def ConvertCompletionData(completion_data):
return responses.BuildCompletionData(
insertion_text=completion_data.TextToInsertInBuffer(),
menu_text=completion_data.MainCompletionText(),
extra_menu_info=completion_data.ExtraMenuInfo(),
kind=completion_data.kind_,
detailed_info=completion_data.DetailedInfoForPreviewWindow())
def ComputeCandidatesInner( self, request_data ):
script = self._GetJediScript( request_data )
return [ responses.BuildCompletionData(
str( completion.name ),
str( completion.description ),
str( completion.doc ) )
for completion in script.completions() ]
def ComputeCandidatesInner(self, request_data):
return [
responses.BuildCompletionData(completion['CompletionText'],
completion['DisplayText'],
completion['Description'])
for completion in self._GetCompletions(request_data)
]
def _FindLabels(self):
"""
Find LaTeX labels for \ref{} completion.
This time we scan through all .tex files in the current
directory and extract the content of all \label{} commands
as sources for completion.
"""
texs = " ".join(glob.glob("*.tex"))
cat_process = subprocess.Popen(shlex.split("cat %s" % texs),
stdout=subprocess.PIPE)
grep_process = subprocess.Popen(shlex.split(r"grep \\\\label"),
stdin=cat_process.stdout,
stdout=subprocess.PIPE)
cat_process.stdout.close()
lines = grep_process.communicate()[0]
ret = []
for label in lines.split("\n"):
ret.append(
responses.BuildCompletionData(
re.sub(r".*\label{(.*)}.*", r"\1", label)))
return ret
def OnBufferVisit(self, request_data):
raw_candidates = request_data.get('ultisnips_snippets', [])
self._candidates = [
responses.BuildCompletionData(
str(snip['trigger']),
str('<snip> ' + snip['description'].encode('utf-8')))
for snip in raw_candidates
]
def ComputeCandidates( self, request_data ):
if not self.ShouldUseNow( request_data ):
return []
completions = self._completer.CandidatesForQueryAndType(
ToUtf8IfNeeded( utils.SanitizeQuery( request_data[ 'query' ] ) ),
ToUtf8IfNeeded( request_data[ 'filetypes' ][ 0 ] ) )
completions = completions[ : MAX_IDENTIFIER_COMPLETIONS_RETURNED ]
completions = _RemoveSmallCandidates(
completions, self.user_options[ 'min_num_identifier_candidate_chars' ] )
return [ responses.BuildCompletionData( x ) for x in completions ]
def _GenerateCandidatesForPaths(absolute_paths):
seen_basenames = set()
completion_dicts = []
for absolute_path in absolute_paths:
basename = os.path.basename(absolute_path)
if basename in seen_basenames:
continue
seen_basenames.add(basename)
is_dir = os.path.isdir(absolute_path)
completion_dicts.append(
responses.BuildCompletionData(basename,
'[Dir]' if is_dir else '[File]'))
return completion_dicts
def _FindBibEntries(self):
"""
Find BIBtex entries.
I'm currently assuming, that Bib entries have the format
^@<articletype> {<ID>,
<bibtex properties>
[..]
}
Hence, to find IDs for completion, I scan for lines starting
with an @ character and extract the ID from there.
The search is done by a shell pipe:
cat *.bib | grep ^@ | grep -v @string
"""
# bibs = " ".join(glob.glob("*.bib"))
# cat_process = subprocess.Popen(shlex.split("cat %s" % bibs),
# stdout=subprocess.PIPE)
# grep_process = subprocess.Popen(shlex.split("grep ^@"),
# stdin=cat_process.stdout,
# stdout=subprocess.PIPE)
# cat_process.stdout.close()
# grep2_process = subprocess.Popen(shlex.split("grep -vi @string"),
# stdin=grep_process.stdout,
# stdout=subprocess.PIPE)
# grep_process.stdout.close()
#
# lines = grep2_process.communicate()[0]
#
ret = []
# for l in lines.split("\n"):
# ret.append(responses.BuildCompletionData(
# re.sub(r"@(.*){([^,]*).*", r"\2", l)
# )
# )
regex = re.compile(r"@([A-Za-z]*)\s*{\s*([^,]*),.*")
for bibfile in self._FindBibFiles('/dev/null'):
for key in self._FindBibEntries(bibfile):
ret.append(responses.BuildCompletionData(key))
return ret
