ak.Record#

Defined in awkward.highlevel on line 1806.

class ak.Record(data, *, behavior=None, with_name=None, check_valid=False, backend=None, attrs=None, named_axis=None)#

Parameters:

data (ak.record.Record, ak.Record, str, or dict) – Data to wrap or convert into a record. If a string, the data are assumed to be JSON. If a dict, calls ak.from_iter, which assumes all inner dimensions have irregular lengths.
behavior (None or dict) – Custom ak.behavior for this Record only.
with_name (None or str) – Gives the record type a name that can be used to override its behavior (see below).
check_valid (bool) – If True, verify that the layout is valid.
backend (None, "cpu", "jax", "cuda") – If "cpu", the Array will be placed in main memory for use with other "cpu" Arrays and Records; if "cuda", the Array will be placed in GPU global memory using CUDA; if "jax", the structure is copied to the CPU for use with JAX. if None, the data are left untouched.

High-level record that can contain fields of any type.

Most users won’t be creating Records manually. This class primarily exists to be overridden in the same way as ak.Array.

Records can be used in Numba: they can be passed as arguments to a Numba-compiled function or returned as return values. The only limitation is that they cannot be created inside the Numba-compiled function; to make outputs, consider ak.ArrayBuilder.

See also ak.Array and ak.behavior.

_layout#

_behavior = None#

_attrs = None#

_update_class()#

property attrs: awkward._attrs.Attrs#

The mapping containing top-level metadata, which is serialised with the record during pickling.

Keys prefixed with @ are identified as “transient” attributes which are discarded prior to pickling, permitting the storage of non-pickleable types.

property layout#

The #ak.record.Record that contains composable #ak.contents.Content elements to determine how the array is structured.

See #ak.Array.layout for a more complete description.

The #ak.record.Record is not a subclass of #ak.contents.Content in Python and it is not composable with them: #ak.record.Record contains one #ak.contents.RecordArray (which is a #ak.contents.Content), but #ak.contents.Content nodes cannot contain a #ak.record.Record.

A #ak.record.Record is not an independent entity from its #ak.contents.RecordArray; it’s really just a marker indicating which element to select. The XML representation reflects that:

>>> vectors = ak.Array([{"x": 0.1, "y": 1.0, "z": 30.0},
...                     {"x": 0.2, "y": 2.0, "z": 20.0},
...                     {"x": 0.3, "y": 3.0, "z": 10.0}])
>>> vectors[1].layout
<Record at='1'>
    <array><RecordArray is_tuple='false' len='3'>
        <content index='0' field='x'>
            <NumpyArray dtype='float64' len='3'>[0.1 0.2 0.3]</NumpyArray>
        </content>
        <content index='1' field='y'>
            <NumpyArray dtype='float64' len='3'>[1. 2. 3.]</NumpyArray>
        </content>
        <content index='2' field='z'>
            <NumpyArray dtype='float64' len='3'>[30. 20. 10.]</NumpyArray>
        </content>
    </RecordArray></array>
</Record>

property behavior#

The behavior parameter passed into this Record’s constructor.

If a dict, this behavior overrides the global #ak.behavior.
Any keys in the global #ak.behavior but not this behavior are still valid, but any keys in both are overridden by this behavior. Keys with a None value are equivalent to missing keys, so this behavior can effectively remove keys from the global #ak.behavior.
If None, the Record defaults to the global #ak.behavior.

See #ak.behavior for a list of recognized key patterns and their meanings.

property positional_axis: tuple[int, Ellipsis]#

property named_axis: awkward._namedaxis.AxisMapping#

tolist()#: Converts this Record into Python objects; same as #ak.to_list (but without the underscore, like NumPy’s [tolist](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.tolist.html)).

to_list()#: Converts this Record into Python objects; same as #ak.to_list.

property nbytes#

The total number of bytes in all the #ak.index.Index, and #ak.contents.NumpyArray buffers in this array tree.

It does not count buffers that must be kept in memory because of ownership, but are not directly used in the array. Nor does it count the (small) Python objects that reference the (large) array buffers.

property fields#

List of field names or tuple slot numbers (as strings) of this record.

If this is actually a tuple its fields are string representations of integers, such as “0”, “1”, “2”, etc.