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Publicize the _evaluator in contexts.

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This commit is contained in:
Dave Halter
2016-11-03 09:54:47 +01:00
parent 63b6fa1416
commit 82667b85b9
9 changed files with 99 additions and 101 deletions
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jedi/evaluate/iterable.py
+24 -24
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@@ -121,18 +121,18 @@ class GeneratorMixin(object):
@memoize_default()
def names_dicts(self, search_global=False): # is always False
gen_obj = compiled.get_special_object(self._evaluator, 'GENERATOR_OBJECT')
gen_obj = compiled.get_special_object(self.evaluator, 'GENERATOR_OBJECT')
yield self._get_names_dict(gen_obj.names_dict)
def get_filters(self, search_global, until_position=None, origin_scope=None):
gen_obj = compiled.get_special_object(self._evaluator, 'GENERATOR_OBJECT')
gen_obj = compiled.get_special_object(self.evaluator, 'GENERATOR_OBJECT')
yield DictFilter(self._get_names_dict(gen_obj.names_dict))
def py__bool__(self):
return True
def py__class__(self):
gen_obj = compiled.get_special_object(self._evaluator, 'GENERATOR_OBJECT')
gen_obj = compiled.get_special_object(self.evaluator, 'GENERATOR_OBJECT')
return gen_obj.py__class__()
@@ -166,7 +166,7 @@ class Comprehension(IterableWrapper):
return cls(evaluator, atom)
def __init__(self, evaluator, atom):
self._evaluator = evaluator
self.evaluator = evaluator
self._atom = atom
def _get_comprehension(self):
@@ -197,7 +197,7 @@ class Comprehension(IterableWrapper):
return helpers.deep_ast_copy(node, parent=last_comp)
def _nested(self, comp_fors):
evaluator = self._evaluator
evaluator = self.evaluator
comp_for = comp_fors[0]
input_node = comp_for.children[3]
input_types = evaluator.eval_element(input_node)
@@ -239,15 +239,15 @@ class ArrayMixin(object):
@memoize_default()
def names_dicts(self, search_global=False): # Always False.
# `array.type` is a string with the type, e.g. 'list'.
scope = compiled.builtin_from_name(self._evaluator, self.type)
scope = compiled.builtin_from_name(self.evaluator, self.type)
# builtins only have one class -> [0]
scopes = self._evaluator.execute_evaluated(scope, self)
scopes = self.evaluator.execute_evaluated(scope, self)
names_dicts = list(scopes)[0].names_dicts(search_global)
yield self._get_names_dict(names_dicts[1])
def get_filters(self, search_global, until_position=None, origin_scope=None):
# `array.type` is a string with the type, e.g. 'list'.
compiled_obj = compiled.builtin_from_name(self._evaluator, self.array_type)
compiled_obj = compiled.builtin_from_name(self.evaluator, self.array_type)
for typ in compiled_obj.execute_evaluated(self):
for filter in typ.get_filters():
yield filter
@@ -258,26 +258,26 @@ class ArrayMixin(object):
return None # We don't know the length, because of appends.
def py__class__(self):
return compiled.builtin_from_name(self._evaluator, self.type)
return compiled.builtin_from_name(self.evaluator, self.type)
@safe_property
def parent(self):
return self._evaluator.BUILTINS
return self.evaluator.BUILTINS
def dict_values(self):
return unite(self._evaluator.eval_element(v) for k, v in self._items())
return unite(self.evaluator.eval_element(v) for k, v in self._items())
@register_builtin_method('values', type='dict')
def _imitate_values(self):
items = self.dict_values()
return create_evaluated_sequence_set(self._evaluator, items, sequence_type='list')
return create_evaluated_sequence_set(self.evaluator, items, sequence_type='list')
@register_builtin_method('items', type='dict')
def _imitate_items(self):
items = [set([FakeSequence(self._evaluator, (k, v), 'tuple')])
items = [set([FakeSequence(self.evaluator, (k, v), 'tuple')])
for k, v in self._items()]
return create_evaluated_sequence_set(self._evaluator, *items, sequence_type='list')
return create_evaluated_sequence_set(self.evaluator, *items, sequence_type='list')
class ListComprehension(Comprehension, ArrayMixin):
@@ -288,7 +288,7 @@ class ListComprehension(Comprehension, ArrayMixin):
result = all_types[index]
if isinstance(index, slice):
return create_evaluated_sequence_set(
self._evaluator,
self.evaluator,
unite(result),
sequence_type='list'
)
@@ -324,11 +324,11 @@ class DictComprehension(Comprehension, ArrayMixin):
@register_builtin_method('items', type='dict')
def _imitate_items(self):
items = set(FakeSequence(self._evaluator,
items = set(FakeSequence(self.evaluator,
(AlreadyEvaluated(keys), AlreadyEvaluated(values)), 'tuple')
for keys, values in self._iterate())
return create_evaluated_sequence_set(self._evaluator, items, sequence_type='list')
return create_evaluated_sequence_set(self.evaluator, items, sequence_type='list')
class GeneratorComprehension(Comprehension, GeneratorMixin):
@@ -391,7 +391,7 @@ class ArrayLiteralContext(ArrayMixin, AbstractSequence):
for node in self._items():
yield context.LazyTreeContext(self._defining_context, node)
additions = check_array_additions(self._evaluator, self)
additions = check_array_additions(self.evaluator, self)
if additions:
yield additions
@@ -447,7 +447,7 @@ class _FakeArray(ArrayLiteralContext):
def __init__(self, evaluator, container, type):
# TODO is this class really needed?
self.array_type = type
self._evaluator = evaluator
self.evaluator = evaluator
self.atom = container
self.parent_context = evaluator.BUILTINS
@@ -519,7 +519,7 @@ class FakeDict(_FakeArray):
def py__iter__(self):
for key in self._dct:
yield context.LazyKnownContext(compiled.create(self._evaluator, key))
yield context.LazyKnownContext(compiled.create(self.evaluator, key))
def py__getitem__(self, index):
return self._dct[index].infer()
@@ -820,7 +820,7 @@ class _ArrayInstance(IterableWrapper):
we don't use these operations in `builtins.py`.
"""
def __init__(self, evaluator, instance):
self._evaluator = evaluator
self.evaluator = evaluator
self.instance = instance
self.var_args = instance.var_args
@@ -831,15 +831,15 @@ class _ArrayInstance(IterableWrapper):
except StopIteration:
types = set()
else:
types = unite(self._evaluator.eval_element(node) for node in first_nodes)
for types in py__iter__(self._evaluator, types, first_nodes[0]):
types = unite(self.evaluator.eval_element(node) for node in first_nodes)
for types in py__iter__(self.evaluator, types, first_nodes[0]):
yield types
module = self.var_args.get_parent_until()
if module is None:
return
is_list = str(self.instance.name) == 'list'
additions = _check_array_additions(self._evaluator, self.instance, module, is_list)
additions = _check_array_additions(self.evaluator, self.instance, module, is_list)
if additions:
yield additions