******************************************* Overview ******************************************* Simulations =========== :mod:`zipline` runs backtests using asynchronous components and zeromq messaging for communication and coordination. :class:`.algorithm.TradingAlgorithm` is the heart of :mod:`zipline`, and the primary access point for creating, launching, and tracking simulations. You can find it in :py:class:`~zipline.algorithm.TradingAlgorithm` Simulator Sub-Components ======================== Each simulation contains numerous subcomponents, each operating asynchronously from all others, and communicating via zeromq. DataSources -------------------- A DataSource represents a historical event record, which will be played back during simulation. A simulation may have one or more DataSources, which will be combined in DataFeed. Generally, datasources read records from a persistent store (db, csv file, remote service), format the messages for downstream simulation components, and send them to a PUSH socket. See the base class for all datasources :py:class:`~zipline.messaging.DataSource` and the module holding all datasources :py:mod:`zipline.sources` DataFeed -------------------- All simulations start with a collection of :py:class:`~zipline.messaging.DataSource`, which need to be fed to an algorithm. Each :py:class:`~zipline.sources.DataSource`can contain events of differing content (trades, quotes, corporate event) and frequency (quarterly, intraday). To simplify the process of managing the data sources, :py:class:`~zipline.core.DataFeed` can receive events from multiple :py:class:`DataSources ` and combine them into a serial chronological stream. Transforms -------------------- Often, an algorithm will require a running calculation on top of a :py:class:`~zipline.messaging.DataSource`, or on the consolidated feed. A simple example is a technical indicator or a moving average. Transforms can be described in :py:class:`~zipline.core.Simulator`'s configuration. Subclass :py:class:`~zipline.transforms.core.Transform` to add your own Transform. Transforms must hold their own state between events, and serialize their current values into messages. Data Alignment -------------------- Like Datasources, Transforms have differing frequencies and results. Simulator manages the results of parallel transforms and **aligns** transform results with the raw DataFeed. Client algorithms simply receive a map of data, which includes the current event and all the transformed values. Time Compression -------------------- According to `this post `_ on the Quantopian forums, time periods during which none of the selected SIDs were traded are skipped. Review the unit test coverage_. .. _coverage: cover/index.html