graphtage.dataclasses

dataclasses classes

DataClassEdit

class graphtage.dataclasses.DataClassEdit(from_node: DataClassNode, to_node: DataClassNode)

Bases: AbstractCompoundEdit

__init__(from_node: DataClassNode, to_node: DataClassNode)

Constructs a new Edit.

Parameters:

from_node – The node that this edit transforms.
to_node – The node that this edit transforms from_node into.
constant_cost – A optional lower bound on the cost of this edit.
cost_upper_bound – An optional upper bound on the cost of this edit.

__iter__() → Iterator[Edit]

Returns an iterator over this edit’s sub-edits.

Returns:: The result of AbstractCompoundEdit.edits()
Return type:: Iterator[Edit]

__lt__(other): Tests whether the bounds of this edit are less than the bounds of other.

_debug_tighten_bounds() → bool: Adds debugging assertions when tightening bounds; for debugging only

bounds() → Range

Returns the bounds of this edit.

This defaults to the bounds provided when this AbstractEdit was constructed. If an upper bound was not provided to the constructor, the upper bound defaults to:

self.from_node.total_size + self.to_node.total_size + 1

Returns:: A range bounding the cost of this edit.
Return type:: Range

edits() → Iterator[Edit]: Returns an iterator over this edit’s sub-edits

from_node: TreeNode

has_non_zero_cost() → bool

Returns whether this edit has a non-zero cost.

This will tighten the edit’s bounds until either its lower bound is greater than zero or its bounds are definitive.

initial_bounds: Range

is_complete() → bool

An edit is complete when no further calls to Edit.tighten_bounds() will change the nature of the edit.

This implementation considers an edit complete if it is valid and its bounds are definitive:

return not self.valid or self.bounds().definitive()

If an edit is able to discern that it has a unique solution even if its final bounds are unknown, it should reimplement this method to define that check.

For example, in the case of a CompoundEdit, this method should only return True if no future calls to Edit.tighten_bounds() will affect the result of CompoundEdit.edits().

Returns:: True if subsequent calls to Edit.tighten_bounds() will only serve to tighten the bounds of this edit and will not affect the semantics of the edit.
Return type:: bool

on_diff(from_node: EditedTreeNode)

A callback for when an edit is assigned to an EditedTreeNode in TreeNode.diff().

This default implementation adds the edit to the node, and recursively calls Edit.on_diff() on all of the sub-edits:

from_node.edit = self
from_node.edit_list.append(self)
for edit in self.edits():
    edit.on_diff(edit.from_node)

Parameters:: from_node – The edited node that was added to the diff

print(formatter: GraphtageFormatter, printer: Printer)

Edits can optionally implement a printing method

This function is called automatically from the formatter in the Printing Protocol and should never be called directly unless you really know what you’re doing! Raising NotImplementedError will cause the formatter to fall back on its own printing implementations.

This implementation is equivalent to:

for edit in self.edits():
    edit.print(formatter, printer)

tighten_bounds() → bool

Tightens the Edit.bounds() on the cost of this edit, if possible.

Returns:: True if the bounds have been tightened.
Return type:: bool

Note

Implementations of this function should return False if and only if self.bounds().definitive().

property valid: bool: Returns whether this edit is valid

DataClassNode

class graphtage.dataclasses.DataClassNode(*args, **kwargs)

Bases: ContainerNode

A container node that can be initialized similar to a Python dataclasses.dataclass()

__init__(*args, **kwargs): Be careful extending __init__; consider using DataClassNode.post_init() instead.

add_edit_modifier(modifier: Callable[[TreeNode, TreeNode], Edit | None])

all_children_are_leaves() → bool

Tests whether all of the children of this container are leaves.

Equivalent to:

all(c.is_leaf for c in self)

Returns:: True if all children are leaves.
Return type:: bool

calculate_total_size() → int

Calculates the size of this node. This is an arbitrary, immutable value that is used to calculate the bounded costs of edits on this node.

Returns:: An arbitrary integer representing the size of this node.
Return type:: int

children() → Sequence[TreeNode]

The children of this node.

Equivalent to:

list(self)

copy() → T: Creates a deep copy of this node

copy_from(children: Iterable[TreeNode]) → T: Constructs a new instance of this tree node from a list of its children

dfs() → Iterator[TreeNode]

Performs a depth-first traversal over all of this node’s descendants.

self is always included and yielded first.

This implementation is equivalent to:

stack = [self]
while stack:
    node = stack.pop()
    yield node
    stack.extend(reversed(node.children()))

diff(node: TreeNode) → EditedTreeNode | T

Performs a diff against the provided node.

Parameters:: node – The node against which to perform the diff.
Returns:: An edited version of this node with all edits being completed.
Return type:: Union[EditedTreeNode, T]

editable_dict() → Dict[str, Any]

Copies self.__dict__, calling TreeNode.editable_dict() on any TreeNode objects therein.

This is equivalent to:

ret = dict(self.__dict__)
if not self.is_leaf:
    for key, value in ret.items():
        if isinstance(value, TreeNode):
            ret[key] = value.make_edited()
return ret

This is used by TreeNode.make_edited().

property edited: bool

Returns whether this node has been edited.

The default implementation returns False, whereas EditedTreeNode.edited() returns True.

edits(node: TreeNode) → Edit

Calculates the best edit to transform this node into the provided node.

Parameters:: node – The node to which to transform.
Returns:: The best possible edit.
Return type:: Edit

get_all_edit_contexts(node: TreeNode) → Iterator[Tuple[Tuple[TreeNode, ...], Edit]]

Returns an iterator over all edit contexts that will transform this node into the provided node.

Parameters:: node – The node to which to transform this one.
Returns:: An iterator over pairs of paths from node to the edited node, as well as its edit. Note that this iterator will automatically explode any CompoundEdit in the sequence.
Return type:: Iterator[Tuple[Tuple[“TreeNode”, …], Edit]

get_all_edits(node: TreeNode) → Iterator[Edit]

Returns an iterator over all edits that will transform this node into the provided node.

Parameters:: node – The node to which to transform this one.
Returns:: An iterator over edits. Note that this iterator will automatically explode any CompoundEdit in the sequence.
Return type:: Iterator[Edit]

property is_leaf: bool

Container nodes are never leaves, even if they have no children.

Returns:: False
Return type:: bool

items() → Iterator[Tuple[str, TreeNode]]

make_edited() → EditedTreeNode | T

Returns a new, copied instance of this node that is also an instance of EditedTreeNode.

This is equivalent to:

return self.__class__.edited_type()(self)

Returns:: A copied version of this node that is also an instance of EditedTreeNode and thereby mutable.
Return type:: Union[EditedTreeNode, T]

property parent: TreeNode | None

The parent node of this node, or None if it has no parent.

The setter for this property should only be called by the parent node setting itself as the parent of its child.

ContainerNode subclasses automatically set this property for all of their children. However, if you define a subclass of TreeNode does not extend off of ContainerNode and for which len(self.children()) > 0, then each child’s parent must be set.

post_init()

Callback called after this class’s members have been initialized.

This callback should not call super().post_init(). Each superclass’s post_init() will be automatically called in order of the __mro__.

print(printer: Printer): Prints this node.

print_parent_context(printer: Printer, for_child: TreeNode)

Prints the context for the given child node.

For example, if this node represents a list and the child is the element at index 3, then “[3]” might be printed.

The child is expected to be one of this node’s children, but this is not validated.

The default implementation prints nothing.

to_obj()

Returns a pure Python representation of this node.

For example, a node representing a list, like graphtage.ListNode, should return a Python list. A node representing a mapping, like graphtage.MappingNode, should return a Python dict. Container nodes should recursively call TreeNode.to_obj() on all of their children.

This is used solely for the providing objects to operate on in the commandline expressions evaluation, for options like –match-if and –match-unless.

property total_size: int

The size of this node.

This is an arbitrary, immutable value that is used to calculate the bounded costs of edits on this node.

The first time this property is called, its value will be set and memoized by calling TreeNode.calculate_total_size().

Returns:: An arbitrary integer representing the size of this node.
Return type:: int