Merge branch 'pr/261' into development

README.md

@@ -554,11 +554,82 @@ help(ta.yf)
 <br/><br/>
 
 # **Indicators** (_by Category_)
-### **Candles** (3)
+### **Candles** (63)
 
-* _Doji_: **cdl_doji**
-* _Inside Bar_: **cdl_inside**
+* _Patterns_: cdl_pattern (Patterns that aren't bold, need TA-Lib to be installed: "```pip install TA-Lib```")
+    * 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
 * _Heikin-Ashi_: **ha**
+```python
+# Get all candle patterns (This is the default behaviour)
+df = df.ta.cdl_pattern(name="all")
+
+# Get only one pattern
+df = df.ta.cdl_pattern(name="doji")
+
+# Get some patterns
+df = df.ta.cdl_pattern(name=["doji", "inside"])
+```
 <br/>
 
 

pandas_ta/__init__.py

@@ -40,7 +40,7 @@ Imports = {
 Category = {
     # Candles
     "candles": [
-        "cdl_doji", "cdl_inside", "ha"
+        "cdl_pattern", "ha"
     ],
     # Cycles
     "cycles": ["ebsw"],

pandas_ta/candles/__init__.py

@@ -2,3 +2,4 @@
 from .ha import ha
 from .cdl_doji import cdl_doji
 from .cdl_inside import cdl_inside
+from .cdl_pattern import cdl_pattern, ALL_PATTERNS as CDL_PATTERN_NAMES

pandas_ta/candles/cdl_pattern.py

@@ -0,0 +1,107 @@
+# -*- 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
+if Imports["talib"]:
+    import talib.abstract as tala
+
+
+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"
+]
+
+
+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]
+
+    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("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["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.
+
+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.
+"""

pandas_ta/core.py

@@ -832,20 +832,12 @@ class AnalysisIndicators(BasePandasObject):
 
     # Public DataFrame Methods: Indicators and Utilities
     # Candles
-    def cdl_doji(self, offset=None, **kwargs):
+    def cdl_pattern(self, name="all", offset=None, **kwargs):
         open_ = self._get_column(kwargs.pop("open", "open"))
         high = self._get_column(kwargs.pop("high", "high"))
         low = self._get_column(kwargs.pop("low", "low"))
         close = self._get_column(kwargs.pop("close", "close"))
-        result = cdl_doji(open_=open_, high=high, low=low, close=close, offset=offset, **kwargs)
-        return self._post_process(result, **kwargs)
-
-    def cdl_inside(self, offset=None, **kwargs):
-        open_ = self._get_column(kwargs.pop("open", "open"))
-        high = self._get_column(kwargs.pop("high", "high"))
-        low = self._get_column(kwargs.pop("low", "low"))
-        close = self._get_column(kwargs.pop("close", "close"))
-        result = cdl_inside(open_=open_, high=high, low=low, close=close, offset=offset, **kwargs)
+        result = cdl_pattern(open_=open_, high=high, low=low, close=close, name=name, offset=offset, **kwargs)
         return self._post_process(result, **kwargs)
 
     def ha(self, offset=None, **kwargs):

tests/test_indicator_candle.py

@@ -39,6 +39,17 @@ class TestCandle(TestCase):
         self.assertIsInstance(result, DataFrame)
         self.assertEqual(result.name, "Heikin-Ashi")
 
+    def test_cdl_pattern(self):
+        result = pandas_ta.cdl_pattern(self.open, self.high, self.low, self.close, name="all")
+        self.assertIsInstance(result, DataFrame)
+        self.assertEqual(len(result.columns), len(pandas_ta.CDL_PATTERN_NAMES))
+
+        result = pandas_ta.cdl_pattern(self.open, self.high, self.low, self.close, name="doji")
+        self.assertIsInstance(result, DataFrame)
+
+        result = pandas_ta.cdl_pattern(self.open, self.high, self.low, self.close, name=["doji", "inside"])
+        self.assertIsInstance(result, DataFrame)
+
     def test_cdl_doji(self):
         result = pandas_ta.cdl_doji(self.open, self.high, self.low, self.close)
         self.assertIsInstance(result, Series)