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# (C) Copyright 2005-2023 Enthought, Inc., Austin, TX
# All rights reserved.
#
# This software is provided without warranty under the terms of the BSD
# license included in LICENSE.txt and may be redistributed only under
# the conditions described in the aforementioned license. The license
# is also available online at http://www.enthought.com/licenses/BSD.txt
#
# Thanks for using Enthought open source!
class ObserverGraph:
""" An ``ObserverGraph`` is an object for describing what traits are being
observed on an instance of ``HasTraits``.
The most basic unit in a graph is a node, which is a context specific
observer. For example, a node can be an observer specialized in
changes on a named trait, an observer specialized in
changes on a number of traits matching a certain criteria, an observer
specialized in mutations on a list, etc.
The most basic example is an ``ObserverGraph`` that contains only one node,
e.g. for observing changes on a named trait.
An ``ObserverGraph`` can have branches, e.g. to observe more than one trait
on a nested object. The attribute ``children`` represents these branches.
Each item in ``children`` is another ``ObserverGraph``.
In order to (1) avoid hooking up a user callback with the same observer
twice, and (2) remove an observer when they are not needed, once an
``ObserverGraph`` object is constructed (e.g. after mutating ``children``
for constructing branches) and is ready to be used against an instance
of ``HasTraits``, it should not be mutated again.
For the same reason, ``ObserverGraph`` implements ``__hash__`` and
``__eq__`` and requires its nodes to also support these methods.
An ``ObserverGraph`` does not keep states regarding the HasTraits instances
and the user callbacks it was used with. An ``ObserverGraph`` can be
reused multiple times on different ``HasTraits`` instance and with
different user callback.
This object is considered a low-level object for the observer mechanism.
It is not intended to be instantiated by users directly. Users will be
given higher-level wrappers for creating ``ObserverGraph`` objects.
Parameters
----------
node : any
A context specific observer.
It must be a hashable object. In practice, this will be
an instance that implements ``IObserver``.
children : iterable of ObserverGraph, optional
Branches on this graph. All children must be unique.
Raises
------
ValueError
If not all children are unique.
"""
__slots__ = ("node", "children")
def __init__(self, *, node, children=None):
if children is not None and len(set(children)) != len(children):
raise ValueError("Not all children are unique.")
self.node = node
self.children = list(children) if children is not None else []
def __hash__(self):
""" Return the hash of this ObserverGraph."""
return hash(
(type(self).__name__, self.node, frozenset(self.children))
)
def __eq__(self, other):
""" Return true if another object is an ObserverGraph with the
same content. The order of children is not taken into account
in the comparison.
"""
return (
type(self) is type(other)
and self.node == other.node
and set(self.children) == set(other.children)
)
def __repr__(self):
formatted_args = [f"node={self.node!r}"]
if self.children:
formatted_args.append(f"children={self.children!r}")
return f"{self.__class__.__name__}({', '.join(formatted_args)})"
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