This commit modifies the DataFrameSource and DataPanelSource to accept only Int64Indexes on the incoming data and moves the burden of mapping user identifiers to TradingAlgorithm.run().
The identifier cache's usage was nearly identical to using lookup_generic, so this commit removes identifier-keyed caching and modifies anything that uses it.
Instead of using the pandas.Series datetime index for every single
vector, get the index at the beginning of the update loop based on the
dt and then use that index to set the values.
Also, since the dt lookup is no longer needed, store the values as numpy
arrays, which are more lightweight.
Locally, this patch cuts out about 60% of the time spent in the update
method.
- AssetFinder no longer accepts an unused trading_calendar.
- AssetFinder correctly accepts a DataFrame as input.
- Tests for AssetFinder no longer rely on a global trading environment.
Test sources are now defined by the sim_params period_start and period_end, rather than by the period_start and a defined 'count' of bars. This allows us to consider the sim_params.period_end as the canonical definition of the end of a simulation.
By having both the trade simulation main loop route events to "process"
methods based on event type and the process methods also checking event
type, there was some duplicated effort in doing that comparison many
times.
A particular case where this was noted in profiling was for the
`process_event` function which was checking if the type was not a trade
and returning early, when in a larger universe of stocks the value
returned False 99% of the time.
Instead provide separate process functions specific to each type,
e.g. e.g. `process_trade` and `process_transaction` and route traffic to
those functions in tradesimulation.
For a universe of 160 stocks on both no-op algo and an algo that rebuys
its universe every day, saw about a 10% increase locally.
Also:
- Add process_benchmark to blotter since internal subclass relies on
logic on benchmark, this allows the internal process_trade to be a
`pass`.
- Add warning on unrecoginzed event types.
Rather than drop files temporarily into the master security lists
directory during unit tests, create temporary directories for the
tests. This avoids issues when the tests are being run at the same
time as other code that uses the real security lists data.
Only fill limit order if impacted fill price is better than the limit price.
If a limit order is partially filled, only fill the remaining shares if the
impacted fill price is better than the limit price.
If a SID hasn't started trading yet, pandas' convention is to use nans.
Before this change, zipline would raise an exception if there were nans in the
input data.
We now skip events where the prices contains a nan and has not been traded
before (in which case forward fill).
Fixes#446.
Remove pieces that are no longer used now that the simple transforms are
wrappers around history via the SIDData object.
Move window length related pieces into batch_transform, since the rest
of the utils module is no longer used.
This commit refactors the Security cython class to Asset, and refactors some fields of the class accordingly. This change is so the terminology is consistent and correct when Asset is extended to asset types that are not securities, such as futures.
on the number of per-tick update that occur since they were duplicated
per each PerformancePeriod. Also opens up the path to cythonizing the
entire object
jfkirk