neurolang.datalog.instance module

class neurolang.datalog.instance.FrozenInstance(elements=None)

Bases: object

Methods

copy
is_empty

copy()

is_empty()

class neurolang.datalog.instance.FrozenMapInstance(elements=None)

Bases: FrozenInstance, Mapping

Methods

get(k[,d])
items()
keys()
values()

as_map
as_set
copy
is_empty

as_map()

as_set()

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

values() → an object providing a view on D's values

class neurolang.datalog.instance.FrozenSetInstance(elements=None)

Bases: FrozenInstance, Set

Methods

isdisjoint(other)

Return True if two sets have a null intersection.

as_map
as_set
copy
is_empty

as_map()

as_set()

class neurolang.datalog.instance.Instance(elements=None)

Bases: FrozenInstance

Methods

copy
is_empty

copy()

class neurolang.datalog.instance.MapInstance(elements=None)

Bases: Instance, FrozenMapInstance, MutableMapping

Methods

clear()
get(k[,d])
items()
keys()
pop(k[,d])	If key is not found, d is returned if given, otherwise KeyError is raised.
popitem()	as a 2-tuple; but raise KeyError if D is empty.
setdefault(k[,d])
update([E, ]**F)	If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v
values()

as_map
as_set
copy
is_empty

as_map()

as_set()

class neurolang.datalog.instance.SetInstance(elements=None)

Bases: Instance, FrozenSetInstance, MutableSet

Methods

add(value)	Add an element.
clear()	This is slow (creates N new iterators!) but effective.
discard(value)	Remove an element.
isdisjoint(other)	Return True if two sets have a null intersection.
pop()	Return the popped value.
remove(value)	Remove an element.

as_map
as_set
copy
is_empty

add(value)

Add an element.

as_map()

as_set()

discard(value)

Remove an element. Do not raise an exception if absent.