import pandas as pd
import numpy as np
import yfinance
from mpl_finance import candlestick_ohlc
import matplotlib.dates as mpl_dates
import matplotlib.pyplot as plt

plt.rcParams['figure.figsize'] = [12, 7]

plt.rc('font', size=14)

name = 'SPY'
ticker = yfinance.Ticker(name)
df = ticker.history(interval="1d",start="2020-01-01",end="2021-06-18")

df['Date'] = pd.to_datetime(df.index)
df['Date'] = df['Date'].apply(mpl_dates.date2num)

df = df.loc[:,['Date', 'Open', 'High', 'Low', 'Close']]
def isSupport(df,i):
  support = df['Low'][i] < df['Low'][i-1]  and df['Low'][i] < df['Low'][i+1] \
  and df['Low'][i+1] < df['Low'][i+2] and df['Low'][i-1] < df['Low'][i-2]
  return support

def isResistance(df,i):
  resistance = df['High'][i] > df['High'][i-1]  and df['High'][i] > df['High'][i+1] \
  and df['High'][i+1] > df['High'][i+2] and df['High'][i-1] > df['High'][i-2] 
  return resistance

levels = []
for i in range(2,df.shape[0]-2):
  if isSupport(df,i):
    levels.append((i,df['Low'][i]))
  elif isResistance(df,i):
    levels.append((i,df['High'][i]))
 
    
def plot_all():
  fig, ax = plt.subplots()

  candlestick_ohlc(ax,df.values,width=0.6, \
                   colorup='green', colordown='red', alpha=0.8)

  date_format = mpl_dates.DateFormatter('%d %b %Y')
  ax.xaxis.set_major_formatter(date_format)
  fig.autofmt_xdate()

  fig.tight_layout()

  for level in levels:
    plt.hlines(level[1],xmin=df['Date'][level[0]],\
               xmax=max(df['Date']),colors='blue')
  fig.show()
  
plot_all()


s =  np.mean(df['High'] - df['Low'])

def isFarFromLevel(l):
  return np.sum([abs(l-x) < s  for x in levels]) == 0

levels = []
for i in range(2,df.shape[0]-2):
  if isSupport(df,i):
    l = df['Low'][i]

    if isFarFromLevel(l):
      levels.append((i,l))

  elif isResistance(df,i):
    l = df['High'][i]

    if isFarFromLevel(l):
      levels.append((i,l))

plot_all()