Data Bundles ------------ A data bundle is a collection of pricing data, adjustment data, and an asset database. Bundles allow us to preload all of the data we will need to run backtests and store the data for future runs. Ingesting Data ~~~~~~~~~~~~~~ The first step to using a data bundle is to ingest the data. This will invoke some custom bundle command and then write the data to a standard location that zipline can find. By default this location is ``$ZIPLINE_ROOT/data/`` where by default ``ZIPLINE_ROOT=~/.zipline``. This step may take some time as it could involve downloading and processing a lot of data. This can be run with: .. code-block:: bash $ python -m zipline ingest where ```` is the name of the bundle to ingest. Old Data ~~~~~~~~ When the ``ingest`` command is used it will write the new data to a subdirectory of ``$ZIPLINE_ROOT/data/`` which is named with the current date. This makes it possible to look at older data or even run backtests with this older copy. This makers it easier to reproduce backtest results later. One drawback of saving all of this data by default is that the data directory may grow quite large even if you do not want to use the data. To solve this problem there is another command ``clean`` which will clear data bundles based on some time constraints. For example: .. code-block:: bash # clean everything older than $ python -m zipline clean --before # clean everything newer than $ python -m zipline clean --after # keep everything in the range of [before, after] and delete the rest $ python -m zipline clean --before --after # clean all but the last runs $ python -m zipline clean --keep-last Running Backtests with Data Bundles ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Now that the data has been ingested we can use it to run backtests with the ``run`` command. This can be specified with the ``--bundle`` option like: .. code-block:: bash $ python -m zipline run --bundle --algofile algo.py ... We may also specify the date to use to look up the bundle data with the ``--bundle-date`` option. This will cause us to the the most recent bundle ingestion that is less than or equal to the ``bundle-date``. This is how we can run backtests with older data. The reason that this uses a less than or equal to relationship is that we can specify the date that we ran an old backtest and get the same data that would have been available to us on that date. The ``bundle-date`` defaults to the current day to use the most recent data. Default Data Bundles ~~~~~~~~~~~~~~~~~~~~ .. _quandl-data-bundle: Quandl WIKI Bundle `````````````````` By default zipline comes with the ``quandl`` data bundle which uses quandl's `WIKI dataset `_. The quandl data bundle includes daily pricing data, splits, cash dividends, and asset metadata. This is the bundle that ``run`` will use by default if no other bundle is specified. To ingest this data bundle we recommend creating an account on quandl.com to get an API key to be able to make more API requests per day. Once we have an API key we may run: .. code-block:: bash $ QUANDL_API_KEY= python -m zipline ingest quandl though we may still run ``ingest`` as an anonymous quandl user (with no API key). We may also set the ``QUANDL_DOWNLOAD_ATTEMPTS`` environment variable to an integer which is the number of attempts that should be made to download data from quandls servers. By default this will be 5, meaning that we will retry each attempt 5 times. .. note:: ``QUANDL_DOWNLOAD_ATTEMPTS`` is not the total number of allowed failures, just the number of allowed failures per request. The quandl loader will make one request per 100 equities for the metadata followed by one request per equity. Yahoo Bundle Factories `````````````````````` Zipline also ships with a factory function for creating a data bundle out of a set of tickers from yahoo: :func:`~zipline.data.bundles.yahoo_equities`. This makes it easy to pre-download and cache the data for a set of equities from yahoo. This includes daily pricing data along with splits, cash dividends, and inferred asset metadata. To create a bundle from a set of equities, add the following to your ``~/.zipline/extensions.py`` file: .. code-block:: python from zipline.bundles import register, yahoo_equities # these are the tickers you would like data for equities = { 'AAPL', 'MSFT', 'GOOG', } register( 'my-yahoo-equities-bundle', # name this whatever you like yahoo_equities(equities), ) This may now be used like: .. code-block:: bash $ python -m zipline ingest my-yahoo-equities-bundle $ python -m zipline run -f algo.py --bundle my-yahoo-equities-bundle More than one yahoo equities bundle may be registered as long as they use different names. Writing a New Bundle ~~~~~~~~~~~~~~~~~~~~ Data bundles exist to make it easy to use different data sources with zipline. To add a new bundle, one must implement an ingest function. This function is responsible for loading the data into memory and passing it to a set of writer objects provided by zipline to convert the data to zipline's internal format. The ingest function may work by downloading data from a remote location like the ``quandl`` bundle or yahoo bundles or it may just load files that are already on the machine. The function is provided with writers that will write the data to the correct location transactionally. If an ingestion fails part way through the bundle will not be written in an incomplete state. The signature of the ingest function should be: .. code-block:: python ingest(environ, asset_db_writer, minute_bar_writer, daily_bar_writer, adjustment_writer, calendar, cache, show_progress) ``environ`` ``````````` ``environ`` is a mapping representing the environment variables to use. This is where any custom arguments needed for the ingestion should be passed, for example: the ``quandl`` bundle uses the enviornment to pass the API key and the download retry attempt count. ``asset_db_writer`` ``````````````````` ``asset_db_writer`` is an instance of :class:`~zipline.assets.AssetDBWriter`. This is the writer for the asset metadata which provides the asset lifetimes and the symbol to asset id (sid) mapping. This may also contain the asset name, exchange and a few other columns. To write data, invoke :meth:`~zipline.assets.AssetDBWriter.write` with dataframes for the various pieces of metadata. More information about the format of the data exists in the docs for write. ``minute_bar_writer`` ````````````````````` ``minute_bar_writer`` is an instance of :class:`~zipline.data.minute_bars.BcolzMinuteBarWriter`. This writer is used to convert data to zipline's internal bcolz format to later be read by a :class:`~zipline.data.minute_bars.BcolzMinuteBarReader`. If minute data is provided, users should call :meth:`~zipline.data.minute_bars.BcolzMinuteBarWriter.write` with an iterable of (sid, dataframe) tuples. The ``show_progress`` argument should also be forwarded to this method. If the data source does not provide minute level data, then there is no need to call the write method. It is also acceptable to pass an empty iterator to :meth:`~zipline.data.minute_bars.BcolzMinuteBarWriter.write` to signal that there is no minutely data. .. note:: The data passed to :meth:`~zipline.data.minute_bars.BcolzMinuteBarWriter.write` may be a lazy iterator or generator to avoid loading all of the minute data into memory at a single time. A given sid may also appear multiple times in the data as long as the dates are strictly increasing. ``daily_bar_writer`` ```````````````````` ``daily_bar_writer`` is an instance of :class:`~zipline.data.us_equity_pricing.BcolzDailyBarWriter`. This writer is used to convert data into zipline's internal bcolz format to later be read by a :class:`~zipline.data.us_equity_pricing.BcolzDailyBarReader`. If daily data is provided, users should call :meth:`~zipline.data.minute_bars.BcolzDailyBarWriter.write` with an iterable of (sid dataframe) tuples. The ``show_progress`` argument should also be forwarded to this method. If the data shource does not provide daily data, then there is no need to call the write method. It is also acceptable to pass an empty iterable to :meth:`~zipline.data.minute_bars.BcolzMinuteBarWriter.write` to signal that there is no daily data. If no daily data is provided but minute data is provided, a daily rollup will happen to service daily history requests. .. note:: Like the ``minute_bar_writer``, the data passed to :meth:`~zipline.data.minute_bars.BcolzMinuteBarWriter.write` may be a lazy iterable or generator to avoid loading all of the data into memory at once. Unlike the ``minute_bar_writer``, a sid may only appear once in the data iterable. ``adjustment_writer`` ````````````````````` ``adjustment_writer`` is an instance of :class:`~zipline.data.us_equity_pricing.SQLiteAdjustmentWriter`. This writer is used to store splits, mergers, dividends, and stock dividends. The data should be provided as dataframes and passed to :meth:`~zipline.data.us_equity_pricing.SQLiteAdjustmentWriter.write`. Each of these fields are optional, but the writer can accept as much of the data as you have. ``calendar`` ```````````` ``calendar`` is a ``pandas.DatetimeIndex`` object holding all of the trading days that the bundle should load data for. This is to help some bundles generate queries for the days needed. ``cache`` ````````` ``cache`` is an instance of :class:`~zipline.utils.cache.dataframe_cache`. This object is a mapping from strings to dataframes. This object is provided in case an ingestion crashes part way through. The idea is that the ingest function should check the cache for raw data, if it doesn't exist in the cache, it should acquire it and then store it in the cache. Then it can parse and write the data. The cache will be cleared only after a successful load, this prevents the ingest function from needing to redownload all the data if there is some bug in the parsing. If it is very fast to get the data, for example if it is coming from another local file, then there is no need to use this cache. ``show_progress`` ````````````````` ``show_progress`` is a boolean indicating that the user would like to receive feedback about the ingest function's progress fetching and writing the data. Some examples for where to show how many files you have downloaded out of the total needed, or how far into some data conversion the ingest function is. One tool that may help with implementing ``show_progress`` for a loop is :class:`~zipline.utils.cli.maybe_show_progress`. This argument should always be forwarded to ``minute_bar_writer.write`` and ``daily_bar_writer.write``.