dask_awkward.Array

dask_awkward.Array¶

class dask_awkward.Array(dsk, name, meta, divisions)[source]¶

Partitioned, lazy, and parallel Awkward Array Dask collection.

The class constructor is not intended for users. Instead use factory functions like from_parquet(), from_json(), etc.

Within dask-awkward the new_array_object factory function is used for creating new instances.

Methods

`__init__`(dsk, name, meta, divisions)
`clear_divisions`()	Clear the divisions of a Dask Awkward Collection.
`compute`(**kwargs)	Compute this dask collection
`eager_compute_divisions`()	Force a compute of the divisions.
`map_partitions`(func, args, *kwargs)	Map a function across all partitions of the collection.
`persist`(**kwargs)	Persist this dask collection into memory
`reset_meta`()	Assign an empty typetracer array as the collection metadata.
`to_dask_array`(*[, dtype, optimize_graph])
`to_dask_bag`()
`to_delayed`([optimize_graph])	Convert the collection to a list of delayed objects.
`to_parquet`(path[, storage_options])
`visualize`([filename, format, optimize_graph])	Render the computation of this object's task graph using graphviz.

Attributes

`behavior`	awkward Array behavior dictionary.
`dask`	High level task graph associated with the collection.
`divisions`	Location of the collections partition boundaries.
`fields`	Record field names (if any).
`form`	awkward Array form associated with the eventual computed result.
`keys`	Task graph keys.
`keys_array`	NumPy array of task graph keys.
`known_divisions`	True of the divisions are known (absence of `None` in the tuple).
`layout`	awkward Array layout associated with the eventual computed result.
`name`	Name of the collection.
`ndim`	Number of dimensions.
`npartitions`	Total number of partitions.
`partitions`	Get a specific partition or slice of partitions.
`type`	awkward Array type associated with the eventual computed result.

Collections

dask_awkward.Record