def get_darwin_dataset(self, assets, cumulative=True, rebase=False):
# Type checks for mandatorily used arguments
if isinstance(assets, str):
_symbols = [assets]
elif isinstance(assets, list):
_symbols = [a for a in assets]
else:
raise TypeError("Invalid DARWIN symbols array '{0}'. "
"It should be a list of strings.".format(assets))
# Get Quotes
_portfolio = self.info_api._Get_Historical_Quotes_(_symbols=_symbols)
# Rebase to common dates
if rebase:
_portfolio.dropna(inplace=True)
# Calculate cumulative portfolio returns
_portfolio = calculate_portfolio_returns(_portfolio,
cumulative=cumulative)
# symbols now contains a dataframe of Quotes by asset, one column per.
# symbols.columns will have a different source later on after calculating
# the portfolio
_portfolio.columns = ['Close']
return qm.Chart(_portfolio)
def update_graph_from_dropdown(dropdown_nsub, multi, arglist, dropdown):
df = None
if dropdown is None or len(dropdown) <= 0:
return None
if len(dropdown.split('.')) > 1:
df = fetch_ib_history(dropdown)
else:
try:
df = web.DataReader(dropdown, 'yahoo', dt.datetime(2016, 1, 1),
dt.datetime.now())
except Exception as e:
try:
df = bca.fetch_history(dropdown, dt.datetime(2016, 1, 1),
dt.datetime.now())
except Exception:
pass
if df is None or len(df) <= 0:
print(f'update_graph_from_dropdown: no data for {dropdown}')
return None
print(df.tail())
print('Loading')
ch = qm.Chart(df)
# Get functions and arglist for technical indicators
if arglist:
arglist = arglist.replace('(', '').replace(')', '').split(';')
arglist = [args.strip() for args in arglist]
for function, args in zip(multi, arglist):
if args:
args = args.split(',')
newargs = []
for arg in args:
try:
arg = int(arg)
except:
try:
arg = float(arg)
except:
pass
newargs.append(arg)
print(newargs)
# Dynamic calling
getattr(qm, function)(ch, *newargs)
else:
getattr(qm, function)(ch)
else:
for function in multi:
# Dynamic calling
getattr(qm, function)(ch)
# Return plot as figure
fig = ch.to_figure(width=1100)
return fig
def update_graph_from_dropdown(dropdown, multi, arglist):
print('start')
# Get Quantmod Chart
df = web.DataReader(dropdown, 'yahoo', dt.datetime(2016, 1, 1),
dt.datetime.now())
print('Loading')
ch = qm.Chart(df)
print(ch)
# try:
# df = web.DataReader(dropdown, 'yahoo', dt.datetime(2016, 1, 1), dt.datetime.now())
# print('Loading')
# ch = qm.Chart(df)
# print(ch)
# except:
# pass
# Get functions and arglist for technical indicators
if arglist:
arglist = arglist.replace('(', '').replace(')', '').split(';')
arglist = [args.strip() for args in arglist]
for function, args in zip(multi, arglist):
if args:
args = args.split(',')
newargs = []
for arg in args:
try:
arg = int(arg)
except:
try:
arg = float(arg)
except:
pass
newargs.append(arg)
print(newargs)
# Dynamic calling
getattr(qm, function)(ch, *newargs)
else:
getattr(qm, function)(ch)
else:
for function in multi:
# Dynamic calling
getattr(qm, function)(ch)
# Return plot as figure
fig = ch.to_figure(width=1100)
return fig
def update_graph_from_dropdown(dropdown, multi, arglist):
# Get Quantmod Chart
try:
#df = web.DataReader(dropdown, 'stooq', dt.datetime(2016, 1, 1), dt.datetime.now())
df = web.DataReader(dropdown, 'moex', dt.datetime(2016, 1, 1), dt.datetime.now()). \
rename(dict(zip(['OPEN', 'LOW', 'HIGH', 'CLOSE', 'VALUE'], ['Open', 'High', 'Low', 'Close', 'Volume'])),
axis=1)
print('Loading')
ch = qm.Chart(df)
except:
print('finito')
raise
# Get functions and arglist for technical indicators
if arglist:
arglist = arglist.replace('(', '').replace(')', '').split(';')
arglist = [args.strip() for args in arglist]
for function, args in zip(multi, arglist):
if args:
args = args.split(',')
newargs = []
for arg in args:
try:
arg = int(arg)
except:
try:
arg = float(arg)
except:
pass
newargs.append(arg)
print(newargs)
# Dynamic calling
getattr(qm, function)(ch, *newargs)
else:
getattr(qm, function)(ch)
else:
for function in multi:
# Dynamic calling
getattr(qm, function)(ch)
# Return plot as figure
fig = ch.to_figure(width=1100)
return fig
def update_graph_from_dropdown(dropdown, multi, arglist):
# Get Quantmod Chart
print('Loading')
strategy, config, res = setup_config(dropdown)
candles, trade_scatter = setup_chart(res)
ch = qm.Chart(candles, src=src)
# Get functions and arglist for technical indicators
if arglist:
for function in multi:
try:
config = talib_dict(json.loads(arglist))
indicator = function.split("_")[1]
newargs = config[indicator]
# Dynamic calling
fn = getattr(qm, function)
fn(ch, **newargs)
except Exception as e:
print(e)
getattr(qm, function)(ch)
pass
else:
for function in multi:
# Dynamic calling
getattr(qm, function)(ch)
fig = ch.to_figure(width=1100)
# hack figure
index = 0
for i in range(len(fig["layout"].keys())):
axis = "yaxis" + str(i)
if axis in fig["layout"]:
index = i + 1
yrange = [candles["low"].min(), candles["high"].max()]
fig["layout"]["yaxis"]["range"] = yrange
fig["layout"]["yaxis" + str(index)] = fig["layout"]["yaxis2"]
fig["layout"]["plot_bgcolor"] = 'rgba(0, 0, 0, 0.00)'
trade_scatter["yaxis"] = "y1"
fig["data"].append(trade_scatter)
return fig
'''
Created on Feb 4, 2019
@author: bperlman1
'''
import dash
import quantmod as qm
import datetime as dt
import pandas_datareader.data as web
import dash_core_components as dcc
import dash_html_components as html
app = dash.Dash(__name__)
df = web.DataReader('SPY', 'yahoo', dt.datetime(2016, 1, 1), dt.datetime.now())
print('Loading')
ch = qm.Chart(df)
fig = ch.to_figure(width=1100)
app.layout = html.Div([
dcc.Graph(id='my-graph', figure=fig),
], )
if __name__ == '__main__':
app.server.run(port=8500)
# In[]: import numpy as np import quantmod as qm import pandas as pd import pandas_datareader as web # In[]: ticker = 'AAPL' df = web.DataReader(ticker, data_source='yahoo', start='2016/01/01') df = df.tail(365) ch = qm.Chart(df, start='2015/01/01', end='2017/03/02') ch.has_open ch.has_high ch.has_low ch.has_close ch.op ch.df ch.ind ch.pri ch.adjust(inplace=True) ch.adjust_volume(inplace=True) ch.has_OHLC print(ch.has_OHLCV) ch.add_MA()
