Both algorithms are written in Python and can be used interchangably with the same grammar (aside for algorithmic restrictions). See "Comparison to other parsers" for more details.
Lark can automagically build an AST from your grammar, without any more code on your part.
## Lark does things a little differently
1.*Separates code from grammar*: The result is parsers that are cleaner and easier to read & work with.
2.*Automatically builds a tree (AST)*: Trees are always simpler to work with than state-machines. (But if you want to provide a callback for efficiency reasons, Lark lets you do that too)
3.*Follows Python's Idioms*: Beautiful is better than ugly. Readability counts.
(*LOC measures lines of code of the parsing algorithm(s), without accompanying files*)
It's hard to compare parsers with different parsing algorithms, since each algorithm has many advantages and disadvantages. However, I will try to summarize the main points here:
- **Earley**: The most powerful context-free algorithm. It can parse all context-free grammars, and it's Big-O efficient. But, its constant-time performance is slow.
- **LALR(1)**: The fastest, most efficient algorithm. It runs at O(n) and uses the least amount of memory. But while it can parse most programming languages, there are many grammars it can't handle.
- **PEG**: A powerful algorithm that can parse all deterministic context-free grammars\* at O(n). But, it hides ambiguity, and takes a lot of memory to run.
- **Recursive-Descent**: Fast for simple grammars, and simple to implement. But poor in Big-O complexity.
Lark offers both Earley and LALR(1), which means you can choose between the most powerful and the most efficient algorithms, without having to change libraries.
(\* *According to Wikipedia, it remains unanswered whether PEGs can really parse all deterministic CFGs*)