UUIDArrowType

final class lsst.daf.butler.arrow_utils.UUIDArrowType

Bases: ExtensionType

An Arrow extension type for astropy.time.Time, stored as TAI nanoseconds since 1970-01-01.

Attributes Summary

bit_width

Bit width for fixed width type.

extension_name

The extension type name.

id

num_buffers

Number of data buffers required to construct Array type excluding children.

num_fields

The number of child fields.

storage_type

The underlying storage type.

Methods Summary

equals(self, other, *[, check_metadata])

Return true if type is equivalent to passed value.

field(self, i)

Parameters:

to_pandas_dtype(self)

Return the equivalent NumPy / Pandas dtype.

wrap_array(self, storage)

Wrap the given storage array as an extension array.

Attributes Documentation

bit_width

Bit width for fixed width type.

Examples

>>> import pyarrow as pa
>>> pa.int64()
DataType(int64)
>>> pa.int64().bit_width
64
extension_name

The extension type name.

id
num_buffers

Number of data buffers required to construct Array type excluding children.

Examples

>>> import pyarrow as pa
>>> pa.int64().num_buffers
2
>>> pa.string().num_buffers
3
num_fields

The number of child fields.

Examples

>>> import pyarrow as pa
>>> pa.int64()
DataType(int64)
>>> pa.int64().num_fields
0
>>> pa.list_(pa.string())
ListType(list<item: string>)
>>> pa.list_(pa.string()).num_fields
1
>>> struct = pa.struct({'x': pa.int32(), 'y': pa.string()})
>>> struct.num_fields
2
storage_type

The underlying storage type.

Methods Documentation

equals(self, other, *, check_metadata=False)

Return true if type is equivalent to passed value.

Parameters:
otherDataType or string convertible to DataType
check_metadatabool

Whether nested Field metadata equality should be checked as well.

Returns:
is_equalbool

Examples

>>> import pyarrow as pa
>>> pa.int64().equals(pa.string())
False
>>> pa.int64().equals(pa.int64())
True
field(self, i) Field
Parameters:
iint
Returns:
pyarrow.Field
to_pandas_dtype(self)

Return the equivalent NumPy / Pandas dtype.

Examples

>>> import pyarrow as pa
>>> pa.int64().to_pandas_dtype()
<class 'numpy.int64'>
wrap_array(self, storage)

Wrap the given storage array as an extension array.

Parameters:
storageArray or ChunkedArray
Returns:
arrayArray or ChunkedArray

Extension array wrapping the storage array