rana-cli/wakatime/packages/pygments/lexers/special.py
2017-02-13 23:25:51 -08:00

103 lines
3.1 KiB
Python

# -*- coding: utf-8 -*-
"""
pygments.lexers.special
~~~~~~~~~~~~~~~~~~~~~~~
Special lexers.
:copyright: Copyright 2006-2017 by the Pygments team, see AUTHORS.
:license: BSD, see LICENSE for details.
"""
import re
from pygments.lexer import Lexer
from pygments.token import Token, Error, Text
from pygments.util import get_choice_opt, text_type, BytesIO
__all__ = ['TextLexer', 'RawTokenLexer']
class TextLexer(Lexer):
"""
"Null" lexer, doesn't highlight anything.
"""
name = 'Text only'
aliases = ['text']
filenames = ['*.txt']
mimetypes = ['text/plain']
priority = 0.01
def get_tokens_unprocessed(self, text):
yield 0, Text, text
def analyse_text(text):
return TextLexer.priority
_ttype_cache = {}
line_re = re.compile(b'.*?\n')
class RawTokenLexer(Lexer):
"""
Recreate a token stream formatted with the `RawTokenFormatter`. This
lexer raises exceptions during parsing if the token stream in the
file is malformed.
Additional options accepted:
`compress`
If set to ``"gz"`` or ``"bz2"``, decompress the token stream with
the given compression algorithm before lexing (default: ``""``).
"""
name = 'Raw token data'
aliases = ['raw']
filenames = []
mimetypes = ['application/x-pygments-tokens']
def __init__(self, **options):
self.compress = get_choice_opt(options, 'compress',
['', 'none', 'gz', 'bz2'], '')
Lexer.__init__(self, **options)
def get_tokens(self, text):
if isinstance(text, text_type):
# raw token stream never has any non-ASCII characters
text = text.encode('ascii')
if self.compress == 'gz':
import gzip
gzipfile = gzip.GzipFile('', 'rb', 9, BytesIO(text))
text = gzipfile.read()
elif self.compress == 'bz2':
import bz2
text = bz2.decompress(text)
# do not call Lexer.get_tokens() because we do not want Unicode
# decoding to occur, and stripping is not optional.
text = text.strip(b'\n') + b'\n'
for i, t, v in self.get_tokens_unprocessed(text):
yield t, v
def get_tokens_unprocessed(self, text):
length = 0
for match in line_re.finditer(text):
try:
ttypestr, val = match.group().split(b'\t', 1)
except ValueError:
val = match.group().decode('ascii', 'replace')
ttype = Error
else:
ttype = _ttype_cache.get(ttypestr)
if not ttype:
ttype = Token
ttypes = ttypestr.split('.')[1:]
for ttype_ in ttypes:
if not ttype_ or not ttype_[0].isupper():
raise ValueError('malformed token name')
ttype = getattr(ttype, ttype_)
_ttype_cache[ttypestr] = ttype
val = val[2:-2].decode('unicode-escape')
yield length, ttype, val
length += len(val)