mirror of
https://github.com/davidhalter/jedi.git
synced 2025-12-06 14:04:26 +08:00
847 lines
29 KiB
Python
847 lines
29 KiB
Python
"""
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Contains all classes and functions to deal with lists, dicts, generators and
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iterators in general.
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Array modifications
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*******************
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If the content of an array (``set``/``list``) is requested somewhere, the
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current module will be checked for appearances of ``arr.append``,
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``arr.insert``, etc. If the ``arr`` name points to an actual array, the
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content will be added
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This can be really cpu intensive, as you can imagine. Because |jedi| has to
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follow **every** ``append`` and check wheter it's the right array. However this
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works pretty good, because in *slow* cases, the recursion detector and other
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settings will stop this process.
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It is important to note that:
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1. Array modfications work only in the current module.
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2. Jedi only checks Array additions; ``list.pop``, etc are ignored.
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"""
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from jedi.common import unite, safe_property
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from jedi import debug
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from jedi import settings
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from jedi._compatibility import use_metaclass, unicode, zip_longest
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from jedi.parser import tree
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from jedi.evaluate import compiled
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from jedi.evaluate import helpers
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from jedi.evaluate.cache import CachedMetaClass, memoize_default
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from jedi.evaluate import analysis
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from jedi.evaluate import pep0484
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class IterableWrapper(tree.Base):
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def is_class(self):
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return False
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@memoize_default()
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def _get_names_dict(self, names_dict):
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builtin_methods = {}
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for cls in reversed(type(self).mro()):
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try:
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builtin_methods.update(cls.builtin_methods)
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except AttributeError:
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pass
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if not builtin_methods:
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return names_dict
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dct = {}
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for names in names_dict.values():
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for name in names:
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name_str = name.value
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try:
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method = builtin_methods[name_str, self.type]
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except KeyError:
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dct[name_str] = [name]
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else:
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parent = BuiltinMethod(self, method, name.parent)
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dct[name_str] = [helpers.FakeName(name_str, parent, is_definition=True)]
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return dct
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class BuiltinMethod(IterableWrapper):
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"""``Generator.__next__`` ``dict.values`` methods and so on."""
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def __init__(self, builtin, method, builtin_func):
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self._builtin = builtin
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self._method = method
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self._builtin_func = builtin_func
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def py__call__(self, params):
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return self._method(self._builtin)
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def __getattr__(self, name):
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return getattr(self._builtin_func, name)
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def has_builtin_methods(cls):
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cls.builtin_methods = {}
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for func in cls.__dict__.values():
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try:
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cls.builtin_methods.update(func.registered_builtin_methods)
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except AttributeError:
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pass
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return cls
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def register_builtin_method(method_name, type=None):
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def wrapper(func):
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dct = func.__dict__.setdefault('registered_builtin_methods', {})
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dct[method_name, type] = func
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return func
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return wrapper
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@has_builtin_methods
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class GeneratorMixin(object):
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type = None
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@register_builtin_method('send')
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@register_builtin_method('next')
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@register_builtin_method('__next__')
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def py__next__(self):
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# TODO add TypeError if params are given.
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return unite(self.py__iter__())
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@memoize_default()
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def names_dicts(self, search_global=False): # is always False
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gen_obj = compiled.get_special_object(self._evaluator, 'GENERATOR_OBJECT')
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yield self._get_names_dict(gen_obj.names_dict)
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def py__bool__(self):
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return True
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def py__class__(self):
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gen_obj = compiled.get_special_object(self._evaluator, 'GENERATOR_OBJECT')
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return gen_obj.py__class__()
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class Generator(use_metaclass(CachedMetaClass, IterableWrapper, GeneratorMixin)):
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"""Handling of `yield` functions."""
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def __init__(self, evaluator, func, var_args):
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super(Generator, self).__init__()
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self._evaluator = evaluator
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self.func = func
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self.var_args = var_args
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def py__iter__(self):
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from jedi.evaluate.representation import FunctionExecution
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f = FunctionExecution(self._evaluator, self.func, self.var_args)
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return f.get_yield_types()
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def __getattr__(self, name):
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if name not in ['start_pos', 'end_pos', 'parent', 'get_imports',
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'doc', 'docstr', 'get_parent_until',
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'get_code', 'subscopes']:
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raise AttributeError("Accessing %s of %s is not allowed."
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% (self, name))
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return getattr(self.func, name)
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def __repr__(self):
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return "<%s of %s>" % (type(self).__name__, self.func)
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class Comprehension(IterableWrapper):
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@staticmethod
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def from_atom(evaluator, atom):
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bracket = atom.children[0]
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if bracket == '{':
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if atom.children[1].children[1] == ':':
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cls = DictComprehension
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else:
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cls = SetComprehension
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elif bracket == '(':
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cls = GeneratorComprehension
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elif bracket == '[':
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cls = ListComprehension
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return cls(evaluator, atom)
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def __init__(self, evaluator, atom):
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self._evaluator = evaluator
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self._atom = atom
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def _get_comprehension(self):
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# The atom contains a testlist_comp
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return self._atom.children[1]
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def _get_comp_for(self):
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# The atom contains a testlist_comp
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return self._get_comprehension().children[1]
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@memoize_default()
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def _eval_node(self, index=0):
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"""
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The first part `x + 1` of the list comprehension:
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[x + 1 for x in foo]
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"""
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comp_for = self._get_comp_for()
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# For nested comprehensions we need to search the last one.
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last_comp = list(comp_for.get_comp_fors())[-1]
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return helpers.deep_ast_copy(self._get_comprehension().children[index], parent=last_comp)
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@memoize_default()
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def _iterate(self):
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def nested(comp_fors):
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comp_for = comp_fors[0]
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input_node = comp_for.children[3]
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input_types = evaluator.eval_element(input_node)
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iterated = py__iter__(evaluator, input_types, input_node)
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exprlist = comp_for.children[1]
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for types in iterated:
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evaluator.predefined_if_name_dict_dict[comp_for] = \
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unpack_tuple_to_dict(evaluator, types, exprlist)
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try:
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for result in nested(comp_fors[1:]):
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yield result
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except IndexError:
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iterated = evaluator.eval_element(self._eval_node())
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if self.type == 'dict':
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yield iterated, evaluator.eval_element(self._eval_node(2))
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else:
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yield iterated
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finally:
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del evaluator.predefined_if_name_dict_dict[comp_for]
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evaluator = self._evaluator
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comp_fors = list(self._get_comp_for().get_comp_fors())
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for result in nested(comp_fors):
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yield result
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def py__iter__(self):
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return self._iterate()
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def __repr__(self):
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return "<%s of %s>" % (type(self).__name__, self._atom)
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@has_builtin_methods
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class ArrayMixin(object):
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@memoize_default()
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def names_dicts(self, search_global=False): # Always False.
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# `array.type` is a string with the type, e.g. 'list'.
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scope = compiled.builtin_from_name(self._evaluator, self.type)
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# builtins only have one class -> [0]
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scopes = self._evaluator.execute_evaluated(scope, self)
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names_dicts = list(scopes)[0].names_dicts(search_global)
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#yield names_dicts[0]
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yield self._get_names_dict(names_dicts[1])
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def py__bool__(self):
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return None # We don't know the length, because of appends.
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def py__class__(self):
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return compiled.builtin_from_name(self._evaluator, self.type)
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@safe_property
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def parent(self):
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return self._evaluator.BUILTINS
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@property
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def name(self):
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return FakeSequence(self._evaluator, [], self.type).name
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@memoize_default()
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def dict_values(self):
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return unite(self._evaluator.eval_element(v) for k, v in self._items())
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@register_builtin_method('values', type='dict')
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def _imitate_values(self):
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items = self.dict_values()
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return create_evaluated_sequence_set(self._evaluator, items, type='list')
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#return set([FakeSequence(self._evaluator, [AlreadyEvaluated(items)], 'tuple')])
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@register_builtin_method('items', type='dict')
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def _imitate_items(self):
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items = [set([FakeSequence(self._evaluator, (k, v), 'tuple')])
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for k, v in self._items()]
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return create_evaluated_sequence_set(self._evaluator, *items, type='list')
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class ListComprehension(Comprehension, ArrayMixin):
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type = 'list'
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def py__getitem__(self, index):
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all_types = list(self.py__iter__())
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return all_types[index]
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class SetComprehension(Comprehension, ArrayMixin):
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type = 'set'
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@has_builtin_methods
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class DictComprehension(Comprehension, ArrayMixin):
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type = 'dict'
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def _get_comp_for(self):
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return self._get_comprehension().children[3]
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def py__iter__(self):
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for keys, values in self._iterate():
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yield keys
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def py__getitem__(self, index):
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for keys, values in self._iterate():
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for k in keys:
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if isinstance(k, compiled.CompiledObject):
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if k.obj == index:
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return values
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return self.dict_values()
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def dict_values(self):
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return unite(values for keys, values in self._iterate())
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@register_builtin_method('items', type='dict')
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def _imitate_items(self):
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items = set(FakeSequence(self._evaluator,
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(AlreadyEvaluated(keys), AlreadyEvaluated(values)), 'tuple')
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for keys, values in self._iterate())
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return create_evaluated_sequence_set(self._evaluator, items, type='list')
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class GeneratorComprehension(Comprehension, GeneratorMixin):
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pass
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class Array(IterableWrapper, ArrayMixin):
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mapping = {'(': 'tuple',
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'[': 'list',
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'{': 'dict'}
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def __init__(self, evaluator, atom):
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self._evaluator = evaluator
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self.atom = atom
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self.type = Array.mapping[atom.children[0]]
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"""The builtin name of the array (list, set, tuple or dict)."""
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c = self.atom.children
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array_node = c[1]
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if self.type == 'dict' and array_node != '}' \
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and (not hasattr(array_node, 'children')
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or ':' not in array_node.children):
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self.type = 'set'
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@property
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def name(self):
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return helpers.FakeName(self.type, parent=self)
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def py__getitem__(self, index):
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"""Here the index is an int/str. Raises IndexError/KeyError."""
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if self.type == 'dict':
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for key, value in self._items():
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for k in self._evaluator.eval_element(key):
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if isinstance(k, compiled.CompiledObject) \
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and index == k.obj:
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return self._evaluator.eval_element(value)
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raise KeyError('No key found in dictionary %s.' % self)
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# Can raise an IndexError
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if isinstance(index, slice):
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return set([self])
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else:
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return self._evaluator.eval_element(self._items()[index])
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def __getattr__(self, name):
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if name not in ['start_pos', 'get_only_subelement', 'parent',
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'get_parent_until', 'items']:
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raise AttributeError('Strange access on %s: %s.' % (self, name))
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return getattr(self.atom, name)
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# @memoize_default()
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def py__iter__(self):
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"""
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While values returns the possible values for any array field, this
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function returns the value for a certain index.
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"""
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if self.type == 'dict':
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# Get keys.
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types = set()
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for k, _ in self._items():
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types |= self._evaluator.eval_element(k)
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# We don't know which dict index comes first, therefore always
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# yield all the types.
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for _ in types:
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yield types
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else:
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for value in self._items():
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yield self._evaluator.eval_element(value)
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additions = check_array_additions(self._evaluator, self)
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if additions:
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yield additions
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def _values(self):
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"""Returns a list of a list of node."""
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if self.type == 'dict':
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return unite(v for k, v in self._items())
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else:
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return self._items()
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def _items(self):
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c = self.atom.children
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array_node = c[1]
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if array_node in (']', '}', ')'):
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return [] # Direct closing bracket, doesn't contain items.
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if tree.is_node(array_node, 'testlist_comp'):
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return array_node.children[::2]
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elif tree.is_node(array_node, 'dictorsetmaker'):
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kv = []
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iterator = iter(array_node.children)
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for key in iterator:
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op = next(iterator, None)
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if op is None or op == ',':
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kv.append(key) # A set.
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else:
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assert op == ':' # A dict.
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kv.append((key, next(iterator)))
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next(iterator, None) # Possible comma.
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return kv
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else:
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return [array_node]
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def __repr__(self):
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return "<%s of %s>" % (type(self).__name__, self.atom)
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class _FakeArray(Array):
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def __init__(self, evaluator, container, type):
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self.type = type
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self._evaluator = evaluator
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self.atom = container
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class ImplicitTuple(_FakeArray):
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def __init__(self, evaluator, testlist):
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super(ImplicitTuple, self).__init__(evaluator, testlist, 'tuple')
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self._testlist = testlist
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def _items(self):
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return self._testlist.children[::2]
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class FakeSequence(_FakeArray):
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def __init__(self, evaluator, sequence_values, type):
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"""
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type should be one of "tuple", "list"
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"""
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super(FakeSequence, self).__init__(evaluator, sequence_values, type)
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self._sequence_values = sequence_values
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def _items(self):
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return self._sequence_values
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def create_evaluated_sequence_set(evaluator, *types_order, **kwargs):
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"""
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``sequence_type`` is a named argument, that doesn't work in Python2. For backwards
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compatibility reasons, we're now using kwargs.
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"""
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sequence_type = kwargs.get('sequence_type')
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sets = tuple(AlreadyEvaluated(types) for types in types_order)
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return set([FakeSequence(evaluator, sets, sequence_type)])
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class AlreadyEvaluated(frozenset):
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"""A simple container to add already evaluated objects to an array."""
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def get_code(self, normalized=False):
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# For debugging purposes.
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return str(self)
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class MergedNodes(frozenset):
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pass
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class FakeDict(_FakeArray):
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def __init__(self, evaluator, dct):
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super(FakeDict, self).__init__(evaluator, dct, 'dict')
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self._dct = dct
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def py__iter__(self):
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yield set(compiled.create(self._evaluator, key) for key in self._dct)
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def py__getitem__(self, index):
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return unite(self._evaluator.eval_element(v) for v in self._dct[index])
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def _items(self):
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for key, values in self._dct.items():
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# TODO this is not proper. The values could be multiple values?!
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yield key, values[0]
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class MergedArray(_FakeArray):
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def __init__(self, evaluator, arrays):
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super(MergedArray, self).__init__(evaluator, arrays, arrays[-1].type)
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self._arrays = arrays
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def py__iter__(self):
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for array in self._arrays:
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for types in array.py__iter__():
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yield types
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def py__getitem__(self, index):
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return unite(self.py__iter__())
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def _items(self):
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for array in self._arrays:
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for a in array._items():
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yield a
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def __len__(self):
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return sum(len(a) for a in self._arrays)
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def unpack_tuple_to_dict(evaluator, types, exprlist):
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"""
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Unpacking tuple assignments in for statements and expr_stmts.
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"""
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if exprlist.type == 'name':
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return {exprlist.value: types}
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elif exprlist.type == 'atom' and exprlist.children[0] in '([':
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return unpack_tuple_to_dict(evaluator, types, exprlist.children[1])
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elif exprlist.type in ('testlist', 'testlist_comp', 'exprlist',
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'testlist_star_expr'):
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dct = {}
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parts = iter(exprlist.children[::2])
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n = 0
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for iter_types in py__iter__(evaluator, types, exprlist):
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n += 1
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try:
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part = next(parts)
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except StopIteration:
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analysis.add(evaluator, 'value-error-too-many-values', part,
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message="ValueError: too many values to unpack (expected %s)" % n)
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else:
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dct.update(unpack_tuple_to_dict(evaluator, iter_types, part))
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has_parts = next(parts, None)
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|
if types and has_parts is not None:
|
|
analysis.add(evaluator, 'value-error-too-few-values', has_parts,
|
|
message="ValueError: need more than %s values to unpack" % n)
|
|
return dct
|
|
elif exprlist.type == 'power' or exprlist.type == 'atom_expr':
|
|
# Something like ``arr[x], var = ...``.
|
|
# This is something that is not yet supported, would also be difficult
|
|
# to write into a dict.
|
|
return {}
|
|
elif exprlist.type == 'star_expr': # `a, *b, c = x` type unpackings
|
|
# Currently we're not supporting them.
|
|
return {}
|
|
raise NotImplementedError
|
|
|
|
|
|
def py__iter__(evaluator, types, node=None):
|
|
debug.dbg('py__iter__')
|
|
type_iters = []
|
|
for typ in types:
|
|
try:
|
|
iter_method = typ.py__iter__
|
|
except AttributeError:
|
|
if node is not None:
|
|
analysis.add(evaluator, 'type-error-not-iterable', node,
|
|
message="TypeError: '%s' object is not iterable" % typ)
|
|
else:
|
|
type_iters.append(iter_method())
|
|
#for result in iter_method():
|
|
#yield result
|
|
|
|
for t in zip_longest(*type_iters, fillvalue=set()):
|
|
yield unite(t)
|
|
|
|
|
|
def py__iter__types(evaluator, types, node=None):
|
|
"""
|
|
Calls `py__iter__`, but ignores the ordering in the end and just returns
|
|
all types that it contains.
|
|
"""
|
|
return unite(py__iter__(evaluator, types, node))
|
|
|
|
|
|
def py__getitem__(evaluator, types, trailer):
|
|
from jedi.evaluate.representation import Class
|
|
result = set()
|
|
|
|
trailer_op, node, trailer_cl = trailer.children
|
|
assert trailer_op == "["
|
|
assert trailer_cl == "]"
|
|
|
|
# special case: PEP0484 typing module, see
|
|
# https://github.com/davidhalter/jedi/issues/663
|
|
for typ in list(types):
|
|
if isinstance(typ, Class):
|
|
typing_module_types = \
|
|
pep0484.get_types_for_typing_module(evaluator, typ, node)
|
|
if typing_module_types is not None:
|
|
types.remove(typ)
|
|
result |= typing_module_types
|
|
|
|
if not types:
|
|
# all consumed by special cases
|
|
return result
|
|
|
|
for index in create_index_types(evaluator, node):
|
|
if isinstance(index, (compiled.CompiledObject, Slice)):
|
|
index = index.obj
|
|
|
|
if type(index) not in (float, int, str, unicode, slice):
|
|
# If the index is not clearly defined, we have to get all the
|
|
# possiblities.
|
|
for typ in list(types):
|
|
if isinstance(typ, Array) and typ.type == 'dict':
|
|
types.remove(typ)
|
|
result |= typ.dict_values()
|
|
return result | py__iter__types(evaluator, types)
|
|
|
|
for typ in types:
|
|
# The actual getitem call.
|
|
try:
|
|
getitem = typ.py__getitem__
|
|
except AttributeError:
|
|
analysis.add(evaluator, 'type-error-not-subscriptable', trailer_op,
|
|
message="TypeError: '%s' object is not subscriptable" % typ)
|
|
else:
|
|
try:
|
|
result |= getitem(index)
|
|
except IndexError:
|
|
result |= py__iter__types(evaluator, set([typ]))
|
|
except KeyError:
|
|
# Must be a dict. Lists don't raise KeyErrors.
|
|
result |= typ.dict_values()
|
|
return result
|
|
|
|
|
|
def check_array_additions(evaluator, array):
|
|
""" Just a mapper function for the internal _check_array_additions """
|
|
if array.type not in ('list', 'set'):
|
|
# TODO also check for dict updates
|
|
return set()
|
|
|
|
is_list = array.type == 'list'
|
|
try:
|
|
current_module = array.atom.get_parent_until()
|
|
except AttributeError:
|
|
# If there's no get_parent_until, it's a FakeSequence or another Fake
|
|
# type. Those fake types are used inside Jedi's engine. No values may
|
|
# be added to those after their creation.
|
|
return set()
|
|
return _check_array_additions(evaluator, array, current_module, is_list)
|
|
|
|
|
|
@memoize_default(default=set(), evaluator_is_first_arg=True)
|
|
@debug.increase_indent
|
|
def _check_array_additions(evaluator, compare_array, module, is_list):
|
|
"""
|
|
Checks if a `Array` has "add" (append, insert, extend) statements:
|
|
|
|
>>> a = [""]
|
|
>>> a.append(1)
|
|
"""
|
|
debug.dbg('Dynamic array search for %s' % compare_array, color='MAGENTA')
|
|
if not settings.dynamic_array_additions or isinstance(module, compiled.CompiledObject):
|
|
debug.dbg('Dynamic array search aborted.', color='MAGENTA')
|
|
return set()
|
|
|
|
def check_additions(arglist, add_name):
|
|
params = list(param.Arguments(evaluator, arglist).unpack())
|
|
result = set()
|
|
if add_name in ['insert']:
|
|
params = params[1:]
|
|
if add_name in ['append', 'add', 'insert']:
|
|
for key, nodes in params:
|
|
result |= unite(evaluator.eval_element(node) for node in nodes)
|
|
elif add_name in ['extend', 'update']:
|
|
for key, nodes in params:
|
|
for node in nodes:
|
|
types = evaluator.eval_element(node)
|
|
result |= py__iter__types(evaluator, types, node)
|
|
return result
|
|
|
|
from jedi.evaluate import representation as er, param
|
|
|
|
def get_execution_parent(element):
|
|
""" Used to get an Instance/FunctionExecution parent """
|
|
if isinstance(element, Array):
|
|
node = element.atom
|
|
else:
|
|
# Is an Instance with an
|
|
# Arguments([AlreadyEvaluated([_ArrayInstance])]) inside
|
|
# Yeah... I know... It's complicated ;-)
|
|
node = list(element.var_args.argument_node[0])[0].var_args.trailer
|
|
if isinstance(node, er.InstanceElement) or node is None:
|
|
return node
|
|
return node.get_parent_until(er.FunctionExecution)
|
|
|
|
temp_param_add, settings.dynamic_params_for_other_modules = \
|
|
settings.dynamic_params_for_other_modules, False
|
|
|
|
search_names = ['append', 'extend', 'insert'] if is_list else ['add', 'update']
|
|
comp_arr_parent = get_execution_parent(compare_array)
|
|
|
|
added_types = set()
|
|
for add_name in search_names:
|
|
try:
|
|
possible_names = module.used_names[add_name]
|
|
except KeyError:
|
|
continue
|
|
else:
|
|
for name in possible_names:
|
|
# Check if the original scope is an execution. If it is, one
|
|
# can search for the same statement, that is in the module
|
|
# dict. Executions are somewhat special in jedi, since they
|
|
# literally copy the contents of a function.
|
|
if isinstance(comp_arr_parent, er.FunctionExecution):
|
|
if comp_arr_parent.start_pos < name.start_pos < comp_arr_parent.end_pos:
|
|
name = comp_arr_parent.name_for_position(name.start_pos)
|
|
else:
|
|
# Don't check definitions that are not defined in the
|
|
# same function. This is not "proper" anyway. It also
|
|
# improves Jedi's speed for array lookups, since we
|
|
# don't have to check the whole source tree anymore.
|
|
continue
|
|
trailer = name.parent
|
|
power = trailer.parent
|
|
trailer_pos = power.children.index(trailer)
|
|
try:
|
|
execution_trailer = power.children[trailer_pos + 1]
|
|
except IndexError:
|
|
continue
|
|
else:
|
|
if execution_trailer.type != 'trailer' \
|
|
or execution_trailer.children[0] != '(' \
|
|
or execution_trailer.children[1] == ')':
|
|
continue
|
|
power = helpers.call_of_leaf(name, cut_own_trailer=True)
|
|
# InstanceElements are special, because they don't get copied,
|
|
# but have this wrapper around them.
|
|
if isinstance(comp_arr_parent, er.InstanceElement):
|
|
power = er.get_instance_el(evaluator, comp_arr_parent.instance, power)
|
|
|
|
if evaluator.recursion_detector.push_stmt(power):
|
|
# Check for recursion. Possible by using 'extend' in
|
|
# combination with function calls.
|
|
continue
|
|
if compare_array in evaluator.eval_element(power):
|
|
# The arrays match. Now add the results
|
|
added_types |= check_additions(execution_trailer.children[1], add_name)
|
|
|
|
evaluator.recursion_detector.pop_stmt()
|
|
# reset settings
|
|
settings.dynamic_params_for_other_modules = temp_param_add
|
|
debug.dbg('Dynamic array result %s' % added_types, color='MAGENTA')
|
|
return added_types
|
|
|
|
|
|
def check_array_instances(evaluator, instance):
|
|
"""Used for set() and list() instances."""
|
|
if not settings.dynamic_array_additions:
|
|
return instance.var_args
|
|
|
|
ai = _ArrayInstance(evaluator, instance)
|
|
from jedi.evaluate import param
|
|
return param.Arguments(evaluator, [AlreadyEvaluated([ai])])
|
|
|
|
|
|
class _ArrayInstance(IterableWrapper):
|
|
"""
|
|
Used for the usage of set() and list().
|
|
This is definitely a hack, but a good one :-)
|
|
It makes it possible to use set/list conversions.
|
|
|
|
In contrast to Array, ListComprehension and all other iterable types, this
|
|
is something that is only used inside `evaluate/compiled/fake/builtins.py`
|
|
and therefore doesn't need `names_dicts`, `py__bool__` and so on, because
|
|
we don't use these operations in `builtins.py`.
|
|
"""
|
|
def __init__(self, evaluator, instance):
|
|
self._evaluator = evaluator
|
|
self.instance = instance
|
|
self.var_args = instance.var_args
|
|
|
|
def py__iter__(self):
|
|
try:
|
|
_, first_nodes = next(self.var_args.unpack())
|
|
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]):
|
|
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)
|
|
if additions:
|
|
yield additions
|
|
|
|
|
|
class Slice(object):
|
|
def __init__(self, evaluator, start, stop, step):
|
|
self._evaluator = evaluator
|
|
# all of them are either a Precedence or None.
|
|
self._start = start
|
|
self._stop = stop
|
|
self._step = step
|
|
|
|
@property
|
|
def obj(self):
|
|
"""
|
|
Imitate CompiledObject.obj behavior and return a ``builtin.slice()``
|
|
object.
|
|
"""
|
|
def get(element):
|
|
if element is None:
|
|
return None
|
|
|
|
result = self._evaluator.eval_element(element)
|
|
if len(result) != 1:
|
|
# For simplicity, we want slices to be clear defined with just
|
|
# one type. Otherwise we will return an empty slice object.
|
|
raise IndexError
|
|
try:
|
|
return list(result)[0].obj
|
|
except AttributeError:
|
|
return None
|
|
|
|
try:
|
|
return slice(get(self._start), get(self._stop), get(self._step))
|
|
except IndexError:
|
|
return slice(None, None, None)
|
|
|
|
|
|
def create_index_types(evaluator, index):
|
|
"""
|
|
Handles slices in subscript nodes.
|
|
"""
|
|
if index == ':':
|
|
# Like array[:]
|
|
return set([Slice(evaluator, None, None, None)])
|
|
elif tree.is_node(index, 'subscript'): # subscript is a slice operation.
|
|
# Like array[:3]
|
|
result = []
|
|
for el in index.children:
|
|
if el == ':':
|
|
if not result:
|
|
result.append(None)
|
|
elif tree.is_node(el, 'sliceop'):
|
|
if len(el.children) == 2:
|
|
result.append(el.children[1])
|
|
else:
|
|
result.append(el)
|
|
result += [None] * (3 - len(result))
|
|
|
|
return set([Slice(evaluator, *result)])
|
|
|
|
# No slices
|
|
return evaluator.eval_element(index)
|