Memoized constructor for Terms. Caching previously-constructed Terms is useful because it allows us to only compute equivale

Add a term and all its children to ``graph``. ``parents`` is the set of all the parents of ``term` that we've added so far.

Checks if any tables are present in the current assets database. Parameters ---------- txn : Transaction

Allocate an output array whose rows should be passed to `self.compute`. The resulting array must have a shape of ``shape``.

Make sure that we've specialized all loadable terms in the graph.

Check that value is a valid categorical missing_value. Raises a TypeError if the value is cannot be used as the missing_value for a cate

Build a preprocessed function with the same signature as `func`. Uses `exec` internally to build a function that actually has the same s

Check that a window of length `window_length` is well-defined on `data`. Parameters ---------- data : np.ndarray[ndim=2] The

Clear out any assets that have expired before starting a new sim day. Performs two functions: 1. Finds all assets for which

Sync the temporary file to the final path.

Sync the temporary directory to the final path.

Compute a lifetimes matrix from our AssetFinder, then drop columns that didn't exist at all during the query dates. Paramete

Compute the raw row indices to load for each asset on a query for the given dates after applying a shift. Parameters

Takes in a dict of Asset init args and converts dates to pd.Timestamps

If the clock property is not set, then create one based on frequency.

Decrement terms recursively. Notes ----- This should only be used to build the initial workspace, after that we

Get dtypes to use when unpacking sqlite tables as dataframes.

Ensure that ``loader`` can load ``terms``.

Create a tuple containing all elements of tup, plus elem. Returns the new tuple and the index of elem in the new tuple.

Ensure that we're going to compute at least N extra rows of `term`.

Ensure that there is a Float64Multiply window for each asset that can provide data for the given parameters. If the correspon

Verify that the baseline and deltas expressions have a timestamp field. If there is not a ``TS_FIELD_NAME`` on either of the expressions, it will

Returns ------- List of tuples of (start, stop) which represent the ranges of minutes which should be excluded when a

Helper method for displaying total execution time of a Pipeline. Parameters ---------- total_seconds : float Numb

Helper for unzip which checks the lengths of each element in it. Parameters ---------- it : iterable[tuple] An iterable of tuples.

Get the Float64Multiply objects to pass to an AdjustedArrayWindow. For the use of AdjustedArrayWindow in the loader, which looks bac

Get a perf message for the given datetime.

Get a perf message for the given datetime.

Internal method that gets a window of adjusted minute data for an asset and specified date range. Used to support the history API me

Create empty ctable for given path. Parameters ---------- path : string The path to rootdir of the new c

Internal method that pre-calculates the benchmark return series for use in the simulation. Parameters ----------

Currency convert raw data loaded for ``column``. Parameters ---------- columns : list[zipline.pipeline.data.BoundCol

Compute inputs for the given term. This is mostly complicated by the fact that for each input we store as many rows as will

Return uniformly-distributed integers between 0 and 100.

The iterator produced when `traverse` is called on this Array.

Returns a standard set of pandas.DataFrames: equities, futures, exchanges, root_symbols

Construct a new dataset given the coordinates.

Build an indexer mapping ``self.sids`` to ``assets``. Parameters ---------- assets : list[int] List of a

Merge the inputs of two NumericalExpressions into a single input tuple, rewriting their respective string expressions to make input n

Calculate the minutes which should be excluded when a window occurs on days which had an early close, i.e. days where the close

Coerce buffer data for an AdjustedArray into a standard scalar representation, returning the coerced array and a dict of argument to pass