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persistent_doc - An XML-like document with spreadsheet formulas for values and underlying persistent data structures


Clone this repository and then

pip install -r requirements.txt

Sample usage

>>> from persistent_doc.document import Document, FrozenNode as Node, Ex
>>> root = Node("foo", params={"id": "one"})
>>> doc = Document(root)
>>> doc['one'].append(Node("bar", params={"id": "two"}))
>>> doc['one.0']
>>> doc['one.x'] = 3
>>> doc['one']['x']
>>> doc['two.x'] = Ex("`one.x + 3")
>>> doc['two.x']
>>> doc['one.x'] += 1
>>> doc['two.x']

Examples of relative paths, longer reference chain and undo-redo

>>> doc['two.y'] = Ex("`two.parent.x + `two.x")
>>> doc['two.y']
>>> doc['one.x'] += 1
>>> doc['two.y']
>>> doc.undo()
>>> doc.undo()
>>> doc.undo()
>>> doc.undo()
>>> doc['one.x'], doc['two.y']
(4, 11)
>>> doc.start_group("one_step")
>>> doc['one.x'] += 1
>>> doc.end_group("one_step")
>>> doc['one.x'], doc['two.y']
(5, 13)
>>> doc.undo()
>>> doc['one.x'], doc['two.y']
(4, 11)
>>> doc.redo()
>>> doc['one.x'], doc['two.y']
(5, 13)

Document model

Like XML, the document is a tree where each node has a list of children and key-value pairs for parameters. Like SVG, each node has a unique id property within the document.

Parameter values can be "formulas" treating other nodes' id as variables (and a relative path of parent, children and parameter keys).

The document is persistent to allow easy undo-redo with spending too much memory. Persistent means that mutations to an object always creates a new version but the new version shares memory with the old version. (It could potentially allow erasing history to save more on memory.)

While the underlying data structures are immutable but have the same interface as mutable objects.

Formula syntax

Syntax may change in the future. To set a formula as value, create an Ex object with a string (in this syntax) to be evaluated.

  • node id: `foo evaluates to the node with id foo in the document.
  • parameter keys: ` evaluates to (the value of) parameter bar of node foo in the document. ` works as expected if is a node.
  • children and parents: `foo[1] and `foo.1 both evaluates to the child of (the node with id) foo at index 1 (i.e., the second child). `foo.1.0 is foo's second child's first child. `foo.parent is the parent of foo.
  • function calls and operations: Function calls foo(`bar, 3 + `baz) work as in Python.

If doc is a persistent_doc.document.Document, doc['foo.parent.3.2'] gives foo's parent's fourth child's second child. Function calls and operations cannot be used with Document.__getitem__ (instead use them outside, in Python f(doc['foo.p1'], doc['bar.p1'])).

Formula reevaluation

There are three reevaluation strategies

  • cached (default): The formula is reevaluated when a term it depends on changes. The result is cached for reads.
  • reeval: The formula is reevaluated every time it is read.
  • on first read: The formula is reevaluated the first time it is read after one of the terms it depends on has changed. The result is cached for reads.

The calc parameter is passed to Ex to indicate which one to use. For example Ex(`foo + 3, calc="reeval"). It is thus possible to have a document with mixed reevaluation strategies.

Expr objects

To get the object for a formula instead of its value, use doc.get_expr('') instead of doc[''].

Errors and debugging

Expressions that produce an error when evaluated will return an EvalError object instead of raising an error.


Run python


Because the document is persistent, pointers to values in the document can become stale. Use doc.m or node.L (instead of doc and node) to use the latest version.



Because parent-child relations are encoded as lookups, its not possible to create a new subtree of Nodes "in the void" and then hook it up to existing nodes. It needs at least a doc (memory) to be created. So default_doc helps with that part.

If there's only one document, persistent_doc.document.default_doc should be set to that.


Parent sets the child's .parent.


numpy isn't really a requirement but since numpy 1.13, equality test behave differently and some of the polymorphism doesn't work otherwise. contains an alternate definition of equal that can be used if there are no numpy arrays as values.

mutable values

Mutable values are expected not to be mutated. They should instead be replaced.

doc['foo.arr'] = numpy.array([1, 2])
doc['foo.arr'] = doc['foo.arr'] + numpy.array([1, 1])

instead of

arr = numpy.array([1, 2])
doc['foo.arr'] = arr
arr += numpy.array([1, 1])


  • Find something better than all the explicit type checking with Ex and Expr.
  • Find a way to automatically decide if a node needs to be replaced by its latest version before an operation. Maybe by comparing timestamps?


An XML-like document with spreadsheet formulas for values and underlying persistent data structures






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