Python3 TA-Lib

This is a Python wrapper for TA-LIB based on Cython instead of SWIG. From the homepage:

TA-Lib is widely used by trading software developers requiring to perform technical analysis of financial market data.

• Includes 150+ indicators such as ADX, MACD, RSI, Stochastic, Bollinger Bands, etc.
• Candlestick pattern recognition
• Open-source API for C/C++, Java, Perl, Python and 100% Managed .NET

The original Python bindings use SWIG which unfortunately are difficult to install and aren't as efficient as they could be. Therefore this project uses Cython and Numpy to efficiently and cleanly bind to TA-Lib -- producing results 2-4 times faster than the SWIG interface.

Installation

You can install from PyPI:

$ pip install TA-Lib

Or checkout the sources and run setup.py yourself:

$ python setup.py install

Troubleshooting

Sometimes installation will produce build errors like this:

func.c:256:28: fatal error: ta-lib/ta_libc.h: No such file or directory
compilation terminated.

or:

common.obj : error LNK2001: unresolved external symbol TA_SetUnstablePeriod
common.obj : error LNK2001: unresolved external symbol TA_Shutdown
common.obj : error LNK2001: unresolved external symbol TA_Initialize
common.obj : error LNK2001: unresolved external symbol TA_GetUnstablePeriod
common.obj : error LNK2001: unresolved external symbol TA_GetVersionString

This typically means that it can't find the underlying TA-Lib library, a dependency which needs to be installed. On Windows, this could be caused by installing the 32-bit binary distribution of the underlying TA-Lib library, but trying to use it with 64-bit Python.

Sometimes installation will fail with errors like this:

talib/common.c:8:22: fatal error: pyconfig.h: No such file or directory
 #include "pyconfig.h"
                      ^
compilation terminated.
error: command 'x86_64-linux-gnu-gcc' failed with exit status 1

This typically means that you need the Python headers, and should run something like:

$ sudo apt-get install python3-dev

Dependencies

To use TA-Lib for python, you need to have the TA-Lib already installed:

Mac OS X

$ brew install ta-lib

Windows

Download ta-lib-0.4.0-msvc.zip and unzip to C:\ta-lib

This is a 32-bit release. If you want to use 64-bit Python, you will need to build a 64-bit version of the library.

Linux

Download ta-lib-0.4.0-src.tar.gz and:

$ untar and cd
$ ./configure --prefix=/usr
$ make
$ sudo make install

If you build TA-Lib using make -jX it will fail but that's OK! Simply rerun make -jX followed by [sudo] make install.

Function API

Similar to TA-Lib, the Function API provides a lightweight wrapper of the exposed TA-Lib indicators.

Each function returns an output array and have default values for their parameters, unless specified as keyword arguments. Typically, these functions will have an initial "lookback" period (a required number of observations before an output is generated) set to NaN.

For convenience, the Function API supports both numpy.ndarray and pandas.Series types.

All of the following examples use the Function API:

import numpy
import talib

close = numpy.random.random(100)

Calculate a simple moving average of the close prices:

output = talib.SMA(close)

Calculating bollinger bands, with triple exponential moving average:

from talib import MA_Type

upper, middle, lower = talib.BBANDS(close, matype=MA_Type.T3)

Calculating momentum of the close prices, with a time period of 5:

output = talib.MOM(close, timeperiod=5)

Abstract API

If you're already familiar with using the function API, you should feel right at home using the Abstract API.

Every function takes a collection of named inputs, either a dict of numpy.ndarray or pandas.Series, or a pandas.DataFrame. If a pandas.DataFrame is provided, the output is returned as a pandas.DataFrame with named output columns.

For example, inputs could be provided for the typical "OHLCV" data:

import numpy as np

# note that all ndarrays must be the same length!
inputs = {
    'open': np.random.random(100),
    'high': np.random.random(100),
    'low': np.random.random(100),
    'close': np.random.random(100),
    'volume': np.random.random(100)
}

Functions can either be imported directly or instantiated by name:

from talib import abstract

# directly
sma = abstract.SMA

# or by name
sma = abstract.Function('sma')

From there, calling functions is basically the same as the function API:

from talib.abstract import *

# uses close prices (default)
output = SMA(inputs, timeperiod=25)

# uses open prices
output = SMA(inputs, timeperiod=25, price='open')

# uses close prices (default)
upper, middle, lower = BBANDS(inputs, 20, 2, 2)

# uses high, low, close (default)
slowk, slowd = STOCH(inputs, 5, 3, 0, 3, 0) # uses high, low, close by default

# uses high, low, open instead
slowk, slowd = STOCH(inputs, 5, 3, 0, 3, 0, prices=['high', 'low', 'open'])

Supported Indicators and Functions

We can show all the TA functions supported by TA-Lib, either as a list or as a dict sorted by group (e.g. "Overlap Studies", "Momentum Indicators", etc):

import talib

# list of functions
print talib.get_functions()

# dict of functions by group
print talib.get_function_groups()

Indicator Groups

• Overlap Studies
• Momentum Indicators
• Volume Indicators
• Volatility Indicators
• Price Transform
• Cycle Indicators
• Pattern Recognition

Overlap Studies

BBANDS               Bollinger Bands
DEMA                 Double Exponential Moving Average
EMA                  Exponential Moving Average
HT_TRENDLINE         Hilbert Transform - Instantaneous Trendline
KAMA                 Kaufman Adaptive Moving Average
MA                   Moving average
MAMA                 MESA Adaptive Moving Average
MAVP                 Moving average with variable period
MIDPOINT             MidPoint over period
MIDPRICE             Midpoint Price over period
SAR                  Parabolic SAR
SAREXT               Parabolic SAR - Extended
SMA                  Simple Moving Average
T3                   Triple Exponential Moving Average (T3)
TEMA                 Triple Exponential Moving Average
TRIMA                Triangular Moving Average
WMA                  Weighted Moving Average

Momentum Indicators

ADX                  Average Directional Movement Index
ADXR                 Average Directional Movement Index Rating
APO                  Absolute Price Oscillator
AROON                Aroon
AROONOSC             Aroon Oscillator
BOP                  Balance Of Power
CCI                  Commodity Channel Index
CMO                  Chande Momentum Oscillator
DX                   Directional Movement Index
MACD                 Moving Average Convergence/Divergence
MACDEXT              MACD with controllable MA type
MACDFIX              Moving Average Convergence/Divergence Fix 12/26
MFI                  Money Flow Index
MINUS_DI             Minus Directional Indicator
MINUS_DM             Minus Directional Movement
MOM                  Momentum
PLUS_DI              Plus Directional Indicator
PLUS_DM              Plus Directional Movement
PPO                  Percentage Price Oscillator
ROC                  Rate of change : ((price/prevPrice)-1)*100
ROCP                 Rate of change Percentage: (price-prevPrice)/prevPrice
ROCR                 Rate of change ratio: (price/prevPrice)
ROCR100              Rate of change ratio 100 scale: (price/prevPrice)*100
RSI                  Relative Strength Index
STOCH                Stochastic
STOCHF               Stochastic Fast
STOCHRSI             Stochastic Relative Strength Index
TRIX                 1-day Rate-Of-Change (ROC) of a Triple Smooth EMA
ULTOSC               Ultimate Oscillator
WILLR                Williams' %R

Volume Indicators

AD                   Chaikin A/D Line
ADOSC                Chaikin A/D Oscillator
OBV                  On Balance Volume

Cycle Indicators

HT_DCPERIOD          Hilbert Transform - Dominant Cycle Period
HT_DCPHASE           Hilbert Transform - Dominant Cycle Phase
HT_PHASOR            Hilbert Transform - Phasor Components
HT_SINE              Hilbert Transform - SineWave
HT_TRENDMODE         Hilbert Transform - Trend vs Cycle Mode

Price Transform

AVGPRICE             Average Price
MEDPRICE             Median Price
TYPPRICE             Typical Price
WCLPRICE             Weighted Close Price

Volatility Indicators

ATR                  Average True Range
NATR                 Normalized Average True Range
TRANGE               True Range

Pattern Recognition

CDL2CROWS            Two Crows
CDL3BLACKCROWS       Three Black Crows
CDL3INSIDE           Three Inside Up/Down
CDL3LINESTRIKE       Three-Line Strike
CDL3OUTSIDE          Three Outside Up/Down
CDL3STARSINSOUTH     Three Stars In The South
CDL3WHITESOLDIERS    Three Advancing White Soldiers
CDLABANDONEDBABY     Abandoned Baby
CDLADVANCEBLOCK      Advance Block
CDLBELTHOLD          Belt-hold
CDLBREAKAWAY         Breakaway
CDLCLOSINGMARUBOZU   Closing Marubozu
CDLCONCEALBABYSWALL  Concealing Baby Swallow
CDLCOUNTERATTACK     Counterattack
CDLDARKCLOUDCOVER    Dark Cloud Cover
CDLDOJI              Doji
CDLDOJISTAR          Doji Star
CDLDRAGONFLYDOJI     Dragonfly Doji
CDLENGULFING         Engulfing Pattern
CDLEVENINGDOJISTAR   Evening Doji Star
CDLEVENINGSTAR       Evening Star
CDLGAPSIDESIDEWHITE  Up/Down-gap side-by-side white lines
CDLGRAVESTONEDOJI    Gravestone Doji
CDLHAMMER            Hammer
CDLHANGINGMAN        Hanging Man
CDLHARAMI            Harami Pattern
CDLHARAMICROSS       Harami Cross Pattern
CDLHIGHWAVE          High-Wave Candle
CDLHIKKAKE           Hikkake Pattern
CDLHIKKAKEMOD        Modified Hikkake Pattern
CDLHOMINGPIGEON      Homing Pigeon
CDLIDENTICAL3CROWS   Identical Three Crows
CDLINNECK            In-Neck Pattern
CDLINVERTEDHAMMER    Inverted Hammer
CDLKICKING           Kicking
CDLKICKINGBYLENGTH   Kicking - bull/bear determined by the longer marubozu
CDLLADDERBOTTOM      Ladder Bottom
CDLLONGLEGGEDDOJI    Long Legged Doji
CDLLONGLINE          Long Line Candle
CDLMARUBOZU          Marubozu
CDLMATCHINGLOW       Matching Low
CDLMATHOLD           Mat Hold
CDLMORNINGDOJISTAR   Morning Doji Star
CDLMORNINGSTAR       Morning Star
CDLONNECK            On-Neck Pattern
CDLPIERCING          Piercing Pattern
CDLRICKSHAWMAN       Rickshaw Man
CDLRISEFALL3METHODS  Rising/Falling Three Methods
CDLSEPARATINGLINES   Separating Lines
CDLSHOOTINGSTAR      Shooting Star
CDLSHORTLINE         Short Line Candle
CDLSPINNINGTOP       Spinning Top
CDLSTALLEDPATTERN    Stalled Pattern
CDLSTICKSANDWICH     Stick Sandwich
CDLTAKURI            Takuri (Dragonfly Doji with very long lower shadow)
CDLTASUKIGAP         Tasuki Gap
CDLTHRUSTING         Thrusting Pattern
CDLTRISTAR           Tristar Pattern
CDLUNIQUE3RIVER      Unique 3 River
CDLUPSIDEGAP2CROWS   Upside Gap Two Crows
CDLXSIDEGAP3METHODS  Upside/Downside Gap Three Methods

安装方法：

1. 确定自己的系统为64位版本

2. 下载安装Python3 64位版本

主页地址： https://www.python.org/downloads/release/python-362/

下载地址： https://www.python.org/ftp/python/3.6.2/python-3.6.2-amd64.exe

安装过程，略。

安装成功

3. 下载安装numpy

主页地址： https://pypi.python.org/pypi/numpy

安装方法：可以直接使用命令pip install numpy进行安装

或者下载后安装

下载地址：https://pypi.python.org/packages/0d/8a/2de59f0154fe9cab6e12c404482714b8b8e8f9b0b561138f1eaf03b8d61f/numpy-1.13.1-cp36-none-win_amd64.whl

然后使用如下命令进行安装：

4. 下载安装TA-Lib

主页地址：http://ta-lib.org/

加利福尼亚大学欧文分校 荧光动力学实验室 的 克里斯托夫·戈尔克( Christoph Gohlke)提供了一个非官方的Python扩展库，地址为 http://www.lfd.uci.edu/~gohlke/pythonlibs

下载地址：http://www.lfd.uci.edu/~gohlke/pythonlibs/hkfw9m5o/TA_Lib-0.4.10-cp36-cp36m-win_amd64.whl

安装方法：

5. 安装PyMySQL

Python3下推荐使用PyMySQL，直接使用命令 pip install PyMySQL

安装方法：