A lexer and tokenizer for grammar files as defined by TextMate and used in VSCode, implemented in Python.
Project description
textmate-grammar-python
A lexer and tokenizer for grammar files as defined by TextMate and used in VSCode, implemented in Python.
Textmate grammars are made for vscode-texmate, allowing for syntax highlighting in VSCode after tokenization. This presents textmate-grammar-python with a large list of potentially supported languages.
flowchart TD
A[grammar file]
Z[code]
B("`vscode-textmate **js**`")
C("`textmate-grammar-**python**`")
D[tokens]
click C "https://github.com/microsoft/vscode-textmate"
Z --> B
Z --> C
A -.-> B --> D
A -.-> C --> D
Usage
Install the module with:
pip install textmate-grammar-python
Before tokenization is possible, a LanguageParser
needs to be initialized using a loaded grammar.
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 in 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.
>>> 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.
>>> 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']]]
Information
- For further information, please checkout the documentation.
- To setup an environment for development, see CONTRIBUTING.md
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for textmate_grammar_python-0.3.0.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2e07dcfd7c06609442188ea8964f4b07ced43c05577bfdce287b806a5f67e8ee |
|
MD5 | ce2492d5ece62810ff1492d76232c2a6 |
|
BLAKE2b-256 | 5cdc1e0c171cf7ba51672da682145ea32c3acd77d04b81a757b0917bab0978c5 |
Hashes for textmate_grammar_python-0.3.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | bcc90a73eb62c841e2d6e72c6cee3fa386169746227ac2d2bc11741b4ffdcb2d |
|
MD5 | 0b051b001b45d37426c29dae58412e22 |
|
BLAKE2b-256 | 305fdfedcf91e062f29b3c071c581996611c5157aaaa40b37dc0afd258d53c49 |