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import streamlit as st |
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import mplfinance as mpf |
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import pandas as pd |
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import datetime |
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from PIL import Image |
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@st.cache(show_spinner=False) |
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def get_graph(df, no_days): |
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plot_df = df.iloc[-no_days:] |
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plot_df = plot_df.set_index('Date') |
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filename = 'CandelPlot.png' |
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mpf.plot(plot_df,type='candle',mav=(21, 55), style="yahoo", figratio=(60,20), linecolor='#00ff00', savefig=filename) |
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def buy_sell_decision(st, lt, close, last): |
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if st == 'None' or lt == 'None': |
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return 'Dont trade', close, last |
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if st >= lt: |
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if close >= st: |
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return 'Buy', last, None |
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elif close <= st: |
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return 'sell', None, last |
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if lt > st : |
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return 'Dont trade', close, last |
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def get_SMA_df(df): |
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moving_average_df = df |
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moving_average_df['St21'] = moving_average_df['Close'].rolling(window = 21, min_periods = 21).mean() |
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moving_average_df['Lt55'] = moving_average_df['Close'].rolling(window = 55, min_periods = 55).mean() |
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moving_average_df = moving_average_df.fillna('None') |
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st_list = moving_average_df['St21'].to_list() |
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lt_list = moving_average_df['Lt55'].to_list() |
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close_price_list = moving_average_df['Close'].to_list() |
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last_price_list = moving_average_df['Last'].to_list() |
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buy_sell_list = [] |
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buy_price_list = [] |
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sell_price_list = [] |
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for idx, value in enumerate(st_list): |
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dec_label, buy_price, sell_price = buy_sell_decision(st_list[idx], lt_list[idx], close_price_list[idx], last_price_list[idx]) |
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buy_sell_list.append(dec_label) |
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buy_price_list.append(buy_price) |
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sell_price_list.append(sell_price) |
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moving_average_df['buy/sell'], moving_average_df['buy_price'], moving_average_df['sell_price'] = buy_sell_list, buy_price_list, sell_price_list |
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return moving_average_df |
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def get_action_dict(sma_df, date): |
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df = sma_df.set_index('Date') |
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try: |
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row = df.loc[datetime.datetime(date.year, date.month, date.day)] |
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action_dict = {} |
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action_dict['symbol'] = row['Symbol'] |
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action_dict['action'] = row['buy/sell'] |
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if action_dict['action'] == 'Buy': |
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price = row['buy_price'] |
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else: |
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price = row['sell_price'] |
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action_dict['price'] = price |
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except: |
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action_dict = None |
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return action_dict |
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def main(): |
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st.set_page_config( |
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page_title="Project", |
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layout="wide", |
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initial_sidebar_state="expanded" |
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) |
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st.write('Upload a CSV file') |
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col1, col2 = st.columns(2) |
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with col1: |
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spectra = st.file_uploader("upload file", type={"csv", "txt"}) |
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if spectra is not None: |
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df = pd.read_csv(spectra) |
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df['Date'] = df['Date'].astype('datetime64[ns]') |
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sma_df =get_SMA_df(df) |
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plot_days = st.slider('Select No. of days to plot graph', 56, len(df), 100) |
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st.write("Plot graph for last", plot_days, 'days') |
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get_image = st.button('Get graph') |
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if spectra is not None: |
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with col2: |
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trade_date = st.date_input("Select Day for trading", max(df['Date']), min_value=min(df['Date']), max_value=max(df['Date'])) |
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get_action = st.button('Check trade or No trade') |
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ref_flag = False |
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if get_action: |
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dict_action = get_action_dict(sma_df, trade_date) |
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if dict_action == None: |
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st.error("Something Went Wrong please try with different date", icon="🚨") |
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else: |
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symbol = dict_action['symbol'] |
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action = dict_action['action'] |
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price = dict_action['price'] |
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st.success(f''' |
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* Symbol : {symbol} |
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* Action : **{action}** |
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* {action} Price : {price} |
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''') |
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ref_flag, get_image = True, True |
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if get_image: |
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get_graph(df, plot_days) |
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image = Image.open('CandelPlot.png') |
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st.image(image, use_column_width='auto', caption='Blue Line = 21-SMA, Orange Line = 55-SMA') |
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if __name__ == '__main__': |
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main() |
