lark/README.md

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# Lark - a modern parsing library for Python
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Parse any context-free grammar, FAST and EASY!
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**Beginners**: Forget everything you knew about parsers. Lark's algorithm can quickly parse any grammar you throw at it, no matter how complicated. It also constructs a parse-tree for you, without additional code on your part.
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**Experts**: Lark lets you choose between Earley and LALR(1), to trade-off power and speed. It also contains experimental features such as a contextual-lexer.
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Lark can:
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- Parse all context-free grammars, and handle all ambiguity
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- Build a parse-tree automagically, no construction code required
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- Outperform all other Python libraries when using LALR(1) (Yes, including PLY)
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- Run on every Python interpreter (it's pure-python)
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And many more features. Read ahead and find out.
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Most importantly, Lark will save you time and prevent you from getting parsing headaches.
### Quick links
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- [Documentation wiki](https://github.com/erezsh/lark/wiki)
- [Tutorial](/docs/json_tutorial.md) for writing a JSON parser.
- Blog post: [How to write a DSL with Lark](http://blog.erezsh.com/how-to-write-a-dsl-in-python-with-lark/)
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### Install Lark
$ pip install lark-parser
Lark has no dependencies.
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[![Build Status](https://travis-ci.org/erezsh/lark.svg?branch=master)](https://travis-ci.org/erezsh/lark)
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### Hello World
Here is a little program to parse "Hello, World!" (Or any other similar phrase):
```python
from lark import Lark
l = Lark('''start: WORD "," WORD "!"
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%import common.WORD
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%ignore " "
''')
print( l.parse("Hello, World!") )
```
And the output is:
```python
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Tree(start, [Token(WORD, 'Hello'), Token(WORD, 'World')])
```
Notice punctuation doesn't appear in the resulting tree. It's automatically filtered away by Lark.
### Fruit Flies Like Bananas
Lark is very good at handling ambiguity. Here's how it parses the phrase "fruit flies like bananas":
![fruitflies.png](examples/fruitflies.png)
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See more [examples in the wiki](https://github.com/erezsh/lark/wiki/Examples)
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## List of Features
- Builds a parse-tree (AST) automagically, based on the structure of the grammar
- **Earley** parser
- Can parse *ALL* context-free grammars
- Full support for ambiguity in grammar
- **LALR(1)** parser
- Competitive with PLY
- **EBNF** grammar
- **Unicode** fully supported
- **Python 2 & 3** compatible
- Automatic line & column tracking
- Standard library of terminals (strings, numbers, names, etc.)
- Import grammars from Nearley.js
- Extensive test suite [![codecov](https://codecov.io/gh/erezsh/lark/branch/master/graph/badge.svg)](https://codecov.io/gh/erezsh/lark)
- And much more!
See the full list of [features in the wiki](https://github.com/erezsh/lark/wiki/Features)
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### Comparison to other libraries
#### Performance comparison
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| Code | CPython Time | PyPy Time | CPython Mem | PyPy Mem
|:-----|:-------------|:------------|:----------|:---------
| **Lark - LALR(1)** | 4.7s | 1.2s | 70M | 134M |
| PyParsing | 32s | 3.5s | 443M | 225M |
| funcparserlib | 8.5s | 1.3s | 483M | 293M |
| Parsimonious | | 5.7s | | 1545M |
Check out the [JSON tutorial](/docs/json_tutorial.md#conclusion) for more details on how the comparison was made.
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#### Feature comparison
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| Library | Algorithm | Grammar | Builds tree? | Supports ambiguity? | Can handle every CFG?
|:--------|:----------|:----|:--------|:------------|:------------
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| **Lark** | Earley/LALR(1) | EBNF | Yes! | Yes! | Yes! |
| [PLY](http://www.dabeaz.com/ply/) | LALR(1) | BNF | No | No | No |
| [PyParsing](http://pyparsing.wikispaces.com/) | PEG | Combinators | No | No | No\* |
| [Parsley](https://pypi.python.org/pypi/Parsley) | PEG | EBNF | No | No | No\* |
| [funcparserlib](https://github.com/vlasovskikh/funcparserlib) | Recursive-Descent | Combinators | No | No | No |
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| [Parsimonious](https://github.com/erikrose/parsimonious) | PEG | EBNF | Yes | No | No\* |
(\* *According to Wikipedia, it remains unanswered whether PEGs can really parse all deterministic CFGs*)
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### Projects using Lark
- [mappyfile](https://github.com/geographika/mappyfile) - a MapFile parser for working with MapServer configuration
- [pytreeview](https://gitlab.com/parmenti/pytreeview) - a lightweight tree-based grammar explorer
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Using Lark? Send me a message and I'll add your project!
### How to use Nearley grammars in Lark
Lark comes with a tool to convert grammars from [Nearley](https://github.com/Hardmath123/nearley), a popular Earley library for Javascript. It uses [Js2Py](https://github.com/PiotrDabkowski/Js2Py) to convert and run the Javascript postprocessing code segments.
Here's an example:
```bash
git clone https://github.com/Hardmath123/nearley
python -m lark.tools.nearley nearley/examples/calculator/arithmetic.ne main nearley > ncalc.py
```
You can use the output as a regular python module:
```python
>>> import ncalc
>>> ncalc.parse('sin(pi/4) ^ e')
0.38981434460254655
```
## Comparison to other parsers
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### Lark does things a little differently
1. *Separates code from grammar*: Parsers written this way are cleaner and easier to read & work with.
2. *Automatically builds a parse 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.
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### Lark is easier to use
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- You can work with parse-trees instead of state-machines
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- The grammar is simple to read and write
- There are no restrictions on grammar structure. Any grammar you write can be parsed.
- Some structures are faster than others. If you care about speed, you can learn them gradually while the parser is already working
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- A well-written grammar is very fast
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- Note: Nondeterminstic grammars will run a little slower
- Note: Ambiguous grammars (grammars that can be parsed in more than one way) are supported, but may cause significant slowdown if the ambiguity is too big)
- You don't have to worry about terminals (regexps) or rules colliding
- You can repeat expressions without losing efficiency (turns out that's a thing)
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## License
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Lark uses the [MIT license](LICENSE).
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## Contribute
Lark is currently accepting pull-requests.
There are many ways you can help the project:
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* Improve the documentation
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* Write new grammars for Lark's library
* Write a blog post introducing Lark to your audience
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* Port Lark to another language
* Help me with code developemnt
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If you're interested in taking one of these on, let me know and I will provide more details and assist you in the process.
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## Contact
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If you have any questions or want my assistance, you can email me at erezshin at gmail com.
I'm also available for contract work.