apps/Home.py

import pandas as pd
from datetime import date
from plotly import graph_objs as go
import pybase64 as base64
import numpy as np
import investpy
import streamlit as st
import datetime as dt
import io


def get_table_excel_link(df, selected_stocks):
    towrite = io.BytesIO()
    downloaded_file = df.to_excel(towrite, encoding='utf-8', index=False,
                                  header=True)
    towrite.seek(0)  # reset pointer
    file_name = 'Data'+ selected_stocks + '.xlsx'
    style = 'style="color:black;text-decoration: none; font-size:18px;"'
    name_mark = "Descargar " + selected_stocks + ".xlsx"
    b64 = base64.b64encode(towrite.read()).decode()  # some strings
    linko= f'<center><a href="data:application/vnd.openxmlformats-officedocument.spreadsheetml.sheet;base64,{b64}" '+style+'download="'+file_name+'"><button>'+name_mark+'</button></a></center>'
    return linko


@st.cache
def tabla_commodity(stocks, TODAY):
    tabla = pd.DataFrame()
    year_ago = date.today() - dt.timedelta(days=365)
    year_ago = year_ago.strftime("%d/%m/%Y")
    for stock in stocks:
        precios = investpy.commodities.get_commodity_historical_data(
                                                    commodity=stock,
                                                    from_date=year_ago,
                                                    to_date=TODAY)
        precios = precios["Close"]
        last_price = precios.iloc[-1]
        oned = precios.iloc[-2]
        onew = precios.iloc[-7]
        onem = precios.iloc[-30]
        oney = precios.iloc[0]
        return1m = str(round((last_price/onem-1)*100, 2))+"%"
        return1d = str(round((last_price/oned-1)*100, 2))+"%"
        return1w = str(round((last_price/onew-1)*100, 2))+"%"
        return1y = str(round((last_price/oney-1)*100, 2))+"%"
        tabla = tabla.append([[return1d, return1w, return1m, return1y]])
    tabla.columns = ["1d", "1w", "1m", "1y"]
    tabla.index = stocks
    return tabla


@st.cache
def tabla_indices(index, countries, TODAY):
    tabla = pd.DataFrame()
    year_ago = date.today() - dt.timedelta(days=365)
    year_ago = year_ago.strftime("%d/%m/%Y")
    for i in range(len(index)):
        precios = investpy.get_index_historical_data(index=index[i],
                                                     country=countries[i],
                                                     from_date=year_ago,
                                                     to_date=TODAY)
        precios = precios["Close"]
        last_price = precios.iloc[-1]
        oned = precios.iloc[-2]
        onew = precios.iloc[-7]
        onem = precios.iloc[-30]
        oney = precios.iloc[0]
        return1m = str(round((last_price/onem-1)*100, 2))+"%"
        return1d = str(round((last_price/oned-1)*100, 2))+"%"
        return1w = str(round((last_price/onew-1)*100, 2))+"%"
        return1y = str(round((last_price/oney-1)*100, 2))+"%"
        tabla = tabla.append([[return1d, return1w, return1m, return1y]])
    tabla.columns = ["1d", "1w", "1m", "1y"]
    tabla.index = index
    return tabla


@st.cache
def tabla_bonos(stocks, TODAY):
    tabla = pd.DataFrame()
    year_ago = date.today() - dt.timedelta(days=365)
    year_ago = year_ago.strftime("%d/%m/%Y")
    for stock in stocks:

        precios = investpy.get_bond_historical_data(bond=stock,
                                                    from_date=year_ago,
                                                    to_date=TODAY)
        precios = precios["Close"]
        last_price = precios.iloc[-1]
        oned = precios.iloc[-2]
        onew = precios.iloc[-7]
        onem = precios.iloc[-30]
        oney = precios.iloc[0]
        return1m = str(round((last_price-onem)*100, 2))+"%"
        return1d = str(round((last_price -oned)*100, 2))+"%"
        return1w = str(round((last_price -onew)*100, 2))+"%"
        return1y = str(round((last_price - oney)*100, 2))+"%"
        tabla = tabla.append([[return1d, return1w, return1m, return1y]])
    tabla.columns = ["1d", "1w", "1m", "1y"]
    tabla.index = stocks
    return tabla


def highlight_max(s):
    if s.dtype == np.object:
        is_neg = [False for _ in range(s.shape[0])]
    else:
        is_neg = s < 0
    return ['color: red;' if cell else 'color:black' for cell in is_neg]


def button_style():
    style_button = """
        <style>
          button {
            display: inline-block;
            background-color: #e8e8e8;
            border-radius: 15px;
            border: 4px  #cccccc;
            color: #4a4a4a;
            text-align: center;
            font-size: 12px;
            padding: 2px;
            width: 250px;
            transition: all 0.5s;
            cursor: pointer;
            margin: 5px;
          }
          button span {
            cursor: pointer;
            display: inline-block;
            position: relative;
            transition: 0.5s;
          }
          button span:after {
            content: '\00bb';
            position: absolute;
            opacity: 0;
            top: 0;
            right: -20px;
            transition: 0.5s;
          }
          button:hover {
            background-color: #bb1114;
            color:#e8e8e8;
          }
          button:hover span {
            padding-right: 25px;
          }
          button:hover span:after {
            opacity: 1;
            right: 0;
            }
         .stMarkdown{
            margin-bottom:0px;}
    </style>
    """
    st.markdown(style_button, unsafe_allow_html=True)


def style_table():
    # tr:hover {background-color: #E8E8E8;
    #          color:#BB1114;}
    style_table = """
                <style>
                tr { line-height: 5px; }
                thead {
                      background-color:#BB1114 ;
                      color: #E8E8E8;
                    }
                tbody tr:nth-child(odd) {
                      background-color: #fff;
                    }
                    tbody tr:nth-child(even) {
                      background-color: #eee;
                    }
                .css-1rcck9u{
                    padding:0.25rem;}
                tbody tr:nth-child(odd)
                stTable {
                    border-collapse: collapse;
                    background-color:red;
                    margin: 25px 0;
                    font-size: 0.9em;
                    min-width: 400px;
                    box-shadow: 0 0 20px rgba(0, 0, 0, 0.15);
                    }
                table{
                    margin-top:0px;
                    font-size:9px;
                    padding:0px;
                    height:200px;}
                .st-cc, .st-cb{
                    padding-top:5px;
                    padding-bottom:5px;}
                        h3, h1, h2, .svg-container {
                  animation-duration: 3s;
                  animation-name: slidein;
                }
                @keyframes slidein {
                  from {
                    margin-left: 100%;
                    width: 300%
                  }
                  to {
                    margin-left: 0%;
                    width: 100%;
                  }
                }
                </style>
                """
    st.markdown(style_table, unsafe_allow_html=True)


def seleccionar_fecha(fecha_select):
    if fecha_select == "1 week":
        fec_in = date.today() - dt.timedelta(days=7)
    elif fecha_select == "1 month":
        fec_in = date.today() - dt.timedelta(days=30)
    elif fecha_select == "3 month":
        fec_in = date.today() - dt.timedelta(days=90)
    elif fecha_select == "6 month":
        fec_in = date.today() - dt.timedelta(days=180)
    elif fecha_select == "1 year":
        fec_in = date.today() - dt.timedelta(days=365)
    elif fecha_select == "5 year":
        fec_in = date.today() - dt.timedelta(days=365*5)
    fec_in = fec_in.strftime("%d/%m/%Y")
    return fec_in


def stock_price():
    style_table()
    button_style()
    TODAY = date.today().strftime("%d/%m/%Y")
    YDAY = date.today() - dt.timedelta(days=1)
    YDAY = YDAY.strftime("%d/%m/%Y")
    commodity = ["Copper", "Silver", "Gold", "Platinum", 'Brent Oil',
                 'Heating Oil']
    # bonos = ["Brazil 10Y", "Mexico 10Y" , "Chile 10Y", "Colombia 10Y"
    #          , "Peru 10Y"]
    bonds10y = ["Brazil 10Y", "Mexico 10Y", "Chile 10Y", "Colombia 10Y",
                "Peru 10Y", "China 10Y"]
    index = ["S&P CLX IPSA", "S&P Merval", "Bovespa", "S&P 500"]
    countries = ["chile", "argentina", "brazil", "united states"]
    col1, col2, col3 = st.beta_columns(3)
    cols = st.beta_columns((3, 2, 3, 2, 3, 2))
    col1.markdown('<center><h1 style="font-size:22px;">Principales bonos 10Y</h1><center>', unsafe_allow_html=True) 
    col2.markdown('<center><h1 style="font-size:22px;">Principales commodities</h1><center>', unsafe_allow_html=True)
    col3.markdown('<center><h1 style="font-size:22px;">Principales indices</h1><center>', unsafe_allow_html=True)
    selected_com = cols[2].selectbox("  ", commodity)
    selected_index = cols[4].selectbox(" ", index)
    selected_bonds = cols[0].selectbox(" ", bonds10y)
    fecha_select = cols[3].selectbox("  ", ["1 year", "6 month", "3 month",
                                            "1 month", "1 week"])
    fecha_select2 = cols[5].selectbox("   ", ["1 year", "6 month", "3 month",
                                              "1 month", "1 week"])
    fecha_select3 = cols[1].selectbox("    ", ["1 year", "6 month", "3 month",
                                               "1 month", "1 week"])
    # fecha_select =cols[2].button("hola")
    fec_in = seleccionar_fecha(fecha_select)
    fec_in2 = seleccionar_fecha(fecha_select2)
    fec_in3 = seleccionar_fecha(fecha_select3)
    selected_country = countries[index.index(selected_index)]
    data_bonds = investpy.get_bond_historical_data(bond=selected_bonds,
                                                   from_date=fec_in3,
                                                   to_date=TODAY)
    data_com = investpy.commodities.get_commodity_historical_data(
                                                        commodity=selected_com,
                                                        from_date=fec_in,
                                                        to_date=TODAY)
    data_index = investpy.get_index_historical_data(index=selected_index,
                                                    country=selected_country,
                                                    from_date=fec_in2,
                                                    to_date=TODAY)

    def plot_raw_data(col, data, color, prefijo):
        fig = go.Figure()
        close_ = go.Scatter(x=data.index, y=data['Close'], name="stock_close",
                            line=dict(color=color), fill='tonexty')
        fig.add_trace(close_)
        fig.layout.update(title_text="", xaxis_rangeslider_visible=True,
                          width=300, height=200, margin_b=0, margin_t=0,
                          margin_r=0, margin_l=0)
        fig.update_yaxes(range=[min(data['Close'])/1.05,
                                max(data['Close'])*1.05], tickprefix=prefijo)
        col.plotly_chart(fig)
    plot_raw_data(cols[0], data_bonds, 'seagreen', "")
    plot_raw_data(cols[2], data_com, 'midnightblue', "$")
    plot_raw_data(cols[4], data_index, 'dimgrey', "$")
    col1, col2, col3 = st.beta_columns(3)
    cols = st.beta_columns((3, 2, 3, 2, 3, 2))
    last_price = data_bonds.iloc[-1]["Close"]
    first_price = data_bonds.iloc[0]["Close"]
    returns = round((last_price/first_price-1)*100, 2)
    cols[0].markdown('<h4 style="font-size:12px; padding-left:15px; margin-bottom:0px;">'+"Precio"+"</h4>", unsafe_allow_html=True)
    cols[0].markdown('<p style="font-size:25px; padding-left:30px;">'+"{:,}".format(last_price)+"%</p>", unsafe_allow_html=True)
    if returns > 0:
        cols[1].markdown('<p style="font-size:20px; padding-top:22px; color:green;">▲ '+str(returns)+" %</p>", unsafe_allow_html=True)
    else:
        cols[1].markdown('<p style="font-size:20px; padding-top:22px; color:red;">▼ '+str(returns)+" %</p>", unsafe_allow_html=True)
    last_price2 = data_com.iloc[-1]["Close"]
    first_price2 = data_com.iloc[0]["Close"]
    returns2 = round((last_price2/first_price2-1)*100, 2)
    cols[2].markdown('<h4 style="font-size:12px; padding-left:15px; margin-bottom:0px;">'+"Precio"+"</h4>", unsafe_allow_html=True)
    cols[2].markdown('<p style="font-size:25px; padding-left:30px;">$'+"{:,}".format(last_price2)+"</p>", unsafe_allow_html=True)
    if returns2 > 0:
        cols[3].markdown('<p style="font-size:20px; padding-top:22px; color:green;">▲ '+str(returns2)+" %</p>", unsafe_allow_html=True)
    else:
        cols[3].markdown('<p style="font-size:20px; padding-top:22px; color:red;">▼ '+str(returns2)+" %</p>", unsafe_allow_html=True)
    last_price3 = data_index.iloc[-1]["Close"]
    first_price3 = data_index.iloc[0]["Close"]
    returns3 = round((last_price3/first_price3-1)*100, 2)
    cols[4].markdown('<h4 style="font-size:12px; padding-left:15px; margin-bottom:0px;">'+"Precio"+"</h4>", unsafe_allow_html=True)
    cols[4].markdown('<p style="font-size:25px; padding-left:30px;">$'+"{:,}".format(last_price3)+"</p>", unsafe_allow_html=True)
    if returns3 > 0:
        cols[5].markdown('<p style="font-size:20px; padding-top:22px; color:green;">▲ '+str(returns3)+" %</p>", unsafe_allow_html=True)
    else:
        cols[5].markdown('<p style="font-size:20px; padding-top:22px; color:red;">▼ '+str(returns3)+" %</p>", unsafe_allow_html=True)
    col1, col2, col3 = st.beta_columns(3)
    col1.table(tabla_bonos(bonds10y, TODAY))
    col2.table(tabla_commodity(commodity, TODAY))
    col3.table(tabla_indices(index, countries, TODAY))

    col1, col2, col3 = st.beta_columns(3)
    col2.markdown(get_table_excel_link(data_com, selected_com),
                  unsafe_allow_html=True)
    col3.markdown(get_table_excel_link(data_index, selected_index),
                  unsafe_allow_html=True)
    col1.markdown(get_table_excel_link(data_bonds, selected_bonds),
                  unsafe_allow_html=True)
    get_table_excel_link