talib_args.py

import talib

# routine to get args required for talib function

def find_talib_args(func):
    s = eval('talib.' + func + '.__doc__')
    try:
        s = s.splitlines()[0].split('(')[1].split(')')[0].replace('[','').replace(']','').replace('?','')
        return s.split(',')
    except:
        return None
    
func='WILLR'
print(eval('talib.' + func + '.__doc__'))
print(find_talib_args(func))

talib_calcs.py

import pandas as pd
from datetime import datetime, timezone
import pytz
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline

from pandas_highcharts.core import serialize
from pandas_highcharts.display import display_charts
    
from fintools import *

tickers =  ['^GSPC','^DJI','^NDX','^OEX','SPY','XLF']
symbols = ['GSPC','DJI','NDX','OEX','SPY','XLF']

start = datetime(2018, 1, 1, 0, 0, 0, 0, pytz.utc)
end = datetime(2018, 1, 5, 0, 0, 0, 0, pytz.utc)

data_path = '/home/scubamut/MEGAsync/10_DATA/'
 
da = get_DataArray(tickers, start, end)
                     
dp = da.to_pandas().transpose(2,1,0)

talib_df_function.py

from datetime import datetime, timezone, timedelta
import pandas as pd
import pytz
import xarray as xr
from fintools import get_DataArray, endpoints
import talib
 
start = datetime(2016, 1, 5, 0, 0, 0, 0, pytz.utc)
end = datetime(2017, 1, 1, 0, 0, 0, 0, pytz.utc)
tickers = ['XLP','XLY']
 
da = get_DataArray(tickers, start, end)
prices = da.loc['close'].transpose().to_pandas()

# Apply function to column of DAILY ADJ_CLOSE prices, COLUMN_BY_COLUMN
df = prices.copy()
function = talib.MA
lookback = 21

# make sure that TALIB fuction only requires one price!

try:
    transformed = pd.DataFrame({etf:function(df[etf], lookback) for etf in df.columns}).dropna()
except:
    print('ValueError: Shape of passed values is incorrect!')

# print(transformed)

MA_daily = transformed
print(MA_daily[:5])

end_points = endpoints(period='M', trading_days=df.index)
df = prices.loc[end_points]
function = talib.MA
lookback = 3

# make sure that TALIB fuction only requires one price!

try:
    transformed = pd.DataFrame({etf:function(df[etf], lookback) for etf in df.columns}).dropna()
except:
    print('ValueError: Shape of passed values is incorrect!')
    
MA_monthly = transformed
MA_monthly[:5]

talib_function.py

from datetime import datetime, timezone, timedelta
import pytz
import xarray as xr
from fintools import get_DataArray
import talib
 
start = datetime(2016, 1, 5, 0, 0, 0, 0, pytz.utc)
end = datetime(2016, 3, 1, 0, 0, 0, 0, pytz.utc)
tickers = ['XLP','XLY']
 
da = get_DataArray(tickers, start, end)
xlp = da.loc['close','XLP'].to_pandas()

print(talib.STDDEV(xlp.values,10))

print_stats(xlp)

talib_plot.py

import talib
import pandas as pd
%matplotlib inline

SPY = pd.read_csv('/home/scubamut/MEGAsync/10_DATA/daily/etfs/SPY.csv')

def ADXR(data, args_ls):
    try:
        return talib.ADXR(data.high.values, data.low.values, data.close.values, args_ls[0])
    except :
        print ('ADXR: USING DEFAULT PARAMETERS')
        return talib.ADXR(data.high.values, data.low.values, data.close.values)
    
print(ADXR (SPY, [252]))

data = SPY
func = "ADXR"
args = "data.high.values, data.low.values, data.close.values, 252"

mycode = "data[func] = talib." + func + "(" + args + ")"
exec (mycode)

data[func].plot(grid=True)