Transformer in lark-parser/lark

What the code was meant to do, written into the code itself as a docstring

Transformers work bottom-up (or depth-first), starting with visiting the leaves and working their way up until ending at the root of the tree. For each node visited, the transformer will call the appropriate method (callbacks), according to the node's `data`, and use the returned value to replace the node, thereby creating a new tree structure. Transformers can be used to implement map & reduce patterns. Because nodes are reduced from leaf to root, at any point the callbacks may assume the children have already been transformed (if applicable). If the transformer cannot find a method with the right name, it will instead call `__default__`, which by default creates a copy of the node. To discard a node, return Discard (`lark.visitors.Discard`). `Transformer` can do anything `Visitor` can do, but because it reconstructs the tree, it is slightly less efficient. A transformer without methods essentially performs a non-memoized partial deepcopy. All these classes implement the transformer interface: - `Transformer` - Recursively transforms the tree. This is the one you probably want. - `Transformer_InPlace` - Non-recursive. Changes the tree in-place instead of returning new instances - `Transformer_InPlaceRecursive` - Recursive. Changes the tree in-place instead of returning new instances Parameters: visit_tokens (bool, optional): Should the transformer visit tokens in addition to rules. Setting this to `False` is slightly faster. Defaults to `True`. (For processing ignored tokens, use the `lexer_callbacks` options)

The change

The check that tells the two apart

Check file tests/test_trees.py, taken without changes from the fix and copied onto the older code, so the exact same check runs against both versions.