# -*- coding: utf-8 -*-
from typing import Sequence, Union
from pandas import Series, DataFrame
from . import cdl_doji, cdl_inside
from pandas_ta.utils import get_offset, verify_series
from pandas_ta import Imports
ALL_PATTERNS = [
"2crows", "3blackcrows", "3inside", "3linestrike", "3outside", "3starsinsouth",
"3whitesoldiers", "abandonedbaby", "advanceblock", "belthold", "breakaway",
"closingmarubozu", "concealbabyswall", "counterattack", "darkcloudcover", "doji",
"dojistar", "dragonflydoji", "engulfing", "eveningdojistar", "eveningstar",
"gapsidesidewhite", "gravestonedoji", "hammer", "hangingman", "harami",
"haramicross", "highwave", "hikkake", "hikkakemod", "homingpigeon",
"identical3crows", "inneck", "inside", "invertedhammer", "kicking", "kickingbylength",
"ladderbottom", "longleggeddoji", "longline", "marubozu", "matchinglow", "mathold",
"morningdojistar", "morningstar", "onneck", "piercing", "rickshawman",
"risefall3methods", "separatinglines", "shootingstar", "shortline", "spinningtop",
"stalledpattern", "sticksandwich", "takuri", "tasukigap", "thrusting", "tristar",
"unique3river", "upsidegap2crows", "xsidegap3methods"
]
[docs]def cdl_pattern(open_, high, low, close, name: Union[str, Sequence[str]]="all", scalar=None, offset=None, **kwargs) -> DataFrame:
"""Candle Pattern"""
# Validate Arguments
open_ = verify_series(open_)
high = verify_series(high)
low = verify_series(low)
close = verify_series(close)
offset = get_offset(offset)
scalar = float(scalar) if scalar else 100
# Patterns that implemented in pandas-ta
pta_patterns = {
"doji": cdl_doji, "inside": cdl_inside,
}
if name == "all":
name = ALL_PATTERNS
if type(name) is str:
name = [name]
if Imports["talib"]:
import talib.abstract as tala
result = {}
for n in name:
if n not in ALL_PATTERNS:
print(f"[X] There is no candle pattern named {n} available!")
continue
if n in pta_patterns:
pattern_result = pta_patterns[n](open_, high, low, close, offset=offset, scalar=scalar, **kwargs)
result[pattern_result.name] = pattern_result
else:
if not Imports["talib"]:
print(f"[X] Please install TA-Lib to use {n}. (pip install TA-Lib)")
continue
pattern_func = tala.Function(f"CDL{n.upper()}")
pattern_result = Series(pattern_func(open_, high, low, close, **kwargs) / 100 * scalar)
pattern_result.index = close.index
# Offset
if offset != 0:
pattern_result = pattern_result.shift(offset)
# Handle fills
if "fillna" in kwargs:
pattern_result.fillna(kwargs["fillna"], inplace=True)
if "fill_method" in kwargs:
pattern_result.fillna(method=kwargs["fill_method"], inplace=True)
result[f"CDL_{n.upper()}"] = pattern_result
if len(result) == 0: return
# Prepare DataFrame to return
df = DataFrame(result)
df.name = "CDL_PATTERN"
df.category = "candles"
return df
cdl_pattern.__doc__ = \
"""Candle Pattern
A wrapper around all candle patterns.
Examples:
Get all candle patterns (This is the default behaviour)
>>> df = df.ta.cdl_pattern(name="all")
Or
>>> df.ta.cdl("all", append=True) # = df.ta.cdl_pattern("all", append=True)
Get only one pattern
>>> df = df.ta.cdl_pattern(name="doji")
Or
>>> df.ta.cdl("doji", append=True)
Get some patterns
>>> df = df.ta.cdl_pattern(name=["doji", "inside"])
Or
>>> df.ta.cdl(["doji", "inside"], append=True)
Args:
open_ (pd.Series): Series of 'open's
high (pd.Series): Series of 'high's
low (pd.Series): Series of 'low's
close (pd.Series): Series of 'close's
name: (Union[str, Sequence[str]]): name of the patterns
scalar (float): How much to magnify. Default: 100
offset (int): How many periods to offset the result. Default: 0
Kwargs:
fillna (value, optional): pd.DataFrame.fillna(value)
fill_method (value, optional): Type of fill method
Returns:
pd.DataFrame: one column for each pattern.
"""
cdl = cdl_pattern