This is a python library and supporting files for calculating various technical indicators used in trading markets. It builds on code from my stocklib module also in github. You feed an indicator a time series of data 1 bar at a time and it continuously updates it's value. I use this personally, but it will likely require some effort for other people to put it to use.

Take a look at stocklib first and get that to work before making use of this code.

indicators uses depends on my stocklib code and it's dependencies.

The indicators code is split between Checks and Metrics.

A Check takes a stream of bar data and indicates a simple True/False value. For example, you might write a custom Check to indicate if the last close price was above a moving average or if average volume was above 500,000 shares. All Checks should inherit from the Check class. Here is a simple example using a check:

check = MyTrendCheck()
for periodData in generate_random_series():
    check.handle(periodData)

    if check.ready():
        if check.check():
            print "%s passed" % (periodData.date,)

A Metric takes a stream of bar data and calculates a numeric float value. This is where concepts like MACD, Stochastics, Bollinger Bands and Moving Averages live.

close = AdjustedClose()
sma = SimpleMovingAverage(metric=close, period=20)

print "Date,SMA"

for periodData in generate_random_series():
    close.handle(periodData)
    sma.handle(periodData)

    if sma.ready() and close.ready():
        print "%s,%f" % (periodData.date, sma.value())