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- [NEW]: Support for TA_SetUnstablePeriod and TA_GetUnstablePeriod
- [NEW]: Support for python 2.6 and earlier for ordereddict.
- [FIX]: Add lib64 paths to setup.py.
- [NEW]: Upgrade to Cython 0.22.
- [FIX]: Allow running setup.py without numpy or cython
- [NEW]: Allow TA_LIBRARY_PATH and TA_INCLUDE_PATH environment variables.
- [NEW]: Support pandas.Series and pandas.Dataframe inputs.
- [FIX]: Simple check to warn if ta-lib library is not installed
- [FIX]: Fix missing key error when inputs are not default names.
- [NEW]: Upgrade to Cython 0.20.
- [FIX]: Check all input array lengths are same.
- [FIX]: Check all input arrays for NaN elements.
- [NEW]: Upgrade to Cython 0.19.1.
- [FIX]: Fix "periods" input arrays in abstract interface.
- [FIX]: Only require necessary input arrays in abstract interface.
- [NEW]: Support for function_flags and output_flags properties in Functions
- [NEW]: Better test coverage of abstract interface.
- [NEW]: Support for Python 3.
- [FIX]: Make installation on Windows easier.
- [NEW]: Upgrade to Cython 0.18.
- [FIX]: Improve docstrings for indicators in talib.func.
- [FIX]: Initialize and shutdown underlying TA-Lib only once each process.
This should give slight speedups when using many indicators (<5%).
- [DEPRECATED]: The old moving average types that were in talib.func are now
deprecated. See the next bullet item for the replacement, or you can
continue using them with "from talib import deprecated" for the time being.
- [NEW]: The new moving average types are in talib.MA_Type. It's a class with SMA,
EMA, DEMA, etc attribute variables you should now use. Human-readable lookups
are also possible by using MA_Type as a dict e.g.:
MA_Type[MA_Type.SMA] # returns "Simple Moving Average"
- [NEW]: In addition to the existing func interface, we now provide an
enhanced abstract interface too. Functions in "import talib" use the
original interface, or you can use "from talib import abstract" for
the full abstract interface. See the README, tools/example.py and
tests/abstract_test.py for more information. The full (commented)
source code is mostly located in talib/abstract.pyx. The basic usage is very
input_arrays = { '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) }
ema_20 = abstract.Function('ema', input_arrays, 20).outputs # function names not case-sensitive
slowd, slowk = abstract.Function('STOCH')(input_arrays, 15, 3, 0, 3, 0)
upper, middle, lower = abstract.Function('bbands')(input_arrays, timeperiod=20)
- Move the functions into ``talib.func``, to prepare for ``talib.abstract``
in a future release.
- Support for MacPorts.
- Fix for FreeBSD.
First version.