Changes the overlap behavior so that it is an error to write data which
would have two companies holding the same ticker. Other than one test
around which company would win in that case, all the other tests are
passing. That single test has been changed to check the write-time
error.
Instead of having separate ExchangeCalendar and TradingSchedule objects, we
now just have TradingCalendar. The TradingCalendar keeps track of each
session (defined as a contiguous set of minutes between an open and a close).
It's also responsible for handling the grouping logic of any given minute
to its containing session, or the next/previous session if it's not a market
minute for the given calendar.
Replace it by distinguishing between "Loadable" and "Computable".
This is useful because it's now possible to write computable terms that
don't require any inputs (e.g. an `Always` filter or an `Everything`
classifier).
EarningsCalendar loader.
- Moves most of AdjustedArray back into Python. The window iterator is
the only part that's performance-intensive.
- Adds a bootleg templating system for creating specialized versions of
AdjustedArrayWindow for each concrete type we care about.
- Adds support for differently dtyped terms in pipeline. This allows us
to use datetime64s which are needed in the EarningsCalendar.
- Adds EarningsCalendar dataset for the next and previous earnings
announcements in pipeline.
- Adds in memory loader for EarningsCalendar.
- Adds blaze loader for EarningsCalendar.
- Adds `zipline.pipeline.Pipeline`, a new user-facing class for managing
pipelines of Modeling API expressions.
- Adds `attach_pipeline` and `drain_pipeline` as API methods
- Removes `add_factor` and `add_filter` as API methods. These have been
replaced two new methods on `Pipeline`: `add`, and `apply_screen`.
- Adding a `Filter` as a column no longer implicitly truncates rows from
the Modelling API output. It simply causes a new column, of dtype
`bool` to show up in the output. Removal of rows is now handled by the
new `apply_screen` method of `Pipeline`.
- Refactors the existing Modeling API tests to reflect the new APIs.
- Fixes an error where Modeling API data known as of the close of `day
N` would be shown to algorithms during `before_trading_start` as of
the close of the same day. Algorithms should now only receive data
during `before_trading_start/handle_data` that was known as of the
simulation time at which the function would be called.
- All Term instances now have a `mask` attribute that must be a `Filter`
or an instance of `AssetExists()`. `mask` can be used to specify that
a Factor should be computed in a manner that ignores the values that
were not `True` in the mask.
- Changed the interface for `FFCLoader.load_adjusted_array` and
`Term._compute` from `(columns, mask)`, with mask as a DataFrame, to
`(columns, dates, assets, mask)`, where mask is a numpy array. This
is primarily to avoid having to reconstruct extra DataFrames when
using masks produced by non `AssetExists` filters.
- Adds `BoundColumn.latest`, which gives the most-recently-known value
of a column.
This commit removes the ability to reference a shared TradingEnvironment through the zipline.finance.trading module. In place, the classes that require a TradingEnvironment, or its child AssetFinder, contain their own references to those objects.
This commit also adds serialization utilities that allow for the pickling/unpickling of objects without unintentionally their TradingEnvironments or AssetFinders.
The write_data methods invokes the relevant AssetDBWriter subclass
to write data to the database. update_asset_finder is no longer
a relevant method since the AssetFinder is strictly a reader class.
This patch lays the groundwork for a compute engine designed to
facilitate construction of factor-based universe screening and portfolio
allocation. It contains:
A new module, `zipline.modelling`, containing entities that can be used
to express computations as dependency graphs. Each node in such a graph
is an instance of the base `Term` class, defined in
`zipline.modelling.term`. Dependency graphs are executed by instances
of `FFCEngine`, defined in `zipline.modelling.engine`.
A new module, `zipline.data.ffc`, containing loaders and dataset
definitions for inputs to the modelling API.
New `TradingAlgorithm` api methods: `add_factor`, and `add_filter`.
These methods can only be called from `initialize`, and are used to
inform the algorithm that each day it should compute the given terms.
Computed factor results are made available through a new attribute of
the `data` object in `before_trading_start` and `handle_data`. Computed
filter results control which assets are available in the factor matrix
on each day.
Removes unused future lookup methods and consolidates everything into lookup_future_chain. Since the FutureChain object will have to hold a root symbol and dates, it should be responsible for cleaning the user input, so this is removed from the lookup method.
Adds knowledge date to future lookups. This makes our definition of valid contracts more flexible. We know about a contract if it starts trading by the knowledge date, and a contract is expired if it expires by the as_of_date.
Also fixes a bug with computing future chains, where contracts were not included in the chain on their expiration date.
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.
- NotHalfDay only worked at midnight
- week_(start|end) were actually month_(start|end)
- Removes check_args from api.
- Default offset of 30mins for market_(open|close)
Previously order was not checking for nan values sent as
limit or stop prices. It will now raise a runtime exception
in the event that an attempt to order with a nan price is made.
Previously, calling order() in initalize resulted in a weird
stack trace. It now returns a well formulated error that is
readable to the user through the API. Adding a slippage
kwarg to test_algorithm and simfactor was necessary because
slippage can only be called during init. Previously initaliazed
was never set to true and calls to init-only function were sprinkled
around the code in non-init sections. Code changes were to enforce
init-only rules.
Make the error messages for {DoBadThing}PostInit no longer reference "the
simulation", since the algorithm may not actually be running as a simulation.
Adds four new methods to the Zipline API that can be used as circuit-breakers
to interrupt the execution of an algorithm. The API methods are:
`set_max_position_size`
`set_max_order_size`
`set_max_order_count`
`set_long_only`
Internally, these methods are implemented by each registering a TradingControl
callback object with the TradingAlgorithm. During
TradingAlgorithm.__validate_order_params (and thus before any side-effects of
the order call occur), each callback's `validate` method is called with
information about the order to be placed and the algorithm's current state,
raising an exception if the callback detects that an error condition has been breached.
Scott Sanderson