def _analysis(self):
self._inference_state.is_analysis = True
self._inference_state.analysis_modules = [self._module_node]
module = self._get_module_context()
try:
for node in get_executable_nodes(self._module_node):
context = module.create_context(node)
if node.type in ('funcdef', 'classdef'):
# Resolve the decorators.
tree_name_to_values(self._inference_state, context, node.children[1])
elif isinstance(node, tree.Import):
import_names = set(node.get_defined_names())
if node.is_nested():
import_names |= set(path[-1] for path in node.get_paths())
for n in import_names:
imports.infer_import(context, n)
elif node.type == 'expr_stmt':
types = context.infer_node(node)
for testlist in node.children[:-1:2]:
# Iterate tuples.
unpack_tuple_to_dict(context, types, testlist)
else:
if node.type == 'name':
defs = self._inference_state.infer(context, node)
else:
defs = infer_call_of_leaf(context, node)
try_iter_content(defs)
self._inference_state.reset_recursion_limitations()
ana = [a for a in self._inference_state.analysis if self.path == a.path]
return sorted(set(ana), key=lambda x: x.line)
finally:
self._inference_state.is_analysis = False
def infer(self, context, name):
def_ = name.get_definition(import_name_always=True)
if def_ is not None:
type_ = def_.type
is_classdef = type_ == 'classdef'
if is_classdef or type_ == 'funcdef':
if is_classdef:
c = ClassValue(self, context, name.parent)
else:
c = FunctionValue.from_context(context, name.parent)
return ValueSet([c])
if type_ == 'expr_stmt':
is_simple_name = name.parent.type not in ('power', 'trailer')
if is_simple_name:
return infer_expr_stmt(context, def_, name)
if type_ == 'for_stmt':
container_types = context.infer_node(def_.children[3])
cn = ContextualizedNode(context, def_.children[3])
for_types = iterate_values(container_types, cn)
n = TreeNameDefinition(context, name)
return check_tuple_assignments(n, for_types)
if type_ in ('import_from', 'import_name'):
return imports.infer_import(context, name)
if type_ == 'with_stmt':
return tree_name_to_values(self, context, name)
elif type_ == 'param':
return context.py__getattribute__(name.value,
position=name.end_pos)
else:
result = follow_error_node_imports_if_possible(context, name)
if result is not None:
return result
return helpers.infer_call_of_leaf(context, name)
def infer(self):
# Refactor this, should probably be here.
from jedi.inference.syntax_tree import tree_name_to_values
return tree_name_to_values(
self.parent_context.inference_state,
self.parent_context,
self.tree_name
)
def infer(self):
# We're using a different value to infer, so we cannot call super().
from jedi.inference.syntax_tree import tree_name_to_values
inferred = tree_name_to_values(
self.parent_context.inference_state, self.parent_context, self.tree_name)
for result_value in inferred:
if self._apply_decorators:
for c in result_value.py__get__(instance=None, class_value=self._class_value):
yield c
else:
yield result_value
