ak.Record — Awkward Array 2.8.2 documentation (original) (raw)

Defined in awkward.highlevel on line 1791.

class ak.Record(self, 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, considerak.ArrayBuilder.

See also ak.fields.

ak.Record.is_tuple#

If True, the top-most record structure has no named fields, i.e. it’s a tuple.

ak.Record._ipython_key_completions_(self)#

ak.Record.__iter__ = None#

ak.Record.type#

The high-level type of this Record; same as ak.type.

Note that the outermost element of a Record’s type is always anak.types.ScalarType, which .

The type of a ak.record.Record (from ak.Array.layout) is not wrapped by an ak.types.ScalarType.

ak.Record.typestr#

The high-level type of this Record, presented as a string.

ak.Record.__getitem__(self, where)#

Parameters:

where (many types supported; see below) – Index of positions to select from this Record.

Select items from the Record using an extension of NumPy’s (already quite extensive) rules.

See ak.Array.__getitem__ for a more complete description. Since this is a record, the first item in the slice tuple must be a string, selecting a field.

For example, with

record = ak.Record({"x": 3.3, "y": [1, 2, 3]})

we can select

record["x"] 3.3 record["y"] <Array [1, 2, 3] type='3 * int64'> record["y", 1] 2

ak.Record.__setitem__(self, where, what)#

Parameters:

where (str or tuple of str) – Field name to add data to the record.
what – Data to add as the new field.

For example:

record = ak.Record({"x": 3.3}) record["y"] = 4 record["z"] = {"another": "record"} record.show() {x: 3.3, y: 4, z: {another: 'record'}}

See ak.with_field for a variant that does not change the ak.Recordin-place. (Internally, this method uses ak.with_field, so performance is not a factor in choosing one over the other.)

ak.Record.__delitem__(self, where)#

Parameters:

where (str or tuple of str) – Field name to remove from the record.

For example:

record = ak.Record({"x": 3.3, "y": {"this": 10, "that": 20}}) del record["y", "that"] record.show() {x: 3.3, y: {this: 10}}

See ak.without_field for a variant that does not change the ak.Recordin-place. (Internally, this method uses ak.without_field, so performance is not a factor in choosing one over the other.)

ak.Record.__getattr__(self, where)#

Whenever possible, fields can be accessed as attributes.

For example, the fields of

record = ak.Record({"x": 1.1, "y": [2, 2], "z": "three"})

can be accessed as

record.x 1.1 record.y <Array [2, 2] type='2 * int64'> record.z 'three'

which are equivalent to record["x"], record["y"], andrecord["z"].

Fields can’t be accessed as attributes when

ak.Record methods or properties take precedence,
a domain-specific behavior has methods or properties that take
precedence, or
the field name is not a valid Python identifier or is a Python
keyword.

ak.Record.__setattr__(self, name, value)#

Parameters:

where (str) – Attribute name to set

Set an attribute on the record.

Only existing public attributes e.g. ak.Record.layout, or private attributes (with leading underscores), can be set.

Fields are not assignable to as attributes, i.e. the following doesn’t work:

Instead, always use ak.Record.__setitem__:

or ak.with_field:

record = ak.with_field(record, new_field, "z")

to add or modify a field.

ak.Record.__dir__(self)#

Lists all methods, properties, and field names (see __getattr__) that can be accessed as attributes.

ak.Record.__str__(self)#

ak.Record.__repr__(self)#

ak.Record._repr(self, limit_cols)#

ak.Record.show(self, limit_rows=20, limit_cols=80, *, type=False, named_axis=False, nbytes=False, backend=False, all=False, stream=STDOUT, formatter=None, precision=3)#

Parameters:

limit_rows (int) – Maximum number of rows (lines) to use in the output.
limit_cols (int) – Maximum number of columns (characters wide).
type (bool) – If True, print the type as well. (Doesn’t count toward number of rows/lines limit.)
named_axis (bool) – If True, print the named axis as well. (Doesn’t count toward number of rows/lines limit.)
nbytes (bool) – If True, print the number of bytes as well. (Doesn’t count toward number of rows/lines limit.)
backend (bool) – If True, print the backend of the array as well. (Doesn’t count toward number of rows/lines limit.)
all (bool) – If True, print the ‘type’, ‘named axis’, ‘nbytes’, and ‘backend’ of the array. (Doesn’t count toward number of rows/lines limit.)
stream (object with a ``write(str)`` method or None) – Stream to write the output to. If None, return a string instead of writing to a stream.
formatter (Mapping or None) – Mapping of types/type-classes to string formatters. If None, use the default formatter.

Display the contents of the array within limit_rows and limit_cols, using ellipsis (...) for hidden nested data.

The formatter argument controls the formatting of individual values, c.f.https://numpy.org/doc/stable/reference/generated/numpy.set_printoptions.htmlAs Awkward Array does not implement strings as a NumPy dtype, the numpystrkey is ignored; instead, a "bytes" and/or "str" key is considered when formatting string values, falling back upon "str_kind".

ak.Record._repr_mimebundle_(self, include=None, exclude=None)#

ak.Record.__array_ufunc__(self, ufunc, method, *inputs)#

Intercepts attempts to pass this Record to a NumPyuniversal functions(ufuncs) and passes it through the Record’s structure.

This method conforms to NumPy’sNEP 13for overriding ufuncs, which has beenavailable since NumPy 1.13(and thus NumPy 1.13 is the minimum allowed version).

See ak.Array.__array_ufunc__ for a more complete description.

ak.Record.numba_type#

The type of this Record when it is used in Numba. It contains enough information to generate low-level code for accessing any element, down to the leaves.

See Numba documentationon types and signatures.

ak.Record.__reduce_ex__(self, protocol)#

ak.Record.__setstate__(self, state)#

ak.Record.__copy__(self)#

ak.Record.__deepcopy__(self, memo)#

ak.Record.__bool__(self)#