This page details the important classes in Lark.
The Lark class is the main interface for the library. It’s mostly a thin wrapper for the many different parsers, and for the tree constructor.
The Lark class accepts a grammar string or file object, and keyword options:
start - The symbol in the grammar that begins the parse (Default: "start"
)
parser - Decides which parser engine to use, “earley”, “lalr” or “cyk”. (Default: "earley"
)
lexer - Overrides default lexer.
transformer - Applies the transformer instead of building a parse tree (only allowed with parser="lalr”)
postlex - Lexer post-processing (Default: None. only works when lexer is “standard” or “contextual”)
ambiguity (only relevant for earley and cyk)
“explicit” - Return all derivations inside an “_ambig” data node.
“resolve” - Let the parser choose the best derivation (greedy for tokens, non-greedy for rules. Default)
debug - Display warnings (such as Shift-Reduce warnings for LALR)
keep_all_tokens - Don’t throw away any terminals from the tree (Default=False)
propagate_positions - Propagate line/column count to tree nodes (default=False)
lexer_callbacks - A dictionary of callbacks of type f(Token) -> Token, used to interface with the lexer Token generation. Only works with the standard and contextual lexers. See Recipes for more information.
Return a complete parse tree for the text (of type Tree)
If a transformer is supplied to __init__
, returns whatever is the result of the transformation.
The main tree class
data
- The name of the rule or aliaschildren
- List of matched sub-rules and terminalsmeta
- Line & Column numbers, if using propagate_positions
Creates a new tree, and stores “data” and “children” in attributes of the same name.
Returns an indented string representation of the tree. Great for debugging.
Returns all nodes of the tree that evaluate pred(node) as true.
Returns all nodes of the tree whose data equals the given data.
Depth-first iteration.
Iterates over all the subtrees, never returning to the same node twice (Lark’s parse-tree is actually a DAG).
Breadth-first iteration.
Iterates over all the subtrees, return nodes in order like pretty() does.
Trees can be hashed and compared.
Returns a pretty string pinpointing the error in the text, with span
amount of context characters around it.
(The parser doesn’t hold a copy of the text it has to parse, so you have to provide it again)
Allows you to detect what’s wrong in the input text by matching against example errors.
Accepts the parse function (usually lark_instance.parse
) and a dictionary of {'example_string': value}
.
The function will iterate the dictionary until it finds a matching error, and return the corresponding value.
For an example usage, see: examples/error_reporting_lalr.py