|
""" |
|
Values are the "values" that Python would return. However Values are at the |
|
same time also the "values" that a user is currently sitting in. |
|
|
|
A ValueSet is typically used to specify the return of a function or any other |
|
static analysis operation. In jedi there are always multiple returns and not |
|
just one. |
|
""" |
|
from functools import reduce |
|
from operator import add |
|
from itertools import zip_longest |
|
|
|
from parso.python.tree import Name |
|
|
|
from jedi import debug |
|
from jedi.parser_utils import clean_scope_docstring |
|
from jedi.inference.helpers import SimpleGetItemNotFound |
|
from jedi.inference.utils import safe_property |
|
from jedi.inference.cache import inference_state_as_method_param_cache |
|
from jedi.cache import memoize_method |
|
|
|
sentinel = object() |
|
|
|
|
|
class HasNoContext(Exception): |
|
pass |
|
|
|
|
|
class HelperValueMixin: |
|
def get_root_context(self): |
|
value = self |
|
if value.parent_context is None: |
|
return value.as_context() |
|
|
|
while True: |
|
if value.parent_context is None: |
|
return value |
|
value = value.parent_context |
|
|
|
def execute(self, arguments): |
|
return self.inference_state.execute(self, arguments=arguments) |
|
|
|
def execute_with_values(self, *value_list): |
|
from jedi.inference.arguments import ValuesArguments |
|
arguments = ValuesArguments([ValueSet([value]) for value in value_list]) |
|
return self.inference_state.execute(self, arguments) |
|
|
|
def execute_annotation(self): |
|
return self.execute_with_values() |
|
|
|
def gather_annotation_classes(self): |
|
return ValueSet([self]) |
|
|
|
def merge_types_of_iterate(self, contextualized_node=None, is_async=False): |
|
return ValueSet.from_sets( |
|
lazy_value.infer() |
|
for lazy_value in self.iterate(contextualized_node, is_async) |
|
) |
|
|
|
def _get_value_filters(self, name_or_str): |
|
origin_scope = name_or_str if isinstance(name_or_str, Name) else None |
|
yield from self.get_filters(origin_scope=origin_scope) |
|
|
|
if self.is_stub(): |
|
from jedi.inference.gradual.conversion import convert_values |
|
for c in convert_values(ValueSet({self})): |
|
yield from c.get_filters() |
|
|
|
def goto(self, name_or_str, name_context=None, analysis_errors=True): |
|
from jedi.inference import finder |
|
filters = self._get_value_filters(name_or_str) |
|
names = finder.filter_name(filters, name_or_str) |
|
debug.dbg('context.goto %s in (%s): %s', name_or_str, self, names) |
|
return names |
|
|
|
def py__getattribute__(self, name_or_str, name_context=None, position=None, |
|
analysis_errors=True): |
|
""" |
|
:param position: Position of the last statement -> tuple of line, column |
|
""" |
|
if name_context is None: |
|
name_context = self |
|
names = self.goto(name_or_str, name_context, analysis_errors) |
|
values = ValueSet.from_sets(name.infer() for name in names) |
|
if not values: |
|
n = name_or_str.value if isinstance(name_or_str, Name) else name_or_str |
|
values = self.py__getattribute__alternatives(n) |
|
|
|
if not names and not values and analysis_errors: |
|
if isinstance(name_or_str, Name): |
|
from jedi.inference import analysis |
|
analysis.add_attribute_error( |
|
name_context, self, name_or_str) |
|
debug.dbg('context.names_to_types: %s -> %s', names, values) |
|
return values |
|
|
|
def py__await__(self): |
|
await_value_set = self.py__getattribute__("__await__") |
|
if not await_value_set: |
|
debug.warning('Tried to run __await__ on value %s', self) |
|
return await_value_set.execute_with_values() |
|
|
|
def py__name__(self): |
|
return self.name.string_name |
|
|
|
def iterate(self, contextualized_node=None, is_async=False): |
|
debug.dbg('iterate %s', self) |
|
if is_async: |
|
from jedi.inference.lazy_value import LazyKnownValues |
|
|
|
|
|
return iter([ |
|
LazyKnownValues( |
|
self.py__getattribute__('__aiter__').execute_with_values() |
|
.py__getattribute__('__anext__').execute_with_values() |
|
.py__getattribute__('__await__').execute_with_values() |
|
.py__stop_iteration_returns() |
|
) |
|
]) |
|
return self.py__iter__(contextualized_node) |
|
|
|
def is_sub_class_of(self, class_value): |
|
with debug.increase_indent_cm('subclass matching of %s <=> %s' % (self, class_value), |
|
color='BLUE'): |
|
for cls in self.py__mro__(): |
|
if cls.is_same_class(class_value): |
|
debug.dbg('matched subclass True', color='BLUE') |
|
return True |
|
debug.dbg('matched subclass False', color='BLUE') |
|
return False |
|
|
|
def is_same_class(self, class2): |
|
|
|
if type(class2).is_same_class != HelperValueMixin.is_same_class: |
|
return class2.is_same_class(self) |
|
return self == class2 |
|
|
|
@memoize_method |
|
def as_context(self, *args, **kwargs): |
|
return self._as_context(*args, **kwargs) |
|
|
|
|
|
class Value(HelperValueMixin): |
|
""" |
|
To be implemented by subclasses. |
|
""" |
|
tree_node = None |
|
|
|
|
|
array_type = None |
|
api_type = 'not_defined_please_report_bug' |
|
|
|
def __init__(self, inference_state, parent_context=None): |
|
self.inference_state = inference_state |
|
self.parent_context = parent_context |
|
|
|
def py__getitem__(self, index_value_set, contextualized_node): |
|
from jedi.inference import analysis |
|
|
|
analysis.add( |
|
contextualized_node.context, |
|
'type-error-not-subscriptable', |
|
contextualized_node.node, |
|
message="TypeError: '%s' object is not subscriptable" % self |
|
) |
|
return NO_VALUES |
|
|
|
def py__simple_getitem__(self, index): |
|
raise SimpleGetItemNotFound |
|
|
|
def py__iter__(self, contextualized_node=None): |
|
if contextualized_node is not None: |
|
from jedi.inference import analysis |
|
analysis.add( |
|
contextualized_node.context, |
|
'type-error-not-iterable', |
|
contextualized_node.node, |
|
message="TypeError: '%s' object is not iterable" % self) |
|
return iter([]) |
|
|
|
def py__next__(self, contextualized_node=None): |
|
return self.py__iter__(contextualized_node) |
|
|
|
def get_signatures(self): |
|
return [] |
|
|
|
def is_class(self): |
|
return False |
|
|
|
def is_class_mixin(self): |
|
return False |
|
|
|
def is_instance(self): |
|
return False |
|
|
|
def is_function(self): |
|
return False |
|
|
|
def is_module(self): |
|
return False |
|
|
|
def is_namespace(self): |
|
return False |
|
|
|
def is_compiled(self): |
|
return False |
|
|
|
def is_bound_method(self): |
|
return False |
|
|
|
def is_builtins_module(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 |
|
|
|
def py__doc__(self): |
|
try: |
|
self.tree_node.get_doc_node |
|
except AttributeError: |
|
return '' |
|
else: |
|
return clean_scope_docstring(self.tree_node) |
|
|
|
def get_safe_value(self, default=sentinel): |
|
if default is sentinel: |
|
raise ValueError("There exists no safe value for value %s" % self) |
|
return default |
|
|
|
def execute_operation(self, other, operator): |
|
debug.warning("%s not possible between %s and %s", operator, self, other) |
|
return NO_VALUES |
|
|
|
def py__call__(self, arguments): |
|
debug.warning("no execution possible %s", self) |
|
return NO_VALUES |
|
|
|
def py__stop_iteration_returns(self): |
|
debug.warning("Not possible to return the stop iterations of %s", self) |
|
return NO_VALUES |
|
|
|
def py__getattribute__alternatives(self, name_or_str): |
|
""" |
|
For now a way to add values in cases like __getattr__. |
|
""" |
|
return NO_VALUES |
|
|
|
def py__get__(self, instance, class_value): |
|
debug.warning("No __get__ defined on %s", self) |
|
return ValueSet([self]) |
|
|
|
def py__get__on_class(self, calling_instance, instance, class_value): |
|
return NotImplemented |
|
|
|
def get_qualified_names(self): |
|
|
|
return None |
|
|
|
def is_stub(self): |
|
|
|
return self.parent_context.is_stub() |
|
|
|
def _as_context(self): |
|
raise HasNoContext |
|
|
|
@property |
|
def name(self): |
|
raise NotImplementedError |
|
|
|
def get_type_hint(self, add_class_info=True): |
|
return None |
|
|
|
def infer_type_vars(self, value_set): |
|
""" |
|
When the current instance represents a type annotation, this method |
|
tries to find information about undefined type vars and returns a dict |
|
from type var name to value set. |
|
|
|
This is for example important to understand what `iter([1])` returns. |
|
According to typeshed, `iter` returns an `Iterator[_T]`: |
|
|
|
def iter(iterable: Iterable[_T]) -> Iterator[_T]: ... |
|
|
|
This functions would generate `int` for `_T` in this case, because it |
|
unpacks the `Iterable`. |
|
|
|
Parameters |
|
---------- |
|
|
|
`self`: represents the annotation of the current parameter to infer the |
|
value for. In the above example, this would initially be the |
|
`Iterable[_T]` of the `iterable` parameter and then, when recursing, |
|
just the `_T` generic parameter. |
|
|
|
`value_set`: represents the actual argument passed to the parameter |
|
we're inferred for, or (for recursive calls) their types. In the |
|
above example this would first be the representation of the list |
|
`[1]` and then, when recursing, just of `1`. |
|
""" |
|
return {} |
|
|
|
|
|
def iterate_values(values, contextualized_node=None, is_async=False): |
|
""" |
|
Calls `iterate`, on all values but ignores the ordering and just returns |
|
all values that the iterate functions yield. |
|
""" |
|
return ValueSet.from_sets( |
|
lazy_value.infer() |
|
for lazy_value in values.iterate(contextualized_node, is_async=is_async) |
|
) |
|
|
|
|
|
class _ValueWrapperBase(HelperValueMixin): |
|
@safe_property |
|
def name(self): |
|
from jedi.inference.names import ValueName |
|
wrapped_name = self._wrapped_value.name |
|
if wrapped_name.tree_name is not None: |
|
return ValueName(self, wrapped_name.tree_name) |
|
else: |
|
from jedi.inference.compiled import CompiledValueName |
|
return CompiledValueName(self, wrapped_name.string_name) |
|
|
|
@classmethod |
|
@inference_state_as_method_param_cache() |
|
def create_cached(cls, inference_state, *args, **kwargs): |
|
return cls(*args, **kwargs) |
|
|
|
def __getattr__(self, name): |
|
assert name != '_wrapped_value', 'Problem with _get_wrapped_value' |
|
return getattr(self._wrapped_value, name) |
|
|
|
|
|
class LazyValueWrapper(_ValueWrapperBase): |
|
@safe_property |
|
@memoize_method |
|
def _wrapped_value(self): |
|
with debug.increase_indent_cm('Resolve lazy value wrapper'): |
|
return self._get_wrapped_value() |
|
|
|
def __repr__(self): |
|
return '<%s>' % (self.__class__.__name__) |
|
|
|
def _get_wrapped_value(self): |
|
raise NotImplementedError |
|
|
|
|
|
class ValueWrapper(_ValueWrapperBase): |
|
def __init__(self, wrapped_value): |
|
self._wrapped_value = wrapped_value |
|
|
|
def __repr__(self): |
|
return '%s(%s)' % (self.__class__.__name__, self._wrapped_value) |
|
|
|
|
|
class TreeValue(Value): |
|
def __init__(self, inference_state, parent_context, tree_node): |
|
super().__init__(inference_state, parent_context) |
|
self.tree_node = tree_node |
|
|
|
def __repr__(self): |
|
return '<%s: %s>' % (self.__class__.__name__, self.tree_node) |
|
|
|
|
|
class ContextualizedNode: |
|
def __init__(self, context, node): |
|
self.context = context |
|
self.node = node |
|
|
|
def get_root_context(self): |
|
return self.context.get_root_context() |
|
|
|
def infer(self): |
|
return self.context.infer_node(self.node) |
|
|
|
def __repr__(self): |
|
return '<%s: %s in %s>' % (self.__class__.__name__, self.node, self.context) |
|
|
|
|
|
def _getitem(value, index_values, contextualized_node): |
|
|
|
result = NO_VALUES |
|
unused_values = set() |
|
for index_value in index_values: |
|
index = index_value.get_safe_value(default=None) |
|
if type(index) in (float, int, str, slice, bytes): |
|
try: |
|
result |= value.py__simple_getitem__(index) |
|
continue |
|
except SimpleGetItemNotFound: |
|
pass |
|
|
|
unused_values.add(index_value) |
|
|
|
|
|
|
|
|
|
if unused_values or not index_values: |
|
result |= value.py__getitem__( |
|
ValueSet(unused_values), |
|
contextualized_node |
|
) |
|
debug.dbg('py__getitem__ result: %s', result) |
|
return result |
|
|
|
|
|
class ValueSet: |
|
def __init__(self, iterable): |
|
self._set = frozenset(iterable) |
|
for value in iterable: |
|
assert not isinstance(value, ValueSet) |
|
|
|
@classmethod |
|
def _from_frozen_set(cls, frozenset_): |
|
self = cls.__new__(cls) |
|
self._set = frozenset_ |
|
return self |
|
|
|
@classmethod |
|
def from_sets(cls, sets): |
|
""" |
|
Used to work with an iterable of set. |
|
""" |
|
aggregated = set() |
|
for set_ in sets: |
|
if isinstance(set_, ValueSet): |
|
aggregated |= set_._set |
|
else: |
|
aggregated |= frozenset(set_) |
|
return cls._from_frozen_set(frozenset(aggregated)) |
|
|
|
def __or__(self, other): |
|
return self._from_frozen_set(self._set | other._set) |
|
|
|
def __and__(self, other): |
|
return self._from_frozen_set(self._set & other._set) |
|
|
|
def __iter__(self): |
|
return iter(self._set) |
|
|
|
def __bool__(self): |
|
return bool(self._set) |
|
|
|
def __len__(self): |
|
return len(self._set) |
|
|
|
def __repr__(self): |
|
return 'S{%s}' % (', '.join(str(s) for s in self._set)) |
|
|
|
def filter(self, filter_func): |
|
return self.__class__(filter(filter_func, self._set)) |
|
|
|
def __getattr__(self, name): |
|
def mapper(*args, **kwargs): |
|
return self.from_sets( |
|
getattr(value, name)(*args, **kwargs) |
|
for value in self._set |
|
) |
|
return mapper |
|
|
|
def __eq__(self, other): |
|
return self._set == other._set |
|
|
|
def __ne__(self, other): |
|
return not self.__eq__(other) |
|
|
|
def __hash__(self): |
|
return hash(self._set) |
|
|
|
def py__class__(self): |
|
return ValueSet(c.py__class__() for c in self._set) |
|
|
|
def iterate(self, contextualized_node=None, is_async=False): |
|
from jedi.inference.lazy_value import get_merged_lazy_value |
|
type_iters = [c.iterate(contextualized_node, is_async=is_async) for c in self._set] |
|
for lazy_values in zip_longest(*type_iters): |
|
yield get_merged_lazy_value( |
|
[l for l in lazy_values if l is not None] |
|
) |
|
|
|
def execute(self, arguments): |
|
return ValueSet.from_sets(c.inference_state.execute(c, arguments) for c in self._set) |
|
|
|
def execute_with_values(self, *args, **kwargs): |
|
return ValueSet.from_sets(c.execute_with_values(*args, **kwargs) for c in self._set) |
|
|
|
def goto(self, *args, **kwargs): |
|
return reduce(add, [c.goto(*args, **kwargs) for c in self._set], []) |
|
|
|
def py__getattribute__(self, *args, **kwargs): |
|
return ValueSet.from_sets(c.py__getattribute__(*args, **kwargs) for c in self._set) |
|
|
|
def get_item(self, *args, **kwargs): |
|
return ValueSet.from_sets(_getitem(c, *args, **kwargs) for c in self._set) |
|
|
|
def try_merge(self, function_name): |
|
value_set = self.__class__([]) |
|
for c in self._set: |
|
try: |
|
method = getattr(c, function_name) |
|
except AttributeError: |
|
pass |
|
else: |
|
value_set |= method() |
|
return value_set |
|
|
|
def gather_annotation_classes(self): |
|
return ValueSet.from_sets([c.gather_annotation_classes() for c in self._set]) |
|
|
|
def get_signatures(self): |
|
return [sig for c in self._set for sig in c.get_signatures()] |
|
|
|
def get_type_hint(self, add_class_info=True): |
|
t = [v.get_type_hint(add_class_info=add_class_info) for v in self._set] |
|
type_hints = sorted(filter(None, t)) |
|
if len(type_hints) == 1: |
|
return type_hints[0] |
|
|
|
optional = 'None' in type_hints |
|
if optional: |
|
type_hints.remove('None') |
|
|
|
if len(type_hints) == 0: |
|
return None |
|
elif len(type_hints) == 1: |
|
s = type_hints[0] |
|
else: |
|
s = 'Union[%s]' % ', '.join(type_hints) |
|
if optional: |
|
s = 'Optional[%s]' % s |
|
return s |
|
|
|
def infer_type_vars(self, value_set): |
|
|
|
from jedi.inference.gradual.annotation import merge_type_var_dicts |
|
|
|
type_var_dict = {} |
|
for value in self._set: |
|
merge_type_var_dicts( |
|
type_var_dict, |
|
value.infer_type_vars(value_set), |
|
) |
|
return type_var_dict |
|
|
|
|
|
NO_VALUES = ValueSet([]) |
|
|
|
|
|
def iterator_to_value_set(func): |
|
def wrapper(*args, **kwargs): |
|
return ValueSet(func(*args, **kwargs)) |
|
|
|
return wrapper |
|
|