main.py

# Importing Necessary Libraries
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import yfinance as yf
import dash
import ta
import plotly.express as px
import plotly.graph_objects as go
import dash_bootstrap_components as dbc


from ta import add_all_ta_features
from ta import trend
from ta import volume
from ta import momentum
from ta import volatility
from ta.trend import sma_indicator
from ta.trend import ema_indicator
from ta.momentum import awesome_oscillator
from ta.volatility import bollinger_hband
from ta.volatility import bollinger_lband
from ta.volatility import bollinger_mavg

from dash.dependencies import Input, Output
from dash import html
from dash import dcc
from datetime import date
from datetime import datetime as dt
import colorlover as cl



# Creating an empty dataframe for later use. 

df = pd.DataFrame()


# Calling the application with the SpaceLabs theme
app = dash.Dash(external_stylesheets=[dbc.themes.SPACELAB])

# Defining Colorscales for the candlestick sharts
colorscale = cl.scales['9']['qual']['Paired']



################################################################################
#                                                                              #
#                          APP LAYOUT STARTS HERE                              #
#                                                                              #
################################################################################

app.layout = html.Div(
    [
        
        # TITLE  
        html.H3(children = "Visualizing Technical Indicators Using Python and Plotly. - By Surya Sashank Gundepudi", 
               style = {
                   'textAlign' : 'center'
               }), 
        
        
        # NOTE
        html.Div(children='''(This is for educational purposes only)''', 
               style = {
                   'textAlign' : 'center', 
               }), 
        
        
        # LINK FOR TUTORIAL
        html.Div(children=[html.A('SEARCH FOR TUTORIAL AND SOURCE AT GITHUB', 
                                  href='https://github.com/suryasashankgundepudi/technical-analysis-visualization-using-python-v1/blob/main/README.md', 
                                  target='_blank')], 
               style = {
                   'textAlign' : 'center', 
               }),
        
        
        # LINK FOR TECHNICAL ANALYSIS LIBRARY DOCUMENTATION
        html.Div(children=[html.A("""UNDERSTAND WHICH PARAMETERS ARE NEEDED PLEASE GO HERE. 
        IF PARAMETERS ARE MISSING DEFAULT VALUES ARE TAKEN""", 
                                  href='https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html', 
                                  target='_blank')], 
               style = {
                   'textAlign' : 'center', 
               }), 
        
        
        #LINK FOR CURRENT INDICATOR
        html.Div(children=[html.A('LEARN MORE ABOUT CURRENT INDICATOR HERE', 
                                  href='https://www.investopedia.com/terms/s/sma.asp', 
                                  id = "indicator-link", 
                                  target='_blank')], 
               style = {
                   'textAlign' : 'center', 
               }),
        
         

        html.Br(), 
        html.Br(),
        
        # THE FIRST ROW AS SEEN IN APPLICATION
        dbc.Row(
            [
                # TEXT FOR TICKER
                dbc.Col(html.Div(children='''Enter The ticker from yahoo finance. Copy and paste all letters 
                at same time please: '''), 
                        align = 'start', 
                       style = {"margin-left": "20px"}),
                
                
                # TEXT FOR START AND END DATE
                dbc.Col((html.Div(children='''Enter the START DATE and END DATE''')), align = 'center', 
                       style = {"margin-left": "100px"}), 
                
                
                dbc.Col((html.Div(children = '''Select what kind of graph you would like along with indicator''')), 
                       align = 'center', style = {"margin-right" : '100px'})
                
                # ROW 1 ENDS HERE 
                
            ],
            align="start",
        ),
        
        
        
        # THE SECOND ROW AS SEEN IN THE APPLICATION
        dbc.Row(
            [
                # INPUT FOR TICKER VALUE
                dbc.Col((dcc.Input(id="input-1", type="text", value="AMZN")), align = 'start', 
                       style = {"margin-left": "20px", 'border-radius': 10}),
                
                
                # INPUT FOR DATE RANGE 
                dbc.Col((dcc.DatePickerRange(
                    id='my-date-picker-range',
                    start_date=date(2018, 1, 1), 
                    end_date = date(2019, 12, 31), 
                    min_date_allowed=date(2003, 1, 1),
                    max_date_allowed=date(2020, 12, 31), 
                    initial_visible_month= date(2018, 1, 12), 
                    start_date_placeholder_text= date(2018, 1, 1),
                    end_date_placeholder_text= date(2019, 12, 31)
                )), align = 'end', 
                       style = {"margin-left": "100px", 'border-radius': 10}), 
                
                
                
                # INPUT FOR TYPE OF GRAPH
                dbc.Col((dcc.Dropdown(
                    id='graphtypeselect',
                    options = [
                        {'label' : "CandleStick Chart", 'value' : "candle"}, 
                        {'label' : "Open of Stock", "value" : "open"}, 
                        {'label' : "Close of Stock", "value" : "close"}
                        
                    ], 
                    value = 'candle'
                )), align = 'end', 
                       style = {"margin-right": "40px", 'border-radius': 10})
                
                # ROW ENDS HERE
            
                
            ]
        ), 
        
        
        html.Br(), 
        html.Br(), 
        
        
        
        # THE THIRD ROW AS SEEN IN THE APPLICATION
        dbc.Row(
            [
                # TEXT FOR SHORT WINDOW LENGTH 
                dbc.Col( html.Div(children='''Enter the Short Window Length'''), align = 'start', 
                       style = {"margin-left": "20px"}),
                
                
                # TEXT FOR LONG WINDOW LENGTH 
                dbc.Col( html.Div(children='''Enter the Long Window Length (if indicator requires only one 
                window it will take the first one)'''),
                        align = 'center'),
                
                
                #TEXT FOR SIGNAL WINDOW
                dbc.Col( html.Div(children='''Enter the signal Window (if indicator requires only one 
                window length it will take the first value)''')), 
                
                
                # TEXT FOR TYPE OF INDICATOR
                dbc.Col((html.Div(children='''Select the Type of Indicator''')), align = 'end', 
                       style = {"margin-right": "40px"}), 
                
            ],
            align="start",
        ),
        
        
        
        # THE FOURTH ROW AS SEEN IN THE APPLICATION
        dbc.Row(
            [
                # INPUT VALUE FOR SHORT WINDOW LENGTH
                dbc.Col((dcc.Input(id="input-window", type="number", value=12)), align = 'start', 
                       style = {"margin-left": "20px", 'border-radius': 10}),
                
                
                # INPUT VALUE FOR LONG WINDOW LENGTH 
                dbc.Col((dcc.Input(id="input-window-long", type="number", value=26,
                       style = {'border-radius': 10})), align = 'center'),
                
                
                # INPUT VALUE FOR LONG WINDOW LENGTH 
                dbc.Col((dcc.Input(id="input-window-signal", type="number", value=9,
                       style = {'border-radius': 10}))),
                
                
                # INPUT VALUE FOR INDICATOR 
                dbc.Col((dcc.Dropdown(
                    id='indicator',
                    options = [
                        {'label' : "Stock Only", 'value' : "PLAIN"}, 
                        {'label' : "Accumulation/Distribution Index", 'value' : "ACCDI"}, 
                        {'label' : 'Aroon Indicator', 'value' : 'AROON'},
                        {'label' : "Average Directional index", 'value' : 'ADX'}, 
                        {'label' : "Average True Range (ATR)", 'value' : 'Average True Range'}, 
                        {'label': 'Awesome Oscillator', 'value' : 'Awesome Oscillator'}, 
                        {'label': 'Bollinger Bands (std - 2)', 'value' : 'Bollinger Bands'}, 
                        {'label': 'Chaikin Money Flow (CMF)', 'value' : 'Chaikin Money Flow'}, 
                        {'label' : 'Cummilative Returm', 'value' : 'CUMRET'}, 
                        {'label' : 'Daily Return', 'value' : 'DRET'},
                        {'label' : 'Donchian Channel Bands', 'value' : 'DCI'}, 
                        {'label': 'Ease of Movement', 'value' : 'Ease of Movement'},
                        {'label': 'Exponential Moving Average', 'value' : 'Exponential Moving Average'},
                        {'label' : "Ichimoku Kinkō Hyō (Ichimoku)", 'value' : 'ICHIMOKU'}, 
                        {'label': 'Kaufman’s Adaptive Moving Average', 'value' : 'KAMA'},
                        {'label' : 'Kelter Channel Index', 'value' : "KCI"}, 
                        {'label' : 'Money Flow index', 'value' : "MFI"},
                        {'label' : 'MACD', 'value' : 'MACD'}, 
                        {'label' : 'Negative Volume Index Indicator', 'value' : "NVII"}, 
                        {'label': 'Percentage Price Oscillator', 'value' : 'Percentage Price Oscillator (PPO)'},
                        {'label': 'Percentage Volume Oscillator', 'value' : 'Percentage Volume Oscillator'},
                        {'label': 'Rate of Change', 'value' : 'Rate of Change'},
                        {'label': 'Relative Strength Index (RSI)', 'value' : 'Relative Strength Index'},
                        {'label': 'Simple Moving Average', 'value' : 'Simple Moving Average'}, 
                        {'label': 'Ulcer Index', 'value' : 'ULCI'},
                        {'label' : 'Volume Weighted Average Price', 'value' : "VWAP"}, 
                        {'label' : 'Weighted Moving Average', 'value': 'WMA'}
                
                        
                        
                    ], 
                    value = 'PLAIN'
                )), align = 'end', 
                       style = {"margin-right": "40px", 'border-radius': 10})]
        ),
        html.Br(),
        dcc.Graph(id='GRAPH'), 
        
        
    ])




# USING THE INPUTS FROM THE APP TO UPDATE THE GRAPH. CURRENT CALLBACK UPDATES THE GRAP
@app.callback(
    Output('GRAPH', 'figure'),
    Input("input-1", "value"),
    Input('indicator', 'value'),
    Input('input-window', 'value'), 
    Input('input-window-long', 'value'), 
    Input('input-window-signal', 'value'),
    Input("graphtypeselect", "value"), 
    Input('my-date-picker-range', 'start_date'),
    Input('my-date-picker-range', 'end_date'))
def update_output(input1, indicator_1, window_input, window_input_long, signal_input, graphtype, start_date, end_date):
    # DOWNLOADING THE DATA FROM YAHOO FINANCE USING THE FIRST INPUT 
    df = yf.download(input1, start_date,end_date)
    
    
    # SAVING ONLY THE NECESSARY VALUES INTO DATAFRAME NAMED STOCK 
    Stock = pd.DataFrame({
        "Date" : df.index, 
        "Close" : df["Close"],
        "Open" : df["Open"], 
        "High" : df["High"],
        "Low" : df["Low"], 
        "Volume" : df["Volume"]
    })
    
    # SETTING THE INDEX OF STOCK AS THE DATES OF THE DATAFRAME
    Stock.set_index("Date")
    
    # SECOND CALLBACK FOR THE TYPE OF GRAPH TO BY PLOTTED 
    if graphtype == "candle": 
        add_trace_graph = go.Candlestick(x = Stock["Date"], 
                                         open=Stock["Open"],
                                         high=Stock['High'],
                                         low=Stock['Low'],
                                         close=Stock['Close'], name = input1)
        
    if graphtype == "close": 
        add_trace_graph = {'x' : Stock["Date"], 'y' : Stock["Close"], 'type' : 'scatter', 'name' : 'Close'}
    if graphtype == "open":
        add_trace_graph = {'x' : Stock["Date"], 'y' : Stock["Open"], 'type' : 'scatter', 'name' : 'Open'}
    
    
    
    
    # ACCUMALATION DISTRIBUTION INDEX
    if indicator_1 == "PLAIN": 
        fig = go.Figure()
        fig.add_trace(add_trace_graph)
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    # ACCUMALATION DISTRIBUTION INDEX
    if indicator_1 == "ACCDI": 
        Stock["ADI"] = volume.acc_dist_index(high = Stock["High"], low = Stock["Low"], 
                                                           close = Stock["Close"], volume = Stock["Volume"])
        fig = px.line(Stock[["ADI"]], title='Accumulation/Distribution Index (ADI)')
        fig.update_layout(transition_duration=500)
        return fig

    
    
    # AROON INDICATOR
    elif indicator_1 == "AROON": 
        Stock["AROON UP"] = trend.aroon_up(Stock["Close"], window = window_input)
        Stock["AROON DOWN"] = trend.aroon_down(Stock["Close"], window = window_input)
        fig = px.line(Stock[["AROON UP", "AROON DOWN"]], title='Aroon Indicator')
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    # AVERAGE DIRECTIONAL INDICATOR
    elif indicator_1 == "ADX": 
        Stock["ADX"] = trend.adx(Stock["High"], Stock["Low"], Stock["Close"],
                                 window=window_input)
        Stock["DX_NEG"] = trend.adx_neg(Stock["High"], Stock["Low"], Stock["Close"],
                                 window=window_input)
        Stock["DX_POS"] = trend.adx_pos(Stock["High"], Stock["Low"], Stock["Close"],
                                 window=window_input)
        fig = px.line(Stock[["ADX"]], title='Average Directional Indicator')
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    # AWESOME INDICATOR
    elif indicator_1 == "Awesome Oscillator": 
        Stock["Awesome Oscillator"] = awesome_oscillator(Stock["High"], Stock["Low"], window1=window_input, 
                                                         window2=window_input_long)
        fig = px.line(Stock[["Awesome Oscillator"]], title='Awesome Indicator')
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    # AVERAGE TRUE RANGE INDICATOR
    elif indicator_1 == "Average True Range": 
        Stock["Average True Range"] = volatility.average_true_range(high = Stock["High"], low = Stock["Low"], 
                                                           close = Stock["Close"], window=window_input)
        fig = px.line(Stock[["Average True Range"]], title='Average True Range')
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    # BOLLINGER BANDS
    elif indicator_1 == "Bollinger Bands": 
        Stock["HIGH BAND"] = bollinger_hband(Stock["Close"], window = window_input, window_dev = 2)
        Stock["LOW BAND"] = bollinger_lband(Stock["Close"], window = window_input, window_dev = 2)
        Stock["MID BAND"] = bollinger_mavg(Stock["Close"], window = window_input)        
        #fig = px.line(Stock[["Close", "HIGH BAND", "LOW BAND", "MID BAND"]], title='Close and Bollinger Bands')
        fig = px.line(Stock[["HIGH BAND", "LOW BAND", "MID BAND"]], title='Close and Bollinger Bands')
        fig.add_trace(add_trace_graph)
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    
    # CHAIKIN INDICATOR
    elif indicator_1 == "Chaikin Money Flow": 
        Stock["Chaikin Money Flow"] = volume.chaikin_money_flow(high = Stock["High"], low = Stock["Low"], 
                                                               close = Stock["Close"], volume = Stock["Volume"], 
                                                               window = window_input)       
        fig = px.line(Stock[["Chaikin Money Flow"]], title='Chaikin Indicator')
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    # Commodity Channel Index (CCI)
    elif indicator_1 == "CCI": 
        Stock["CCI"] = trend.cci(high = Stock["High"], low = Stock["Low"], 
                                                           close = Stock["Close"], window=window_input)
        fig = px.line(Stock["CCI"], title='Close VS Commodity Chanel Index')
        fig.add_trace(add_trace_graph)
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    
    # CUMMILATIVE RETURN
    elif indicator_1 == "CUMRET": 
        Stock["Cummilative Return"] = ta.others.cumulative_return(Stock['Close'])
        fig = px.line(Stock[["Cummilative Return"]], title='Cummilative Return')
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    # DAILY RETURN
    elif indicator_1 == "DRET": 
        Stock["Daily Return"] = ta.others.daily_return(Stock['Close'])
        fig = px.line(Stock[["Daily Return"]], title='Daily Return')
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    # Donchian CHANNEL INDICATOR
    elif indicator_1 == "DCI": 
        Stock["HIGH BAND"] = volatility.donchian_channel_hband(high = Stock["High"], low = Stock["Low"], 
                                                               close = Stock["Close"], window = window_input)
        Stock["LOW BAND"] = volatility.donchian_channel_lband(high = Stock["High"], low = Stock["Low"], 
                                                               close = Stock["Close"], window = window_input)
        Stock["MID BAND"] = volatility.donchian_channel_mband(high = Stock["High"], low = Stock["Low"], 
                                                               close = Stock["Close"], window = window_input)        
        fig = px.line(Stock[["HIGH BAND", "LOW BAND", "MID BAND"]], title='Close and Donchian Channel Bands')
        fig.add_trace(add_trace_graph)
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    # EASE OF MOVEMENT INDICATOR
    elif indicator_1 == "Ease of Movement": 
        Stock["Ease of Movement"] = volume.ease_of_movement(high = Stock["High"], low = Stock["Low"],
                                                            volume = Stock["Volume"], window = window_input)       
        fig = px.line(Stock[["Ease of Movement"]], title='Ease of Movement')
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    
    # EXPONENTIAL MOVING AVERAGE
    elif indicator_1 == "Exponential Moving Average": 
        Stock["EMA"] = ema_indicator(Stock["Close"], window = window_input)
        fig = px.line(Stock["EMA"], title='Close VS Exponential Moving Average')
        fig.add_trace(add_trace_graph)
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
  
    
    
    
    # Ichimoku Kinkō Hyō (Ichimoku)
    elif indicator_1 == "ICHIMOKU": 
        Stock["Senkou Span A"] = trend.ichimoku_a(high = Stock["High"], low = Stock["Low"], window1 = window_input, 
                                                 window2 = window_input_long)       
        Stock["Senkou Span B"] = trend.ichimoku_b(high = Stock["High"], low = Stock["Low"], window2 = window_input_long, 
                                                 window3 = signal_input)       
        Stock["Kiju Sen (Base Line)"] = trend.ichimoku_base_line(high = Stock["High"], low = Stock["Low"], 
                                                                 window1 = window_input, 
                                                                 window2 = window_input_long)       
        Stock["Tenkan Sen (Conversion Line)"] = trend.ichimoku_conversion_line(high = Stock["High"], low = Stock["Low"], 
                                                                             window1 = window_input, 
                                                                             window2 = window_input_long)       
        fig = px.line(Stock[["Senkou Span A", "Senkou Span B", "Kiju Sen (Base Line)", 
                             "Tenkan Sen (Conversion Line)"]], 
                      title='Close and Ichimoku')
        fig.add_trace(add_trace_graph)
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    # KAUFMAN'S ADAPTIVE MOVING AVERAGE
    elif indicator_1 == "KAMA":
        Stock["KAMA"] = momentum.kama(Stock["Close"], window = window_input)
        fig = px.line(Stock["KAMA"], title='Close VS KAMA')
        fig.add_trace(add_trace_graph)
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    # KELTER CHANNEL INDICATOR
    elif indicator_1 == "KCI": 
        Stock["HIGH BAND"] = volatility.keltner_channel_hband(Stock['High'], Stock['Low'], 
                                                              Stock["Close"], window = window_input,
                                                              window_atr=window_input_long)
        Stock["LOW BAND"] = volatility.keltner_channel_lband(Stock['High'], Stock['Low'], 
                                                              Stock["Close"], window = window_input, 
                                                             window_atr=window_input_long)
        Stock["MID BAND"] = volatility.keltner_channel_mband(Stock['High'], Stock['Low'], 
                                                              Stock["Close"], window = window_input, 
                                                             window_atr=window_input_long)        
        fig = px.line(Stock[["HIGH BAND", "LOW BAND", "MID BAND"]], title='Close and Keltner Indicator')
        fig.add_trace(add_trace_graph)
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    # MONEY FLOW INDEX
    elif indicator_1 == "MFI": 
        Stock["MFI"] = volume.money_flow_index(high = Stock["High"], low = Stock["Low"], 
                                                               close = Stock["Close"], volume = Stock["Volume"], 
                                                               window = window_input)       
        fig = px.line(Stock["MFI"], title='MONEY FLOW INDEX')
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    # MOVING AVERAGE CONVERGENCE DIVERGENCE
    elif indicator_1 == "MACD":
        Stock["MACD"] = trend.macd(Stock["Close"], window_slow = window_input_long, 
                                   window_fast=window_input)
        Stock["MACD SIGNAL"] = trend.macd_signal(Stock["Close"], window_slow = window_input_long, 
                                   window_fast=window_input, window_sign= signal_input)
        fig = px.line(Stock[["MACD", "MACD SIGNAL"]], title='MACD AND MACD SIGNAL')
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    # NEGATIVE VOLUME INDEX INDICATOR
    elif indicator_1 == "NVII": 
        Stock["NVII"] = volume.negative_volume_index(close = Stock["Close"], volume = Stock["Volume"])       
        fig = px.line(Stock["NVII"], title='Close and Negative Volume Index Indicator')
        fig.add_trace(add_trace_graph)
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    # PERCENTAGE PRICE OSCILLATOR 
    elif indicator_1 == "Percentage Price Oscillator (PPO)":
        Stock["PPO"] = momentum.ppo(Stock["Close"], window_slow = window_input_long, 
                                   window_fast=window_input, window_sign= signal_input)
        fig = px.line(Stock[["PPO"]], title='PPO')
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    # PERCENTAGE VOLUME OSCILLATOR 
    elif indicator_1 == "Percentage Volume Oscillator":
        Stock["PVO"] = momentum.pvo(Stock["Close"], window_slow = window_input_long, 
                                   window_fast=window_input, window_sign= signal_input)
        Stock["SIGNAL"] = momentum.pvo(Stock["Close"], window_slow = window_input_long, 
                                   window_fast=window_input, window_sign= signal_input)
        fig = px.line(Stock[["PVO", "SIGNAL"]], title='PVO VS PVO SIGNAL')
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    # RATE OF CHANGE
    elif indicator_1 == "Rate of Change":
        Stock["ROC"] = momentum.roc(Stock["Close"], window=window_input)
        fig = px.line(Stock["ROC"], title='RATE OF CHANGE')
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    # RELATIVE STRENGTH INDEX
    elif indicator_1 == "Relative Strength Index":
        Stock["RSI"] = momentum.rsi(Stock["Close"], window = window_input)
        fig = px.line(Stock[["RSI"]], title='Relative Strength Index')
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    # SIMPLE MOVING AVERAGE
    elif indicator_1 == "Simple Moving Average":
        Stock["MA"] = sma_indicator(Stock["Close"], window = window_input)
        fig = px.line(Stock["MA"], title='Close VS Simple Moving Average')
        fig.add_trace(add_trace_graph)
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    # ULCER INDEX
    elif indicator_1 == "ULCI":
        Stock["ULCI"] = volatility.ulcer_index(Stock["Close"], window = window_input)
        fig = px.line(Stock["ULCI"], title='Ulcer Index')
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    
    # VOLUME WEIGHTED AVERAGE PRICE
    elif indicator_1 == "VWAP":
        Stock["VWAP"] = volume.volume_weighted_average_price(high = Stock["High"], low = Stock["Low"], 
                                                               close = Stock["Close"], volume = Stock["Volume"], 
                                                               window = window_input)
        fig = px.line(Stock["VWAP"]
                      , title='Close VS Volume Weighter Average Price')
        fig.add_trace(add_trace_graph)
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig
    
    
    # WEIGHTED MOVING AVERAGE
    elif indicator_1 == "WMA":
        Stock["WMA"] = trend.wma_indicator(close = Stock["Close"], window = window_input)
        fig = px.line(Stock["WMA"], title='Close VS Weighted Moving Average')
        fig.add_trace(add_trace_graph)
        fig.update_yaxes(fixedrange=False)
        fig.update_layout(transition_duration=500)
        return fig


#UPDATING THE LINKS FOR TECHNICAL INDICATOR

@app.callback(
    Output('indicator-link', 'href'), 
    Input('indicator', 'value')
)

def update_link(indicator_1):
    if indicator_1 == "ACCDI": 
        url = """https://www.ifcm.co.uk/ntx-indicators/awesome-oscillatorr"""
        return url
    

    elif indicator_1 == "Awesome Oscillator": 
        url = "https://www.ifcm.co.uk/ntx-indicators/awesome-oscillator"
        return url
    
    
    elif indicator_1 == "ADX": 
        url = """https://www.ifcm.co.uk/ntx-indicators/awesome-oscillator"""
        return url
    
    
    
    elif indicator_1 == "AROON": 
        url = """https://www.investopedia.com/terms/a/aroon.asp"""
        return url
    
    
    elif indicator_1 == "Average True Range": 
        url = """https://www.ifcm.co.uk/ntx-indicators/awesome-oscillatore"""
        return url
    
    
    elif indicator_1 == "Bollinger Bands": 
        url = "https://www.investopedia.com/trading/using-bollinger-bands-to-gauge-trends/"
        return url
    
    
    elif indicator_1 == "Chaikin Money Flow": 
        url = "https://school.stockcharts.com/doku.php?id=technical_indicators:chaikin_money_flow_cmf"
        return url
    
    
    elif indicator_1 == "CCI": 
        url = "https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.CCIIndicator"
        return url
    
    
    elif indicator_1 == "Ease of Movement": 
        url = """https://en.wikipedia.org/wiki/Ease_of_movement"""
        return url
    
    
    elif indicator_1 == "Exponential Moving Average": 
        url = "https://www.investopedia.com/terms/e/ema.asp"
        return url
  
    
    elif indicator_1 == "ICHIMOKU": 
        url = """https://school.stockcharts.com/doku.php?id=technical_indicators:ichimoku_cloud"""
        return url
    elif indicator_1 == "KAMA": 
        url = "https://www.tradingview.com/ideas/kama/"
        return url
    
    elif indicator_1 == "KCI": 
        url = """https://school.stockcharts.com/doku.php?id=technical_indicators:keltner_channels"""
        return url
    
    
    elif indicator_1 == "MFI": 
        url = """https://school.stockcharts.com/doku.php?id=technical_indicators:money_flow_index_mfi"""
        return url
    
    
    elif indicator_1 == "MACD": 
        url = """https://technical-analysis-library-in-python.readthedocs.io/en/latest/ta.html#ta.trend.MACD"""
        return url
    
    
    elif indicator_1 == "Percentage Price Oscillator (PPO)": 
        url = "https://school.stockcharts.com/doku.php?id=technical_indicators:price_oscillators_ppo"
        return url
    
    
    elif indicator_1 == "Percentage Volume Oscillator":
        url = "https://school.stockcharts.com/doku.php?id=technical_indicators:percentage_volume_oscillator_pvo"
        return url
    
    
    elif indicator_1 == "Rate of Change":
        url = "https://school.stockcharts.com/doku.php?id=technical_indicators:rate_of_change_roc_and_momentum"
        return url
    
    
    elif indicator_1 == "Relative Strength Index":
        url = "https://www.investopedia.com/terms/r/rsi.asp"
        return url
    
    
    elif indicator_1 == "Simple Moving Average":
        url = "https://www.investopedia.com/terms/s/sma.asp"
        return url
    
    elif indicator_1 == "ULCI": 
        url = """https://school.stockcharts.com/doku.php?id=technical_indicators:ulcer_index"""
        return url
    
    elif indicator_1 == "VWAP": 
        url = """https://school.stockcharts.com/doku.php?id=technical_indicators:vwap_intraday"""
        return url
    
    
    elif indicator_1 == "WMA": 
        url = "https://corporatefinanceinstitute.com/resources/knowledge/trading-investing/weighted-moving-average-wma/"
        return url


# In[6]:


if __name__ == '__main__':
    app.run_server()


# In[ ]: