full history stock chart like IBD in multipage pdf

gistfile1.txt

import json
from tqdm import tqdm
from bs4 import BeautifulSoup
import requests
import pandas_ta as ta
import yfinance as yf
import pandas as pd
import numpy as np

import mplfinance as mpf
import matplotlib.pyplot as plt
import matplotlib.ticker as mticker
import matplotlib.dates as mdates
from matplotlib.backends.backend_pdf import PdfPages

# !!! you need set stock symbol, if you want set other index
# how many bars you want on each page, and how many bars overlaping you want

STOCK = 'TSLA'
INDEX = '^GSPC' # S&P500
bar_in_page = 220
shift = 35


# get stock data 
def get_ohlc (stock, period = 'max', interval = '1d'):
    df_ohlc = yf.Ticker(stock.upper()).history(actions = False, period = period, interval = interval)
    return df_ohlc

df = get_ohlc(STOCK) # main DataFrame for join everything
df_idx = get_ohlc(INDEX)

df=df.join(df_idx['Close'], rsuffix='_idx')


# add TA columns 

df.ta.sma(length=50,append=True)
df.ta.sma(length=200,append=True)
df.ta.sma(length=150,append=True)
df.ta.ema(length=20,append=True)
df['VOL_50'] = df.ta.sma(close=df['volume'], length=50)

# add RS-line column

stock_close = df['close']
ind_close = df['Close_idx']
df['rs_line'] = stock_close/ind_close*100 * stock_close.shift(60)/(stock_close/ind_close *100).shift(60)*0.68  # 0.68 for placing like in  IBD chart


# add space to the right side of chart

dfpad = df.tail(2).copy()
dfpad.loc[:,:] = float('nan')
newdf = df.append(dfpad)
df = newdf


# todo - get financial info like EPS and Sales

def get_macro_info(stock="AAPL", period='q'):
    pass

# make chunks for export in multiple pages pdf, I guess there is the way to do the same better 

iter_list = list(range(len(df)))
#bar_in_page = 220
#shift = 35
chunks = [iter_list[i:i + bar_in_page] for i in range(0, len(iter_list), bar_in_page-shift)] 
pages = [(x[0],x[-1]+1) for x in chunks] # pages[n][0] - slice start, pages[n][1] - slice end


# styling chart

mc = mpf.make_marketcolors(up='#2A3FE5', down='#DB39AD', inherit=True)

base_style = {  'axes.titlesize':       5,
                'axes.labelsize':       5,
                'lines.linewidth':      3,
                'lines.markersize':     4,
                'ytick.left':           False,
                'ytick.right':          True,
                'ytick.labelleft':      False,   
                'ytick.labelright':     True, 
                'xtick.labelsize':      6,
                'ytick.labelsize':      6,
                'axes.linewidth':       0.8,
                
                'grid.alpha':           0.2}

ibd = mpf.make_mpf_style(marketcolors=mc, mavcolors=['green', 'red', 'black', 'blue'], y_on_right=True, rc=base_style)

def get_pdf(pages):
    for (start,end) in pages:
        ### !!! temporary replace to chunks loop
        df_slice = df[start:end]
        print(start,end)


        # ======== starting plot =======


        # making grid of axis
        egrid = (21,29)

        fig = mpf.figure(style=ibd, figsize=(11, 8))
        ax1 = plt.subplot2grid(egrid,(2,0),colspan=29,rowspan=15)
        ax3 = plt.subplot2grid(egrid,(0,0),colspan=29,rowspan=2,sharex=ax1)
        ax2 = plt.subplot2grid(egrid,(17,0),colspan=29,rowspan=4,sharex=ax1)


        #  Set locator intervals


        lim_bottom =min(df_slice['rs_line'].min(), df_slice['SMA_200'].min())
        lim_top =  max(df_slice['rs_line'].max(), df_slice['SMA_200'].max(),df_slice['close'].max())


        #  Включаем видимость делений:

        ax1.minorticks_on()

        ax1.grid(which='major',color='k')
        ax1.grid(which='minor',color='gray')
        ax2.grid(which='major',color='gray')



        ax2.tick_params(axis='x', which='major', pad = 8)

        ax1.tick_params(axis='x', which='both',labelbottom= False, labeltop=False )
        ax3.tick_params(axis='x', which='both',labelbottom= False, labeltop=False, bottom=False, top=True, direction='in')



        ax1.xaxis.set_major_formatter(mdates.DateFormatter('%m'))
        ax1.xaxis.set_major_locator(mticker.IndexLocator(base=30, offset=0))
        ax1.xaxis.set_minor_formatter(mdates.DateFormatter('%d'))
        ax1.xaxis.set_minor_locator(mticker.IndexLocator(base=5, offset=0))

        maxprice = df_slice.high.max()
        if maxprice > 100:
            locator_size = 100
        elif maxprice < 10:
            locator_size = 1
        else:
            locator_size = 10


        ax1.yaxis.set_major_locator(mticker.MultipleLocator(locator_size))
        ax1.yaxis.set_minor_locator(mticker.MultipleLocator(locator_size/4))
        ax2.yaxis.set_major_locator(mticker.MultipleLocator(df_slice['volume'].max()/5))



        # additional lines
        sp500 = mpf.make_addplot( df_slice['Close_idx'], color='black', width=0.9, panel=0, title=f'{STOCK.upper()} {df_slice.index[0]} - {df_slice.index[-1]}', ax=ax3)

        vol50 = mpf.make_addplot(
            df_slice['VOL_50'], panel=2, color='red', width=0.6, ax=ax2)
        rs_line = mpf.make_addplot(
            df_slice['rs_line'], ax=ax1, color='blue', width=1.2, alpha=0.35, panel=1)

        sma200 = mpf.make_addplot(
            df_slice['SMA_200'], ax=ax1,color='black', width=0.8, panel=1)
        sma50 = mpf.make_addplot(
            df_slice['SMA_50'], ax=ax1,color='red', width=0.6, panel=1)
        sma150 = mpf.make_addplot(
        df_slice['SMA_150'], ax=ax1,color='gray', width=0.2, alpha=0.8, panel=1)
        ema20 = mpf.make_addplot(
        df_slice['EMA_20'], ax=ax1,color='green', width=0.3, panel=1)




        mpf.plot(df_slice, ax=ax1, volume=ax2,addplot=[sp500, rs_line, sma200, sma150, sma50, ema20, vol50], datetime_format="%b'20",tight_layout=True, xrotation=0,
            scale_width_adjustment=dict(volume=0.2),ylim=(lim_bottom*0.1,lim_top*1.1))

        # scale_width_adjustment=dict(volume=0.2), addplot=[sp500, rs_line, sma200, sma150, sma50, ema20, vol50],
        # datetime_format="%b'20",tight_layout=True, xrotation=0, ylim=(lim_bottom*0.1,lim_top*1.1),update_width_config=dict(ohlc_linewidth=0.9,ohlc_ticksize=0.4)

        # remove gaps among axis panels
        plt.tight_layout(h_pad= -0.8)

        fig.savefig(f'figure{end}.pdf')

get_pdf(pages)