tfds.core.BeamMetadataDict

A tfds.core.Metadata object supporting Beam-generated datasets.

Inherits From: MetadataDict

Methods

clear

D.clear() -> None. Remove all items from D.

copy

D.copy() -> a shallow copy of D

fromkeys

Create a new dictionary with keys from iterable and values set to value.

get

Return the value for key if key is in the dictionary, else default.

items

D.items() -> a set-like object providing a view on D's items

keys

D.keys() -> a set-like object providing a view on D's keys

load_metadata

View source

Restore the metadata.

pop

D.pop(k[,d]) -> v, remove specified key and return the corresponding value. If key is not found, d is returned if given, otherwise KeyError is raised

popitem

D.popitem() -> (k, v), remove and return some (key, value) pair as a 2-tuple; but raise KeyError if D is empty.

save_metadata

View source

Save the metadata inside the beam job.

setdefault

Insert key with a value of default if key is not in the dictionary.

Return the value for key if key is in the dictionary, else default.

update

D.update([E, ]**F) -> None. Update D from dict/iterable E and F. If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]

values

D.values() -> an object providing a view on D's values

__contains__

True if the dictionary has the specified key, else False.

__eq__

Return self==value.

__ge__

Return self>=value.

__getitem__

x.getitem(y) <==> x[y]

__gt__

Return self>value.

__iter__

Implement iter(self).

__le__

Return self<=value.

__len__

Return len(self).

__lt__

Return self<value.

__ne__

Return self!=value.