutes)', 1,30,1)

vol_data,fp_data,vol_keys,fp_keys,vol_time,fp_time = get_predict_data()




vol_opts = st.selectbox(
    'Select Volatility Pair',
    list(vol_keys),
)
vol_df = pd.DataFrame({vol_opts:vol_data[vol_opts]})

vol_df['time'] = pd.to_datetime(vol_time[vol_opts],utc=False) - datetime.timedelta(hours=8)
vol_df.index = vol_df.time

vol_df = vol_df.resample(f'{resample_rate*60}s').agg('last')

plost.line_chart(
    vol_df,
    x='time',
    y=(vol_opts),
    opacity=0.5
)
fp_opts = st.selectbox(
    'Select FP Prediction',
    list(fp_keys),
)

fp_df = pd.DataFrame({fp_opts:fp_data[fp_opts]})


fp_df['time'] = pd.to_datetime(fp_time[fp_opts],utc=False)- datetime.timedelta(hours=8)


fp_df.index = fp_df.time
fp_df = fp_df.resample(f'{resample_rate*60}s').agg('last')
plost.line_chart(
    fp_df,
    x='time',
    y=(fp_opts),
    opacity=0.5
)