When zipline is imported it checks whether
it runs in the IPython notebook. If it does,
it registers a %%zipline magic that takes the
same arguments as the CLI with the addition of
a -o for specifying the output variable to store
the performance frame in.
The algo code in the cell is, as of yet, executed
in its own environment rather than that of the
IPython NB which is probably what we want.
Also adds cli option to save the perf dataframe
to a pickle file.
Also adds an IPython notebook buyapple example.
Add a CLI that reads in an algorithm, loads data,
run the algorithm, and output performance metrics.
The examples are adapted to the new zipline API and
analyses are split into separate files.
Also add config files that run the example
algorithms with preset settings.
This is a step towards the goal of uniting Quantopian scripts
and zipline.
To make the syntax of zipline identical to Quantopian
we break out the API methods (like order) and turn them into
functions. To access the algo object we add a thread local reference
to the current algorithm that is accessed in the API functions.
TradingAlgorithm now takes either a string or two functions
(initialize and handle_data) that it executes.
Use api method decorator for methods available in algoscript.
Ported appropriate algorithm tests from internal code.
Stewart Douglas