forked from VimPlug/jedi
146 lines
4.1 KiB
Python
146 lines
4.1 KiB
Python
from jedi._compatibility import Python3Method
|
|
from jedi.common import unite
|
|
|
|
|
|
class Context(object):
|
|
api_type = None
|
|
"""
|
|
To be defined by subclasses.
|
|
"""
|
|
predefined_names = {}
|
|
|
|
def __init__(self, evaluator, parent_context=None):
|
|
self.evaluator = evaluator
|
|
self.parent_context = parent_context
|
|
|
|
def get_node(self):
|
|
return None
|
|
|
|
def get_parent_flow_context(self):
|
|
return self.parent_context
|
|
|
|
def get_root_context(self):
|
|
context = self
|
|
while True:
|
|
if context.parent_context is None:
|
|
return context
|
|
context = context.parent_context
|
|
|
|
def execute(self, arguments):
|
|
return self.evaluator.execute(self, arguments)
|
|
|
|
def execute_evaluated(self, *value_list):
|
|
"""
|
|
Execute a function with already executed arguments.
|
|
"""
|
|
from jedi.evaluate.param import ValuesArguments
|
|
arguments = ValuesArguments([[value] for value in value_list])
|
|
return self.execute(arguments)
|
|
|
|
def eval_node(self, node):
|
|
return self.evaluator.eval_element(self, node)
|
|
|
|
def eval_stmt(self, stmt, seek_name=None):
|
|
return self.evaluator.eval_statement(self, stmt, seek_name)
|
|
|
|
@Python3Method
|
|
def eval_trailer(self, types, trailer):
|
|
return self.evaluator.eval_trailer(self, types, trailer)
|
|
|
|
@Python3Method
|
|
def py__getattribute__(self, name_or_str, name_context=None, position=None,
|
|
search_global=False, is_goto=False):
|
|
if name_context is None:
|
|
name_context = self
|
|
return self.evaluator.find_types(
|
|
self, name_or_str, name_context, position, search_global, is_goto)
|
|
|
|
def create_context(self, node, node_is_context=False, node_is_object=False):
|
|
return self.evaluator.create_context(self, node, node_is_context, node_is_object)
|
|
|
|
def is_class(self):
|
|
return False
|
|
|
|
def py__bool__(self):
|
|
"""
|
|
Since Wrapper is a super class for classes, functions and modules,
|
|
the return value will always be true.
|
|
"""
|
|
return True
|
|
|
|
|
|
class TreeContext(Context):
|
|
def __init__(self, evaluator, parent_context=None):
|
|
super(TreeContext, self).__init__(evaluator, parent_context)
|
|
self.predefined_names = {}
|
|
|
|
def __repr__(self):
|
|
return '<%s: %s>' % (self.__class__.__name__, self.get_node())
|
|
|
|
|
|
class FlowContext(TreeContext):
|
|
def get_parent_flow_context(self):
|
|
if 1:
|
|
return self.parent_context
|
|
|
|
|
|
class AbstractLazyContext(object):
|
|
def __init__(self, data):
|
|
self.data = data
|
|
|
|
def __repr__(self):
|
|
return '<%s: %s>' % (self.__class__.__name__, self.data)
|
|
|
|
def infer(self):
|
|
raise NotImplementedError
|
|
|
|
|
|
class LazyKnownContext(AbstractLazyContext):
|
|
"""data is a context."""
|
|
def infer(self):
|
|
return set([self.data])
|
|
|
|
|
|
class LazyKnownContexts(AbstractLazyContext):
|
|
"""data is a set of contexts."""
|
|
def infer(self):
|
|
return self.data
|
|
|
|
|
|
class LazyUnknownContext(AbstractLazyContext):
|
|
def __init__(self):
|
|
super(LazyUnknownContext, self).__init__(None)
|
|
|
|
def infer(self):
|
|
return set()
|
|
|
|
|
|
class LazyTreeContext(AbstractLazyContext):
|
|
def __init__(self, context, node):
|
|
super(LazyTreeContext, self).__init__(node)
|
|
self._context = context
|
|
# We need to save the predefined names. It's an unfortunate side effect
|
|
# that needs to be tracked otherwise results will be wrong.
|
|
self._predefined_names = dict(context.predefined_names)
|
|
|
|
def infer(self):
|
|
old, self._context.predefined_names = \
|
|
self._context.predefined_names, self._predefined_names
|
|
try:
|
|
return self._context.eval_node(self.data)
|
|
finally:
|
|
self._context.predefined_names = old
|
|
|
|
|
|
def get_merged_lazy_context(lazy_contexts):
|
|
if len(lazy_contexts) > 1:
|
|
return MergedLazyContexts(lazy_contexts)
|
|
else:
|
|
return lazy_contexts[0]
|
|
|
|
|
|
class MergedLazyContexts(AbstractLazyContext):
|
|
"""data is a list of lazy contexts."""
|
|
def infer(self):
|
|
return unite(l.infer() for l in self.data)
|