Undoable - a decorated undo stack
Introduction
I enjoy playing with state in programming. The more pointless, (often) the better. Python’s accessible introspection and reflection offers nice opportunities for exploration. In just a few lines you can find out the members (methods and variables) an object has, make copies, and decorate their behaviours.
So, here’s Undoable: An undo stack for objects via decoration or extension.
The code is available here: https://github.com/maankoe/undoable
Usage
You can use it by decorating the class with @unndoable($variable)
, to add an undo stack for $variable
, for example:
@undoable("x")
class State:
def __init__(self, x):
self.x = x
After this decoration, a State
object will have two new methods, undo()
, which undoes any change to State.x
and redo()
, which redoes that change.
state = Stateful(1) # state.x == 1
state.x = 2 # state.x == 2
state.x = 3 # state.x == 3
state.undo() # state.x == 2
state.redo() # state.x == 3
state.undo() # state.x == 2
state.undo() # state.x == 1
If decorating the whole class is too broad-brush, individual methods can be decorated (but of course, only their changes will go onto the stack).
class Stateful(Undoable):
def __init__(self, x):
super().__init__()
self.x = x
@undoable("x")
def set_x(self, x):
self.x = x
If undoable runs out of stack (undo or redo is called one too many times), an exception will be thrown. For undo:
state = Stateful(1)
state.undo() # raise IndexError - empty undo stack,
and redo:
state = Stateful(1)
state.redo() # raise IndexError - empty redo stack.
Implementation
The mechanics behind the scenes is to decorate each of the methods and maintain two stacks: undo
and redo
.
When a class method is called, the current (before method execution) state is added to the undo stack.
State is represented as a dictionary mapping the variable’s name to it’s value, i.e., {$variable_name: $variable}
.
When undo()
is called, a copy (via copy.copy
) of the current state is pushed onto the redo stack, then the undo stack is popped and the previous state is restored.
When redo()
is called, the opposite happens, the current state is pushed onto the undo stack, then the redo stack is popped and the state is restored.
In the above example, we would have the following stacks:
state = Stateful(1) # undo: [], redo: []
state.x = 2 # undo: [{"x": 1}], redo: []
state.x = 3 # undo: [{"x": 1}, {"x": 2}], redo: []
state.undo() # undo: [{"x": 1}], redo: [{"x": 3}]
state.redo() # undo: [{"x": 1}, {"x": 2}], redo: []
state.undo() # undo: [{"x": 1}], redo: [{"x": 3}]
state.undo() # undo: [], redo: [{"x": 3}, {"x": 2}]
Given this representation, Undoable neatly can track multiple variables when they are provided as var-args, @undoable("x", "y")
.
Alternatively, all fields can be tracked by extending Undoable.
class Stateful(Undoable):
def __init__(self, x, y, z):
super().__init__()
self.x = x
self.y = y
self.z = z
Limitations and extensions
One limitation Undoable has is fields are tracked individually, rather than together.
This can be problematic if a method call changes multiple tracked variables, each change will be added to the stack individually.
This means undo
and redo
only partially roll-back the effects of the method call.
For instance, consider the following class:
@undoable("x", "y")
class Stateful:
def __init__(self, x, y):
super().__init__()
self.x = x
self.y = y
def operation(self, new_x, new_y):
self.x = new_x
self.y = new_y
Calling Stateful.operation(..)
changes first x
and then y
, causing the stack and state to be as follows.
state = Stateful(1, 11) # x==1, y==11, undo: [], redo: []
state.operation(2, 12) # x==2, y==12, undo: [{"x": 1}, {"y": 11}], redo: []
state.undo() # x==2, y==11, undo: [{"x": 1}], redo: [{"y": 12}]
state.redo() # x==2, y==12, undo: [{"x": 1}, {"y": 11}], redo: []
state.undo() # x==2, y==11, undo: [{"x": 1}], redo: [{"y": 12}]
state.undo() # x==1, y==11, undo: [], redo: [{"y": 12}, {"x": 2}]
Clearly then, an extension would be to have multiple variables inside each stack entry.
Another extension that may be interesting is to allow dependency injection for copy
, paving the way for deepcopy
when needed or custom copy functions if desired.