Metadata-Version: 2.1
Name: textmate-grammar-python
Version: 0.1.1
Summary: An interpreter for grammar files as defined by TextMate and used in VSCode, implemented in Python. TextMate grammars use the oniguruma dialect (https://github.com/kkos/oniguruma). Supports loading grammar files from JSON, PLIST, or YAML format.
Home-page: https://github.com/watermarkhu/textmate-grammar-python
License: MIT
Keywords: textmate,tokenization
Author: Mark Shui Hu
Author-email: watermarkhu@gmail.com
Requires-Python: >=3.11,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: PyYAML (>=6.0.1,<7.0.0)
Requires-Dist: onigurumacffi (>=1.3.0,<2.0.0)
Project-URL: Repository, https://github.com/watermarkhu/textmate-grammar-python
Description-Content-Type: text/markdown

# textmate-grammar-python

An interpreter for grammar files as defined by TextMate and used in VSCode, implemented in Python. TextMate grammars use the oniguruma dialect (https://github.com/kkos/oniguruma). Supports loading grammar files from JSON, PLIST, or YAML format. 


## Usage
Install the module using `pip install textmate-grammar-python`.

Before tokenization is possible, a `LanguageParser` needs to be initialized using a loaded grammar. 

```python
from textmate_grammar.language import LanguageParser
from textmate_grammar.grammars import matlab
parser = LanguageParser(matlab.GRAMMAR)
```

After this, one can either choose to call `parser.parsing_string` to parse a input string directly, or call `parser.parse_file` with the path to the appropiate source file as the first argument, such as the the example `example.py`. 

The parsed `element` object can be displayed directly by calling the `print` method. By default the element is printed as an element tree in a dictionary format. 

```python
>>> element = parser.parse_string("value = num2str(10);")
>>> element.print()

{'token': 'source.matlab',
 'children': [{'token': 'meta.assignment.variable.single.matlab', 
               'children': [{'token': 'variable.other.readwrite.matlab', 'content': 'value'}]},
              {'token': 'keyword.operator.assignment.matlab', 'content': '='},
              {'token': 'meta.function-call.parens.matlab',
               'begin': [{'token': 'entity.name.function.matlab', 'content': 'num2str'},
                         {'token': 'punctuation.section.parens.begin.matlab', 'content': '('}],
               'end': [{'token': 'punctuation.section.parens.end.matlab', 'content': ')'}],
               'children': [{'token': 'constant.numeric.decimal.matlab', 'content': '10'}]},
              {'token': 'punctuation.terminator.semicolon.matlab', 'content': ';'}]}

```
Alternatively, with the keyword argument `flatten` the element is displayed as a list per unique token. Here the first item in the list is the starting position (line, column) of the unique tokenized element. 

```python
>>> element.print(flatten=True)

[[(0, 0), 'value', ['source.matlab', 'meta.assignment.variable.single.matlab', 'variable.other.readwrite.matlab']],
 [(0, 5), ' ', ['source.matlab']],
 [(0, 6), '=', ['source.matlab', 'keyword.operator.assignment.matlab']],
 [(0, 7), ' ', ['source.matlab']],
 [(0, 8), 'num2str', ['source.matlab', 'meta.function-call.parens.matlab', 'entity.name.function.matlab']],
 [(0, 15), '(', ['source.matlab', 'meta.function-call.parens.matlab', 'punctuation.section.parens.begin.matlab']],
 [(0, 16), '10', ['source.matlab', 'meta.function-call.parens.matlab', 'constant.numeric.decimal.matlab']],
 [(0, 18), ')', ['source.matlab', 'meta.function-call.parens.matlab', 'punctuation.section.parens.end.matlab']],
 [(0, 19), ';', ['source.matlab', 'punctuation.terminator.semicolon.matlab']]]
```

## Supported Languages
- [MATLAB](https://github.com/mathworks/MATLAB-Language-grammar)

## TODO
- Implement Begin/While pattern, required for other grammars.

## Sources
- [Textmate guide](https://www.apeth.com/nonblog/stories/textmatebundle.html)
- [VSCode Syntax Highlighting guide](https://code.visualstudio.com/api/language-extensions/syntax-highlight-guide)
- [vscode-textmate](https://github.com/microsoft/vscode-textmate)
- [Macromates texmate](https://macromates.com/textmate/manual/)


## Development

Install the repository after cloning with [poetry](https://python-poetry.org/)

```bash
> pip install poetry
> cd textmate-grammar-python
> poetry install
```

Setup nodejs dependencies in the regression testing folder.
```bash
> cd test/regression
> bash install.js
```

Run all tests in main test directory
```bash
> cd ..
> pytest

====================== test session starts =====================
platform linux -- Python 3.11.4, pytest-7.4.0, pluggy-1.2.0
rootdir: /home/watermarkhu/repositories/sphinx-matlab/test
plugins: icdiff-0.8
...
```


