finplot/finplot/examples/bfx.py at master · robot-python/finplot · GitHub

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#!/usr/bin/env python3

import math

import pandas as pd

import finplot as fplt

import requests

import time

def cumcnt_indices(v):

v[~v] = math.nan

cumsum = v.cumsum().fillna(method='pad')

reset = -cumsum[v.isnull()].diff().fillna(cumsum)

r = v.where(v.notnull(), reset).cumsum().fillna(0.0)

return r.astype(int)

def td_sequential(close):

close4 = close.shift(4)

td = cumcnt_indices(close > close4)

ts = cumcnt_indices(close < close4)

return td, ts

def update():

# load data

limit = 500

start = int(time.time()*1000) - (500-2)*60*1000

url = 'https://api.bitfinex.com/v2/candles/trade:1m:tBTCUSD/hist?limit=%i&sort=1&start=%i' % (limit, start)

table = requests.get(url).json()

df = pd.DataFrame(table, columns='time open close high low volume'.split())

# calculate indicator

tdup,tddn = td_sequential(df['close'])

df['tdup'] = [('%i'%i if 0<i<10 else '') for i in tdup]

df['tddn'] = [('%i'%i if 0<i<10 else '') for i in tddn]

# pick columns for our three data sources: candlesticks and TD sequencial labels for up/down

candlesticks = df['time open close high low'.split()]

volumes = df['time open close volume'.split()]

td_up_labels = df['time high tdup'.split()]

td_dn_labels = df['time low tddn'.split()]

plot_candles.candlestick_ochl(candlesticks)

plot_volume.volume_ocv(volumes, ax=ax.overlay())

plot_td_up.labels(td_up_labels, color='#009900')

plot_td_dn.labels(td_dn_labels, color='#990000', anchor=(0.5,0))

plots = []

ax = fplt.create_plot('Realtime Bitcoin/Dollar 1m TD Sequential (BitFinex REST)', init_zoom_periods=100, maximize=False)

plot_candles, plot_volume, plot_td_up, plot_td_dn = fplt.live(4)

update()

fplt.timer_callback(update, 5.0) # update (using synchronous rest call) every N seconds

fplt.show()

finplot/finplot/examples/bfx.py at master · robot-python/finplot · GitHub

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