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Python wrapper for TA-Lib (http://ta-lib.org/).

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TA-Lib/ta-lib-python

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This is a Python wrapper forTA-LIB based on Cythoninstead of SWIG. From the homepage:

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

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

The original Python bindings included with TA-Lib useSWIG which unfortunately are difficult to install andaren't as efficient as they could be. Therefore this project usesCython andNumpy to efficientlyand cleanly bind to TA-Lib -- producing results 2-4 times faster than theSWIG interface.

In addition, this project also supports the use of thePolars andPandaslibraries.

Versions

The upstream TA-Lib C library released version 0.6.1 and changed the libraryname to-lta-lib from-lta_lib. After trying to support both viaautodetect and having some issues, we have decided to currently support threefeature branches:

  • ta-lib-python 0.4.x (supportsta-lib 0.4.x andnumpy 1)
  • ta-lib-python 0.5.x (supportsta-lib 0.4.x andnumpy 2)
  • ta-lib-python 0.6.x (supportsta-lib 0.6.x andnumpy 2)

Installation

You can install from PyPI:

$ python -m pip install TA-Lib

Or checkout the sources and runsetup.py yourself:

$ python setup.py install

It also appears possible to install viaConda Forge:

$ conda install -c conda-forge ta-lib

Dependencies

To use TA-Lib for python, you need to have theTA-Libalready installed. You should probably follow theirinstallationdirections for your platform, but somesuggestions are included below for reference.

Some Conda Forge users have reported success installing the underlying TA-Lib Clibrary usingthe libta-lib package:

$ conda install -c conda-forge libta-lib

Mac OS X

You can simply install using Homebrew:

$ brew install ta-lib

If you are using Apple Silicon, such as the M1 processors, and building mixedarchitecture Homebrew projects, you might want to make sure it's being builtfor your architecture:

$ arch -arm64 brew install ta-lib

And perhaps you can set these before installing withpip:

$ export TA_INCLUDE_PATH="$(brew --prefix ta-lib)/include"$ export TA_LIBRARY_PATH="$(brew --prefix ta-lib)/lib"

You might also find this helpful, particularly if you have tried severaldifferent installations without success:

$ your-arm64-python -m pip install --no-cache-dir ta-lib
Windows

For 64-bit Windows, the easiest way is to get theexecutable installer:

  1. Downloadta-lib-0.6.4-windows-x86_64.msi.
  2. Run the Installer or runmsiexecfrom the command-line.

Alternatively, if you prefer to get the libraries without installing, orwould like to use the 32-bit version:

Linux

Downloadta-lib-0.6.4-src.tar.gzand:

$ tar -xzf ta-lib-0.6.4-src.tar.gz$ cd ta-lib-0.6.4/$ ./configure --prefix=/usr$ make$ sudo make install

If you buildTA-Lib usingmake -jX it will fail but that's OK!Simply rerunmake -jX followed by[sudo] make install.

Note: if your directory path includes spaces, the installation will probablyfail withNo such file or directory errors.

Troubleshooting

If you get a warning that looks like this:

setup.py:79: UserWarning: Cannot find ta-lib library, installation may fail.warnings.warn('Cannot find ta-lib library, installation may fail.')

This typically meanssetup.py can't find the underlyingTA-Liblibrary, a dependency which needs to be installed.

If you installed the underlyingTA-Lib library with a custom prefix(e.g., with./configure --prefix=$PREFIX), then when you go to installthis python wrapper you can specify additional search paths to find thelibrary and include files for the underlyingTA-Lib library using theTA_LIBRARY_PATH andTA_INCLUDE_PATH environment variables:

$export TA_LIBRARY_PATH=$PREFIX/lib$export TA_INCLUDE_PATH=$PREFIX/include$ python setup.py install# or pip install ta-lib

Sometimes installation will produce build errors like this:

talib/_ta_lib.c:601:10: fatal error: ta-lib/ta_defs.h: No such file or directory  601 | #include "ta-lib/ta_defs.h"      |          ^~~~~~~~~~~~~~~~~~compilation terminated.

or:

common.obj : error LNK2001: unresolved external symbol TA_SetUnstablePeriodcommon.obj : error LNK2001: unresolved external symbol TA_Shutdowncommon.obj : error LNK2001: unresolved external symbol TA_Initializecommon.obj : error LNK2001: unresolved external symbol TA_GetUnstablePeriodcommon.obj : error LNK2001: unresolved external symbol TA_GetVersionString

This typically means that it can't find the underlyingTA-Lib library, adependency which needs to be installed. On Windows, this could be caused byinstalling the 32-bit binary distribution of the underlyingTA-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 runsomething like:

$ sudo apt-get install python3-dev

Sometimes building the underlyingTA-Lib library has errors runningmake that look like this:

../libtool: line 1717: cd: .libs/libta_lib.lax/libta_abstract.a: No such file or directorymake[2]: *** [libta_lib.la] Error 1make[1]: *** [all-recursive] Error 1make: *** [all-recursive] Error 1

This might mean that the directory path to the underlyingTA-Lib libraryhas spaces in the directory names. Try putting it in a path that does not haveany spaces and trying again.

Sometimes you might get this error runningsetup.py:

/usr/include/limits.h:26:10: fatal error: bits/libc-header-start.h: No such file or directory#include <bits/libc-header-start.h>         ^~~~~~~~~~~~~~~~~~~~~~~~~~

This is likely an issue with trying to compile for 32-bit platform butwithout the appropriate headers. You might find some success looking at thefirst answer tothis question.

If you get an error on macOS like this:

code signature in <141BC883-189B-322C-AE90-CBF6B5206F67>'python3.9/site-packages/talib/_ta_lib.cpython-39-darwin.so' not valid foruse in process: Trying to load an unsigned library)

You might look atthis questionand usexcrun codesign to fix it.

If you wonder whySTOCHRSI gives you different results than you expect,probably you wantSTOCH applied toRSI, which is a little differentthan theSTOCHRSI which isSTOCHF applied toRSI:

>>>importtalib>>>importnumpyasnp>>>c=np.random.randn(100)# this is the library function>>>k,d=talib.STOCHRSI(c)# this produces the same result, calling STOCHF>>>rsi=talib.RSI(c)>>>k,d=talib.STOCHF(rsi,rsi,rsi)# you might want this instead, calling STOCH>>>rsi=talib.RSI(c)>>>k,d=talib.STOCH(rsi,rsi,rsi)

If the build appears to hang, you might be running on a VM with not enoughmemory -- try 1 GB or 2 GB.

It has also been reported that using a swapfile could help, for example:

$ sudo fallocate -l 1G /swapfile$ sudo chmod 600 /swapfile$ sudo mkswap /swapfile$ sudo swapon /swapfile

If you get "permission denied" errors such as this, you might need to giveyour user access to the location where the underlying TA-Lib C library isinstalled -- or install it to a user-accessible location.

talib/_ta_lib.c:747:28: fatal error: /usr/include/ta-lib/ta_defs.h: Permission denied #include "ta-lib/ta-defs.h"                            ^compilation terminatederror: command 'gcc' failed with exit status 1

If you're having trouble compiling the underlying TA-Lib C library on ARM64,you might need to configure it with an explicit build type before runningmake andmake install, for example:

$ ./configure --build=aarch64-unknown-linux-gnu

This is caused by oldconfig.guess file, so another way to solve this isto copy a newer version of config.guess into the underlying TA-Lib C librarysources:

$ cp /usr/share/automake-1.16/config.guess /path/to/extracted/ta-lib/config.guess

And then re-run configure:

$ ./configure

If you're having trouble usingPyInstaller andget an error that looks like this:

...site-packages\PyInstaller\loader\pyimod03_importers.py", line 493, in exec_module    exec(bytecode, module.__dict__)  File "talib\__init__.py", line 72, in <module>ModuleNotFoundError: No module named 'talib.stream'

Then, perhaps you can use the--hidden-import argument to fix this:

$ pyinstaller --hidden-import talib.stream "replaceToYourFileName.py"

If you want to usenumpy<2, then you should useta-lib<0.5.

If you want to usenumpy>=2, then you should useta-lib>=0.5.

If you have trouble getting the code autocompletions to work in VisualStudio Code, a suggestion was made to look for thePython extensionsettings, and an option forLanguage Server, and change it fromDefault (which meansPylance if it is installed, Jedi otherwise, tomanually setJedi and the completions should work. It is possible thatyou might need toinstall itmanually for this towork.

Function API

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

Each function returns an output array and have default values for theirparameters, unless specified as keyword arguments. Typically, these functionswill have an initial "lookback" period (a required number of observationsbefore an output is generated) set toNaN.

For convenience, the Function API supports bothnumpy.ndarray andpandas.Series andpolars.Series inputs.

All of the following examples use the Function API:

importnumpyasnpimporttalibclose=np.random.random(100)

Calculate a simple moving average of the close prices:

output=talib.SMA(close)

Calculating bollinger bands, with triple exponential moving average:

fromtalibimportMA_Typeupper,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)
NaN's

The underlying TA-Lib C library handles NaN's in a sometimes surprising mannerby typically propagating NaN's to the end of the output, for example:

>>>c=np.array([1.0,2.0,3.0,np.nan,4.0,5.0,6.0])>>>talib.SMA(c,3)array([nan,nan,2.,nan,nan,nan,nan])

You can compare that to a Pandas rolling mean, where their approach is tooutput NaN until enough "lookback" values are observed to generate new outputs:

>>>c=pandas.Series([1.0,2.0,3.0,np.nan,4.0,5.0,6.0])>>>c.rolling(3).mean()0NaN1NaN22.03NaN4NaN5NaN65.0dtype:float64

Abstract API

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

Every function takes a collection of named inputs, either adict ofnumpy.ndarray orpandas.Series orpolars.Series, or apandas.DataFrame orpolars.DataFrame. If apandas.DataFrame orpolars.DataFrame is provided, the output is returned as the same typewith named output columns.

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

importnumpyasnp# 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:

fromtalibimportabstract# directlySMA=abstract.SMA# or by nameSMA=abstract.Function('sma')

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

fromtalib.abstractimport*# uses close prices (default)output=SMA(inputs,timeperiod=25)# uses open pricesoutput=SMA(inputs,timeperiod=25,price='open')# uses close prices (default)upper,middle,lower=BBANDS(inputs,20,2.0,2.0)# uses high, low, close (default)slowk,slowd=STOCH(inputs,5,3,0,3,0)# uses high, low, close by default# uses high, low, open insteadslowk,slowd=STOCH(inputs,5,3,0,3,0,prices=['high','low','open'])

Streaming API

An experimental Streaming API was added that allows users to compute the latestvalue of an indicator. This can be faster than using the Function API, forexample in an application that receives streaming data, and wants to know justthe most recent updated indicator value.

importtalibfromtalibimportstreamclose=np.random.random(100)# the Function APIoutput=talib.SMA(close)# the Streaming APIlatest=stream.SMA(close)# the latest value is the same as the last output valueassert (output[-1]-latest)<0.00001

Supported Indicators and Functions

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

importtalib# list of functionsfornameintalib.get_functions():print(name)# dict of functions by groupforgroup,namesintalib.get_function_groups().items():print(group)fornameinnames:print(f"{name}")

Indicator Groups

  • Overlap Studies
  • Momentum Indicators
  • Volume Indicators
  • Volatility Indicators
  • Price Transform
  • Cycle Indicators
  • Pattern Recognition
Overlap Studies
BBANDS               Bollinger BandsDEMA                 Double Exponential Moving AverageEMA                  Exponential Moving AverageHT_TRENDLINE         Hilbert Transform - Instantaneous TrendlineKAMA                 Kaufman Adaptive Moving AverageMA                   Moving averageMAMA                 MESA Adaptive Moving AverageMAVP                 Moving average with variable periodMIDPOINT             MidPoint over periodMIDPRICE             Midpoint Price over periodSAR                  Parabolic SARSAREXT               Parabolic SAR - ExtendedSMA                  Simple Moving AverageT3                   Triple Exponential Moving Average (T3)TEMA                 Triple Exponential Moving AverageTRIMA                Triangular Moving AverageWMA                  Weighted Moving Average
Momentum Indicators
ADX                  Average Directional Movement IndexADXR                 Average Directional Movement Index RatingAPO                  Absolute Price OscillatorAROON                AroonAROONOSC             Aroon OscillatorBOP                  Balance Of PowerCCI                  Commodity Channel IndexCMO                  Chande Momentum OscillatorDX                   Directional Movement IndexMACD                 Moving Average Convergence/DivergenceMACDEXT              MACD with controllable MA typeMACDFIX              Moving Average Convergence/Divergence Fix 12/26MFI                  Money Flow IndexMINUS_DI             Minus Directional IndicatorMINUS_DM             Minus Directional MovementMOM                  MomentumPLUS_DI              Plus Directional IndicatorPLUS_DM              Plus Directional MovementPPO                  Percentage Price OscillatorROC                  Rate of change : ((price/prevPrice)-1)*100ROCP                 Rate of change Percentage: (price-prevPrice)/prevPriceROCR                 Rate of change ratio: (price/prevPrice)ROCR100              Rate of change ratio 100 scale: (price/prevPrice)*100RSI                  Relative Strength IndexSTOCH                StochasticSTOCHF               Stochastic FastSTOCHRSI             Stochastic Relative Strength IndexTRIX                 1-day Rate-Of-Change (ROC) of a Triple Smooth EMAULTOSC               Ultimate OscillatorWILLR                Williams' %R
Volume Indicators
AD                   Chaikin A/D LineADOSC                Chaikin A/D OscillatorOBV                  On Balance Volume
Cycle Indicators
HT_DCPERIOD          Hilbert Transform - Dominant Cycle PeriodHT_DCPHASE           Hilbert Transform - Dominant Cycle PhaseHT_PHASOR            Hilbert Transform - Phasor ComponentsHT_SINE              Hilbert Transform - SineWaveHT_TRENDMODE         Hilbert Transform - Trend vs Cycle Mode
Price Transform
AVGPRICE             Average PriceMEDPRICE             Median PriceTYPPRICE             Typical PriceWCLPRICE             Weighted Close Price
Volatility Indicators
ATR                  Average True RangeNATR                 Normalized Average True RangeTRANGE               True Range
Pattern Recognition
CDL2CROWS            Two CrowsCDL3BLACKCROWS       Three Black CrowsCDL3INSIDE           Three Inside Up/DownCDL3LINESTRIKE       Three-Line StrikeCDL3OUTSIDE          Three Outside Up/DownCDL3STARSINSOUTH     Three Stars In The SouthCDL3WHITESOLDIERS    Three Advancing White SoldiersCDLABANDONEDBABY     Abandoned BabyCDLADVANCEBLOCK      Advance BlockCDLBELTHOLD          Belt-holdCDLBREAKAWAY         BreakawayCDLCLOSINGMARUBOZU   Closing MarubozuCDLCONCEALBABYSWALL  Concealing Baby SwallowCDLCOUNTERATTACK     CounterattackCDLDARKCLOUDCOVER    Dark Cloud CoverCDLDOJI              DojiCDLDOJISTAR          Doji StarCDLDRAGONFLYDOJI     Dragonfly DojiCDLENGULFING         Engulfing PatternCDLEVENINGDOJISTAR   Evening Doji StarCDLEVENINGSTAR       Evening StarCDLGAPSIDESIDEWHITE  Up/Down-gap side-by-side white linesCDLGRAVESTONEDOJI    Gravestone DojiCDLHAMMER            HammerCDLHANGINGMAN        Hanging ManCDLHARAMI            Harami PatternCDLHARAMICROSS       Harami Cross PatternCDLHIGHWAVE          High-Wave CandleCDLHIKKAKE           Hikkake PatternCDLHIKKAKEMOD        Modified Hikkake PatternCDLHOMINGPIGEON      Homing PigeonCDLIDENTICAL3CROWS   Identical Three CrowsCDLINNECK            In-Neck PatternCDLINVERTEDHAMMER    Inverted HammerCDLKICKING           KickingCDLKICKINGBYLENGTH   Kicking - bull/bear determined by the longer marubozuCDLLADDERBOTTOM      Ladder BottomCDLLONGLEGGEDDOJI    Long Legged DojiCDLLONGLINE          Long Line CandleCDLMARUBOZU          MarubozuCDLMATCHINGLOW       Matching LowCDLMATHOLD           Mat HoldCDLMORNINGDOJISTAR   Morning Doji StarCDLMORNINGSTAR       Morning StarCDLONNECK            On-Neck PatternCDLPIERCING          Piercing PatternCDLRICKSHAWMAN       Rickshaw ManCDLRISEFALL3METHODS  Rising/Falling Three MethodsCDLSEPARATINGLINES   Separating LinesCDLSHOOTINGSTAR      Shooting StarCDLSHORTLINE         Short Line CandleCDLSPINNINGTOP       Spinning TopCDLSTALLEDPATTERN    Stalled PatternCDLSTICKSANDWICH     Stick SandwichCDLTAKURI            Takuri (Dragonfly Doji with very long lower shadow)CDLTASUKIGAP         Tasuki GapCDLTHRUSTING         Thrusting PatternCDLTRISTAR           Tristar PatternCDLUNIQUE3RIVER      Unique 3 RiverCDLUPSIDEGAP2CROWS   Upside Gap Two CrowsCDLXSIDEGAP3METHODS  Upside/Downside Gap Three Methods
Statistic Functions
BETA                 BetaCORREL               Pearson's Correlation Coefficient (r)LINEARREG            Linear RegressionLINEARREG_ANGLE      Linear Regression AngleLINEARREG_INTERCEPT  Linear Regression InterceptLINEARREG_SLOPE      Linear Regression SlopeSTDDEV               Standard DeviationTSF                  Time Series ForecastVAR                  Variance
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