def _threaded_complete_all(self, doc_uri, line, col, monitor: IMonitor):
from robotframework_ls.impl import section_name_completions
from robotframework_ls.impl import keyword_completions
from robotframework_ls.impl import variable_completions
from robotframework_ls.impl import filesystem_section_completions
from robotframework_ls.impl import keyword_parameter_completions
completion_context = self._create_completion_context(
doc_uri, line, col, monitor)
if completion_context is None:
return []
ret = section_name_completions.complete(completion_context)
if not ret:
ret.extend(
filesystem_section_completions.complete(completion_context))
if not ret:
ret.extend(keyword_completions.complete(completion_context))
if not ret:
ret.extend(variable_completions.complete(completion_context))
if not ret:
ret.extend(
keyword_parameter_completions.complete(completion_context))
return ret
def _threaded_complete_all(self, doc_uri, line, col, monitor: IMonitor):
from robotframework_ls.impl import section_name_completions
from robotframework_ls.impl import keyword_completions
from robotframework_ls.impl import variable_completions
from robotframework_ls.impl import filesystem_section_completions
from robotframework_ls.impl import keyword_parameter_completions
from robotframework_ls.impl import auto_import_completions
from robotframework_ls.impl.collect_keywords import (
collect_keyword_name_to_keyword_found,
)
from robotframework_ls.impl import ast_utils
completion_context = self._create_completion_context(
doc_uri, line, col, monitor
)
if completion_context is None:
return []
ret = section_name_completions.complete(completion_context)
if not ret:
ret.extend(filesystem_section_completions.complete(completion_context))
if not ret:
token_info = completion_context.get_current_token()
if token_info is not None:
token = ast_utils.get_keyword_name_token(
token_info.node, token_info.token
)
if token is not None:
keyword_name_to_keyword_found: Dict[
str, List[IKeywordFound]
] = collect_keyword_name_to_keyword_found(completion_context)
ret.extend(keyword_completions.complete(completion_context))
ret.extend(
auto_import_completions.complete(
completion_context, keyword_name_to_keyword_found
)
)
return ret
if not ret:
ret.extend(variable_completions.complete(completion_context))
if not ret:
ret.extend(keyword_parameter_completions.complete(completion_context))
return ret
def _complete_from_completion_context(self, completion_context):
from robotframework_ls.impl import section_name_completions
from robotframework_ls.impl import keyword_completions
from robotframework_ls.impl import variable_completions
from robotframework_ls.impl import dictionary_completions
from robotframework_ls.impl import filesystem_section_completions
from robotframework_ls.impl import keyword_parameter_completions
from robotframework_ls.impl import auto_import_completions
from robotframework_ls.impl.collect_keywords import (
collect_keyword_name_to_keyword_found,
)
from robotframework_ls.impl import ast_utils
ret = section_name_completions.complete(completion_context)
if not ret:
ret.extend(filesystem_section_completions.complete(completion_context))
if not ret:
token_info = completion_context.get_current_token()
if token_info is not None:
token = ast_utils.get_keyword_name_token(
token_info.node, token_info.token
)
if token is not None:
keyword_name_to_keyword_found: Dict[
str, List[IKeywordFound]
] = collect_keyword_name_to_keyword_found(completion_context)
ret.extend(keyword_completions.complete(completion_context))
ret.extend(
auto_import_completions.complete(
completion_context, keyword_name_to_keyword_found
)
)
return ret
if not ret:
ret.extend(variable_completions.complete(completion_context))
if not ret:
ret.extend(dictionary_completions.complete(completion_context))
if not ret:
ret.extend(keyword_parameter_completions.complete(completion_context))
return ret
def check_func(source, col_delta=0, expect_completions=True):
from robotframework_ls.impl.completion_context import CompletionContext
from robotframework_ls.impl import keyword_parameter_completions
workspace.set_root("case2", libspec_manager=libspec_manager)
doc = workspace.get_doc("case2.robot")
doc.source = source
line, col = doc.get_last_line_col()
col += col_delta
completions = keyword_parameter_completions.complete(
CompletionContext(doc, workspace=workspace.ws, line=line, col=col))
if expect_completions:
data_regression.check(completions)
else:
assert not completions