Lark is a parsing toolkit for Python, built with a focus on ergonomics, performance and modularity.
Lark can parse all context-free languages. To put it simply, it means that it is capable of parsing almost any programming language out there, and to some degree most natural languages too.
Who is it for?
Beginners: Lark is very friendly for experimentation. It can parse any grammar you throw at it, no matter how complicated or ambiguous, and do so efficiently. It also constructs an annotated parse-tree for you, using only the grammar and an input, and it gives you convienient and flexible tools to process that parse-tree.
Experts: Lark implements both Earley(SPPF) and LALR(1), and several different lexers, so you can trade-off power and speed, according to your requirements. It also provides a variety of sophisticated features and utilities.
What can it do?
And many more features. Read ahead and find out!
Most importantly, Lark will save you time and prevent you from getting parsing headaches.
$ pip install lark-parser --upgrade
Lark has no dependencies.
Lark provides syntax highlighting for its grammar files (*.lark):
Here is a little program to parse "Hello, World!" (Or any other similar phrase):
from lark import Lark l = Lark('''start: WORD "," WORD "!" %import common.WORD // imports from terminal library %ignore " " // Disregard spaces in text ''') print( l.parse("Hello, World!") )
And the output is:
Tree(start, [Token(WORD, 'Hello'), Token(WORD, 'World')])
Notice punctuation doesn't appear in the resulting tree. It's automatically filtered away by Lark.
Lark is great at handling ambiguity. Here is the result of parsing the phrase "fruit flies like bananas":
See the full list of features here
Lark is the fastest and lightest (lower is better)
Check out the JSON tutorial for more details on how the comparison was made.
Note: I really wanted to add PLY to the benchmark, but I couldn't find a working JSON parser anywhere written in PLY. If anyone can point me to one that actually works, I would be happy to add it!
Note 2: The parsimonious code has been optimized for this specific test, unlike the other benchmarks (Lark included). Its "real-world" performance may not be as good.
|Library||Algorithm||Grammar||Builds tree?||Supports ambiguity?||Can handle every CFG?||Line/Column tracking||Generates Stand-alone|
|Lark||Earley/LALR(1)||EBNF||Yes!||Yes!||Yes!||Yes!||Yes! (LALR only)|
(* PEGs cannot handle non-deterministic grammars. Also, according to Wikipedia, it remains unanswered whether PEGs can really parse all deterministic CFGs)
Using Lark? Send me a message and I'll add your project!
Lark uses the MIT license.
(The standalone tool is under MPL2)
Lark is currently accepting pull-requests. See How to develop Lark
If you like Lark, and want to see it grow, please consider sponsoring us!
Questions about code are best asked on gitter or in the issues.
For anything else, I can be reached by email at erezshin at gmail com.