mementum / bta-lib Goto Github PK

I am trying to calculate the ema with the default periods.

import btalib
import pandas as pd
df = pd.read_csv("C:\\data\\nifty2019.csv")
df['Date'] = pd.to_datetime(df['Date'])
kama = btalib.ema(df.Close)

This is giving me an error trace like below. Can you help me to see if something is wrong with the way I am using it?

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
C:\app\Anaconda3\lib\site-packages\pandas\core\series.py in __setitem__(self, key, value)
   1013         try:
-> 1014             self._set_with_engine(key, value)
   1015         except com.SettingWithCopyError:

C:\app\Anaconda3\lib\site-packages\pandas\core\series.py in _set_with_engine(self, key, value)
   1053         try:
-> 1054             self.index._engine.set_value(values, key, value)
   1055             return

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.set_value()

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.set_value()

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()

TypeError: 'slice(29, None, None)' is an invalid key

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
<ipython-input-3-3a859967fb56> in <module>
----> 1 kama = btalib.ema(df.Close)

C:\app\Anaconda3\lib\site-packages\btalib\indicator.py in __call__(cls, *args, **kwargs)
    150         # Auto-call base classes
    151         for b_init in reversed(list(dict.fromkeys(b.__init__ for b in bases))):
--> 152             b_init(self, *args, **kwargs)
    153 
    154         # delete old aliases only meant for operational purposes

C:\app\Anaconda3\lib\site-packages\btalib\indicators\ema.py in __init__(self, poffset)
     37     def __init__(self, poffset=0):  # see above for poffset
     38         span, seed, poff = self.p.period, self.p._seed, poffset
---> 39         self.o.ema = self.i0._ewm(span=span, _seed=seed, _poffset=poff).mean()

C:\app\Anaconda3\lib\site-packages\btalib\meta\lines.py in call_op(*args, **kwargs)
    377                     sargs.append(arg)
    378 
--> 379                 result[self._minidx:] = r = op(*sargs, **kwargs)  # run/store
    380                 result = result.astype(r.dtype, copy=False)
    381                 return self._line._clone(result, period=self._minperiod)

C:\app\Anaconda3\lib\site-packages\pandas\core\series.py in __setitem__(self, key, value)
   1040                     pass
   1041 
-> 1042             self._set_with(key, value)
   1043 
   1044         if cacher_needs_updating:

C:\app\Anaconda3\lib\site-packages\pandas\core\series.py in _set_with(self, key, value)
   1062         if isinstance(key, slice):
   1063             indexer = self.index._convert_slice_indexer(key, kind="getitem")
-> 1064             return self._set_values(indexer, value)
   1065 
   1066         elif is_scalar(key) and not is_integer(key) and key not in self.index:

C:\app\Anaconda3\lib\site-packages\pandas\core\series.py in _set_values(self, key, value)
   1109         if isinstance(key, Series):
   1110             key = key._values
-> 1111         self._data = self._data.setitem(indexer=key, value=value)
   1112         self._maybe_update_cacher()
   1113 

C:\app\Anaconda3\lib\site-packages\pandas\core\internals\managers.py in setitem(self, **kwargs)
    559 
    560     def setitem(self, **kwargs):
--> 561         return self.apply("setitem", **kwargs)
    562 
    563     def putmask(self, **kwargs):

C:\app\Anaconda3\lib\site-packages\pandas\core\internals\managers.py in apply(self, f, filter, **kwargs)
    440                 applied = b.apply(f, **kwargs)
    441             else:
--> 442                 applied = getattr(b, f)(**kwargs)
    443             result_blocks = _extend_blocks(applied, result_blocks)
    444 

C:\app\Anaconda3\lib\site-packages\pandas\core\internals\blocks.py in setitem(self, indexer, value)
    875 
    876         # length checking
--> 877         check_setitem_lengths(indexer, value, values)
    878         exact_match = (
    879             len(arr_value.shape)

C:\app\Anaconda3\lib\site-packages\pandas\core\indexers.py in check_setitem_lengths(indexer, value, values)
    121             if len(value) != length_of_indexer(indexer, values):
    122                 raise ValueError(
--> 123                     "cannot set using a slice indexer with a "
    124                     "different length than the value"
    125                 )

ValueError: cannot set using a slice indexer with a different length than the value

Traceback (most recent call last):
File "/Users/cosmos/GitHub/haasomeapitools/.env/lib/python3.7/site-packages/pandas/core/series.py", line 1014, in setitem
self._set_with_engine(key, value)
File "/Users/cosmos/GitHub/haasomeapitools/.env/lib/python3.7/site-packages/pandas/core/series.py", line 1054, in _set_with_engine
self.index._engine.set_value(values, key, value)
File "pandas/_libs/index.pyx", line 96, in pandas._libs.index.IndexEngine.set_value
File "pandas/_libs/index.pyx", line 106, in pandas._libs.index.IndexEngine.set_value
File "pandas/_libs/index.pyx", line 116, in pandas._libs.index.IndexEngine.get_loc
TypeError: 'slice(11, None, None)' is an invalid key

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/Users/cosmos/GitHub/haasomeapitools/btalibtest.py", line 23, in
mama, fama = btalib.mama(data.High,data.Low,fastlimit=10,slowlimit=5)
File "/Users/cosmos/GitHub/haasomeapitools/.env/lib/python3.7/site-packages/btalib/indicator.py", line 152, in call
b_init(self, *args, **kwargs)
File "/Users/cosmos/GitHub/haasomeapitools/.env/lib/python3.7/site-packages/btalib/indicators/mama.py", line 79, in init
_mama = p0._ewm(alpha=alpha, span=1, _seed=SEED_ZERO)._mean()
File "/Users/cosmos/GitHub/haasomeapitools/.env/lib/python3.7/site-packages/btalib/meta/lines.py", line 357, in _mean
return self._apply(_dynalpha) # triggers getattr for _apply
File "/Users/cosmos/GitHub/haasomeapitools/.env/lib/python3.7/site-packages/btalib/meta/lines.py", line 379, in call_op
result[self._minidx:] = r = op(*sargs, **kwargs) # run/store
File "/Users/cosmos/GitHub/haasomeapitools/.env/lib/python3.7/site-packages/pandas/core/series.py", line 1042, in setitem
self._set_with(key, value)
File "/Users/cosmos/GitHub/haasomeapitools/.env/lib/python3.7/site-packages/pandas/core/series.py", line 1064, in _set_with
return self._set_values(indexer, value)
File "/Users/cosmos/GitHub/haasomeapitools/.env/lib/python3.7/site-packages/pandas/core/series.py", line 1111, in _set_values
self._data = self._data.setitem(indexer=key, value=value)
File "/Users/cosmos/GitHub/haasomeapitools/.env/lib/python3.7/site-packages/pandas/core/internals/managers.py", line 561, in setitem
return self.apply("setitem", **kwargs)
File "/Users/cosmos/GitHub/haasomeapitools/.env/lib/python3.7/site-packages/pandas/core/internals/managers.py", line 442, in apply
applied = getattr(b, f)(**kwargs)
File "/Users/cosmos/GitHub/haasomeapitools/.env/lib/python3.7/site-packages/pandas/core/internals/blocks.py", line 877, in setitem
check_setitem_lengths(indexer, value, values)
File "/Users/cosmos/GitHub/haasomeapitools/.env/lib/python3.7/site-packages/pandas/core/indexers.py", line 124, in check_setitem_lengths
"cannot set using a slice indexer with a "

https://en.wikipedia.org/wiki/Donchian_channel

Hello, I'm trying to use btalib and I'm having some trouble when having it run from inside a thread.

The below code works fine:

import [...]

symbol = 'BTCEUR'

with open('./data/' + symbol + '/' + symbol + '_kline.p', 'rb') as handle:
    kline_df = pickle.load(handle)

sma = btalib.sma(kline_df).df
print(sma)

But when I try to use threads...

import [...]

symbol = 'BTCEUR'

with open('./data/' + symbol + '/' + symbol + '_kline.p', 'rb') as handle:
    kline_df = pickle.load(handle)

def thread():
    sma = btalib.sma(kline_df).df
    print(sma)
    time.sleep(5)

x = threading.Thread(target=thread)
x.start()

... I get the following error:

Traceback (most recent call last):
  File "/usr/lib/python3.9/threading.py", line 954, in _bootstrap_inner
    self.run()
  File "/usr/lib/python3.9/threading.py", line 892, in run
    self._target(*self._args, **self._kwargs)
  File "/home/nick/storage/Documents/_Projects/Python/Crypto/btalib_test.py", line 13, in thread
    sma = btalib.sma(kline_df).df
  File "/home/nick/storage/Documents/_Projects/Python/Crypto/venv/lib/python3.9/site-packages/btalib/indicator.py", line 110, in __call__
    self.outputs = self.o = meta.outputs._from_class(cls)
  File "/home/nick/storage/Documents/_Projects/Python/Crypto/venv/lib/python3.9/site-packages/btalib/meta/outputs.py", line 30, in _from_class
    return _CLSOUTPUTS[cls]()  # defvals params in dict format
  File "/home/nick/storage/Documents/_Projects/Python/Crypto/venv/lib/python3.9/site-packages/btalib/meta/lines.py", line 630, in __init__
    metadata.minperiods[self] = [1] * len(self)
AttributeError: '_thread._local' object has no attribute 'minperiods'

Any help would be appreciated!

SMMA Function is working good when calling in not threading modus however when code is running in muli thread we get the following error:

File "/home/engine.traderbot/src/indicators/smma.py", line 192, in __calculate_smma
tmp = btalib.smma(self.ohlc_data[self.source], period=self.length)

File "/home/anaconda/envs/traderbot/lib/python3.7/site-packages/btalib/indicator.py", line 110, in call
self.outputs = self.o = meta.outputs._from_class(cls)
File "/home/anaconda/envs/traderbot/lib/python3.7/site-packages/btalib/meta/outputs.py", line 30, in _from_class
return _CLSOUTPUTScls # defvals params in dict format
File "/home/anaconda/envs/traderbot/lib/python3.7/site-packages/btalib/meta/lines.py", line 630, in init
metadata.minperiods[self] = [1] * len(self)

BTA-LIB is running into compatibility issues with Numpy. From backtrader forum:
bta-lib adx() error

@run-out I found the library version incompatibility! I was running with numpy v1.20.1, the latest version. I installed an older version, the version of numpy available right around when btalib v1.0.0 was released, numpy v1.18.2. It worked 🙌🏼 So that means bta-lib needs to be updated to work with the latest versions of pandas and numpy.
Thanks again for taking the time to work this out with me 👍🏼🌷
Here's my output now:

(sandbox) 13:13 • screener • master • d5822cb ✗
❯ python bta-adx.py
numpy v1.18.2
pandas v1.0.4
btalib v1.0.0
                 Open       High        Low  ...    Volume        rsi        adx
Date                                         ...
2021-03-22  79.989998  81.269997  79.220001  ...  39648600  44.939105  26.393616
2021-03-23  80.129997  80.339996  77.949997  ...  40466600  41.737588  26.112061
2021-03-24  77.550003  78.800003  76.400002  ...  43753600  38.792404  26.252038
2021-03-25  75.849998  76.949997  74.959999  ...  44735100  38.393151  26.729348
2021-03-26  76.620003  77.500000  75.029999  ...  49109400  41.367524  26.915669

Hi,
Thanks for this project! very convenient to use.
I am wondering if it supports dynamic update the indicator values as I feed more newly incoming data. If it is supported, how to do it? I seem not finding the information in the document. If not, is there a suggestion w.r.t how to implement the functionality in my own application on top of bta-lib? Thanks!

I am getting bunch of errors :
result[minidx:] = r = binop(other, *args, **kwargs) # exec / store
Traceback (most recent call last):
File "C:\IB\pyGame\ALGO_AMD.py", line 30, in
mama(amdDF).df
^^^^^^^^^^^
File "C:\IB\pyGame\venv\Lib\site-packages\btalib\indicator.py", line 152, in call
b_init(self, *args, **kwargs)
File "C:\IB\pyGame\venv\Lib\site-packages\btalib\indicators\mama.py", line 79, in init
_mama = p0._ewm(alpha=alpha, span=1, _seed=SEED_ZERO)._mean()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\IB\pyGame\venv\Lib\site-packages\btalib\meta\lines.py", line 357, in _mean
return self._apply(_dynalpha) # triggers getattr for _apply
^^^^^^^^^^^^^^^^^^^^^^
File "C:\IB\pyGame\venv\Lib\site-packages\btalib\meta\lines.py", line 379, in call_op
result[self._minidx:] = r = op(*sargs, **kwargs) # run/store
^^^^^^^^^^^^^^^^^^^^
TypeError: BaseWindow._apply() missing 1 required positional argument: 'name'

My code:
from ib_insync import *
import btalib
import pandas
from btalib import *
from btalib import bbands

ib = IB()
ib.connect('127.0.0.1', 7497, clientId=0)

amd_contract = Stock('AMD', 'SMART', 'USD')

ib.qualifyContracts(amd_contract)
data = ib.reqMktData(amd_contract)
ib.sleep(1)
print(data.marketPrice())

historical_data_amd = ib.reqHistoricalData(
amd_contract,
'',
barSizeSetting='3 mins',
durationStr='2 D',
whatToShow='TRADES',
useRTH=True
)
amdDF = util.df(historical_data_amd)
#amdH = amdDF.filter(['high','low'])
#amdL = amdDF.fi
#print(amdDF.high)
#print (bbands(amdDF).df)
mama(amdDF).df

I Apricate your help .

Thanks

Murthy

I am trying to create trailing ATR with fixed multiplier using mult function but I failed as it throws AttributeError: 'float' object has no attribute 'index' and that makes sense.

My Question is how to do that? Should I need to add index and perform or is there a simple way to do that.

Looking for a direction.

When I run

btalib.dx(btc_df.high, btc_df.low, btc_df.close)

or

btalib.dm(btc_df.high, btc_df.low)

with btc_df.high, btc_df.low and btc_df.close being columns from a pandas data frame (series of floats).

I get:

TypeError Traceback (most recent call last)
in
1 # import talib
2
----> 3 btalib.dx(btc_df.high, btc_df.low, btc_df.close)

~/Documents/external_projects/trading/venv/lib/python3.8/site-packages/btalib/indicator.py in call(cls, *args, **kwargs)
150 # Auto-call base classes
151 for b_init in reversed(list(dict.fromkeys(b.init for b in bases))):
--> 152 b_init(self, *args, **kwargs)
153
154 # delete old aliases only meant for operational purposes

~/Documents/external_projects/trading/venv/lib/python3.8/site-packages/btalib/indicators/directionalmove.py in init(self)
95 if self._plus: # upvmoe > 0 and where upmove > downmove
96 pdm = upmove.clip(lower=0.0) * (upmove > downmove)
---> 97 self._pdm = self._smoother(pdm, **smoothargs)
98
99 if self._minus: # downmove > 0 and where downmove > upmove

~/Documents/external_projects/trading/venv/lib/python3.8/site-packages/btalib/indicator.py in call(cls, *args, **kwargs)
150 # Auto-call base classes
151 for b_init in reversed(list(dict.fromkeys(b.init for b in bases))):
--> 152 b_init(self, *args, **kwargs)
153
154 # delete old aliases only meant for operational purposes

~/Documents/external_projects/trading/venv/lib/python3.8/site-packages/btalib/indicators/directionalmove.py in init(self)
50 p = self.p.period
51 _ewm = self.i0._ewm(span=p, _pearly=self.p._pearly, _seed=self.p._seed)
---> 52 self.o.smacc = _ewm._lfilter(alpha=1.0, beta=(p - 1) / p)
53
54 def _talib(self, kwdict):

~/Documents/external_projects/trading/venv/lib/python3.8/site-packages/btalib/meta/lines.py in _lfilter(self, alpha, beta)
341 return scipy.signal.lfilter([alpha], [1.0, -beta], x)
342
--> 343 return self._apply(_sp_lfilter) # trigger getattr for _apply
344
345 def _mean(self): # meant for ewm with dynamic alpha

~/Documents/external_projects/trading/venv/lib/python3.8/site-packages/btalib/meta/lines.py in call_op(*args, **kwargs)
377 sargs.append(arg)
378
--> 379 result[self._minidx:] = r = op(*sargs, **kwargs) # run/store
380 result = result.astype(r.dtype, copy=False)
381 return self._line._clone(result, period=self._minperiod)

~/Documents/external_projects/trading/venv/lib/python3.8/site-packages/pandas/core/window/rolling.py in _apply(self, func, name, numba_cache_key, **kwargs)
467 return result
468
--> 469 return self._apply_blockwise(homogeneous_func, name)
470
471 def aggregate(self, func, *args, **kwargs):

~/Documents/external_projects/trading/venv/lib/python3.8/site-packages/pandas/core/window/rolling.py in _apply_blockwise(self, homogeneous_func, name)
382 """
383 if self._selected_obj.ndim == 1:
--> 384 return self._apply_series(homogeneous_func, name)
385
386 obj = self._create_data(self._selected_obj)

~/Documents/external_projects/trading/venv/lib/python3.8/site-packages/pandas/core/window/rolling.py in _apply_series(self, homogeneous_func, name)
371 raise DataError("No numeric types to aggregate") from err
372
--> 373 result = homogeneous_func(values)
374 return obj._constructor(result, index=obj.index, name=obj.name)
375

~/Documents/external_projects/trading/venv/lib/python3.8/site-packages/pandas/core/window/rolling.py in homogeneous_func(values)
459 result = np.apply_along_axis(calc, self.axis, values)
460 else:
--> 461 result = calc(values)
462 result = np.asarray(result)
463

~/Documents/external_projects/trading/venv/lib/python3.8/site-packages/pandas/core/window/rolling.py in calc(x)
453 closed=self.closed,
454 )
--> 455 return func(x, start, end, min_periods)
456
457 with np.errstate(all="ignore"):

TypeError: _sp_lfilter() takes 1 positional argument but 4 were given

Python version 3.8.2

Package versions:

bta-lib 1.0.0
numpy 1.19.5
pandas 1.2.1
scipy 1.6.0

As I have mentioned on the community forum:
https://community.backtrader.com/topic/3687/bta-lib-and-bt-indicators-deliver-different-values-when-using-indicator-on-indicator

The bta-lib indicator on indicator gives different results than when using this in backtrader internally.

The problem surfaces when you use RSI on ATR for example.

atr14 = ATR(High, Low, Close, period=14)

This will return a pandas dataframe containing NaN values.

When you feed this to the next indicator, this results in different values from Backtrader:

rsi_atr = RSI(atr14, period=7)

In order to come up with the same results, one should implement the dataframe without the NaN values.

rsi_atr = RSI(atr14.dropna(), period=7)

I am uncertain considering the setup of the bta-lib framework if the dataframe returned from the functions should be stripped of NaN values (losing the index compatibility, don't think that is good) or if bta-lib functions should drop NaN values before computations.

However, in the Backtrader implementation this is done correctly. I feel bta-lib should deliver exactly the same results.

import btalib
import pandas as pd

df = pd.read_csv('2006-day-001.txt', parse_dates=True, index_col='Date')
sma = btalib.sma(df)

gives AttributeError: module 'btalib' has no attribute 'sma'

Im trying to use bta-lib to calculate rsi indicator although it was fine with the sma function but through an error on rsi function
'''
df=pd.read_csv('prices.csv')
sma=btalib.sma(df,period=9)#works fine
rsi=btalib.rsi(df,period=14)#through an error
'''
error= ValueError: cannot set using a slice indexer with a different length than the value... my df len is enough.

I am running a MultiplexSocket on Binance API to get 5 minute klines of around 200 symbols. On every new completed candle I call a "run_technical_analysis" function. Inside that function I calculate indicators for each symbol like this:

period = 14
value = btalib.ema(candlesticks_df.tail(period + 1), period=period) ## Version A
#value = candlesticks_df.Close.tail(14).ewm(span=14).mean() ## Version B

After that I append value.df.tail(1) to a list. On Version A my RAM goes up almost 10 MB every 5 minutes. It seems like the allocated memory for 'value' is not beeing freed. When I use Version B instead there is no such issue.

What can I do to reduce that memory usage?

When I print this:
btalib.stochrsi(df['close'],period=8).df

I only get one column called "stochrsi". But in all trading platforms the "Stoch RSI" is 2 curves. How do I get the values of those 2 curves?

(The parameters for the Stoch RSI would be "Smooth K", "Smooth D", "RSI Length", "Stoch Length")

https://www.backtrader.com/home/helloalgotrading/

Exception has occurred: FileNotFoundError       (note: full exception trace is shown but execution is paused at: _run_module_as_main)
[Errno 2] No such file or directory: 'MSFT'
  File "D:\anaconda3\Lib\site-packages\backtrader\feed.py", line 674, in start
    self.f = io.open(self.p.dataname, 'r')
  File "D:\anaconda3\Lib\site-packages\backtrader\feeds\yahoo.py", line 94, in start
    super(YahooFinanceCSVData, self).start()
  File "D:\anaconda3\Lib\site-packages\backtrader\feeds\yahoo.py", line 355, in start
    super(YahooFinanceData, self).start()
  File "D:\anaconda3\Lib\site-packages\backtrader\feed.py", line 203, in _start
    self.start()
  File "D:\anaconda3\Lib\site-packages\backtrader\cerebro.py", line 1210, in runstrategies
    data._start()
  File "D:\anaconda3\Lib\site-packages\backtrader\cerebro.py", line 1127, in run
    runstrat = self.runstrategies(iterstrat)
  File "D:\code\digifinex\backTrader\1.py", line 37, in <module>
    cerebro.run()  # run it all
  File "D:\anaconda3\Lib\runpy.py", line 87, in _run_code
    exec(code, run_globals)
  File "D:\anaconda3\Lib\runpy.py", line 97, in _run_module_code
    _run_code(code, mod_globals, init_globals,
  File "D:\anaconda3\Lib\runpy.py", line 265, in run_path
    return _run_module_code(code, init_globals, run_name,
  File "D:\anaconda3\Lib\runpy.py", line 87, in _run_code
    exec(code, run_globals)
  File "D:\anaconda3\Lib\runpy.py", line 194, in _run_module_as_main (Current frame)
    return _run_code(code, main_globals, None,

btalib.macd(df.close,pfast=12,pslow=26,psignal=9)

TypeError Traceback (most recent call last)
~/anaconda3/lib/python3.7/site-packages/pandas/core/series.py in setitem(self, key, value)
1013 try:
-> 1014 self._set_with_engine(key, value)
1015 except com.SettingWithCopyError:

~/anaconda3/lib/python3.7/site-packages/pandas/core/series.py in _set_with_engine(self, key, value)
1053 try:
-> 1054 self.index._engine.set_value(values, key, value)
1055 return

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.set_value()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.set_value()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

TypeError: 'slice(11, None, None)' is an invalid key

During handling of the above exception, another exception occurred:

ValueError Traceback (most recent call last)
in
----> 1 btalib.macd(df.close,pfast=12,pslow=26,psignal=9)

~/anaconda3/lib/python3.7/site-packages/btalib/indicator.py in call(cls, *args, **kwargs)
150 # Auto-call base classes
151 for b_init in reversed(list(dict.fromkeys(b.init for b in bases))):
--> 152 b_init(self, *args, **kwargs)
153
154 # delete old aliases only meant for operational purposes

~/anaconda3/lib/python3.7/site-packages/btalib/indicators/macd.py in init(self)
38
39 def init(self):
---> 40 ma1 = self.p._ma(self.i0, period=self.p.pfast, **self._talibkw)
41 ma2 = self.p._ma(self.i0, period=self.p.pslow)
42 self.o.macd = ma1 - ma2

~/anaconda3/lib/python3.7/site-packages/btalib/indicator.py in call(cls, *args, **kwargs)
150 # Auto-call base classes
151 for b_init in reversed(list(dict.fromkeys(b.init for b in bases))):
--> 152 b_init(self, *args, **kwargs)
153
154 # delete old aliases only meant for operational purposes

~/anaconda3/lib/python3.7/site-packages/btalib/indicators/ema.py in init(self, poffset)
37 def init(self, poffset=0): # see above for poffset
38 span, seed, poff = self.p.period, self.p._seed, poffset
---> 39 self.o.ema = self.i0._ewm(span=span, _seed=seed, _poffset=poff).mean()

~/anaconda3/lib/python3.7/site-packages/btalib/meta/lines.py in call_op(*args, **kwargs)
377 sargs.append(arg)
378
--> 379 result[self._minidx:] = r = op(*sargs, **kwargs) # run/store
380 result = result.astype(r.dtype, copy=False)
381 return self._line._clone(result, period=self._minperiod)

~/anaconda3/lib/python3.7/site-packages/pandas/core/series.py in setitem(self, key, value)
1040 pass
1041
-> 1042 self._set_with(key, value)
1043
1044 if cacher_needs_updating:

~/anaconda3/lib/python3.7/site-packages/pandas/core/series.py in _set_with(self, key, value)
1062 if isinstance(key, slice):
1063 indexer = self.index._convert_slice_indexer(key, kind="getitem")
-> 1064 return self._set_values(indexer, value)
1065
1066 elif is_scalar(key) and not is_integer(key) and key not in self.index:

~/anaconda3/lib/python3.7/site-packages/pandas/core/series.py in _set_values(self, key, value)
1109 if isinstance(key, Series):
1110 key = key._values
-> 1111 self._data = self._data.setitem(indexer=key, value=value)
1112 self._maybe_update_cacher()
1113

~/anaconda3/lib/python3.7/site-packages/pandas/core/internals/managers.py in setitem(self, **kwargs)
559
560 def setitem(self, **kwargs):
--> 561 return self.apply("setitem", **kwargs)
562
563 def putmask(self, **kwargs):

~/anaconda3/lib/python3.7/site-packages/pandas/core/internals/managers.py in apply(self, f, filter, **kwargs)
440 applied = b.apply(f, **kwargs)
441 else:
--> 442 applied = getattr(b, f)(**kwargs)
443 result_blocks = _extend_blocks(applied, result_blocks)
444

~/anaconda3/lib/python3.7/site-packages/pandas/core/internals/blocks.py in setitem(self, indexer, value)
875
876 # length checking
--> 877 check_setitem_lengths(indexer, value, values)
878 exact_match = (
879 len(arr_value.shape)

~/anaconda3/lib/python3.7/site-packages/pandas/core/indexers.py in check_setitem_lengths(indexer, value, values)
122 if len(value) != length_of_indexer(indexer, values):
123 raise ValueError(
--> 124 "cannot set using a slice indexer with a "
125 "different length than the value"
126 )

ValueError: cannot set using a slice indexer with a different length than the value

https://www.metatrader5.com/en/terminal/help/indicators/bw_indicators/fractals

Can you add a Bill Williams fractals indicator to the library please?

https://btalib.backtrader.com/introduction/

Cannot be accessed anymore.