def parse(text):
text = drop_c_comments(text)
text, comments, trailing_comments = extract_comments(text)
lexer = Lexer()
parser = Parser(comments, trailing_comments)
result = parser.parse(lexer.tokenize(text))
return result
def parse(
text: str,
cells: Optional[Index] = None,
surfaces: Optional[Index] = None,
transformations: Optional[Index] = None,
compositions: Optional[Index] = None,
) -> Body:
cells, surfaces, transformations, compositions = map(
lambda x: x[1]() if x[0] is None else x[0],
zip(
[cells, surfaces, transformations, compositions],
[
CellStrictIndex,
SurfaceStrictIndex,
TransformationStrictIndex,
CompositionStrictIndex,
],
),
)
original = text
text = pu.drop_c_comments(text)
text, comments, trailing_comments = pu.extract_comments(text)
lexer = Lexer()
parser = Parser(
cells,
surfaces,
transformations,
compositions,
comments,
trailing_comments,
original,
)
result = parser.parse(lexer.tokenize(text))
return result
def test_extract_comments(text, expected_new_text, expected_comments,
expected_trailing_comment):
actual_new_text, actual_comments, actual_trailing_comment = m.extract_comments(
text)
assert actual_new_text == expected_new_text
assert actual_comments == expected_comments
assert actual_trailing_comment == expected_trailing_comment
def parse(text: str) -> Transformation:
text = drop_c_comments(text)
text, comments, trailing_comments = extract_comments(text)
lexer = Lexer()
parser = Parser()
result: Transformation = parser.parse(lexer.tokenize(text))
if trailing_comments:
result.options["comment"] = trailing_comments
return result
def parse(text: str, transformations: Optional[Index] = None) -> Surface:
if transformations is None:
transformations = TransformationStrictIndex()
else:
assert isinstance(transformations, Index)
text = drop_c_comments(text)
text, comments, trailing_comments = extract_comments(text)
lexer = Lexer()
parser = Parser(transformations)
result = parser.parse(lexer.tokenize(text))
if trailing_comments:
result.options["comment"] = trailing_comments
return result