""" Implementations of standard library functions, because it's not possible to understand them with Jedi. To add a new implementation, create a function and add it to the ``_implemented`` dict at the bottom of this module. """ import collections import re from jedi._compatibility import unicode from jedi.evaluate import compiled from jedi.evaluate import representation as er from jedi.evaluate import iterable from jedi.parser import Parser from jedi.parser import tree from jedi import debug from jedi.evaluate import precedence from jedi.evaluate import param class NotInStdLib(LookupError): pass def execute(evaluator, obj, arguments): try: obj_name = str(obj.name) except AttributeError: pass else: if obj.parent == compiled.builtin: module_name = 'builtins' elif isinstance(obj.parent, tree.Module): module_name = str(obj.parent.name) else: module_name = '' # for now we just support builtin functions. try: return _implemented[module_name][obj_name](evaluator, obj, arguments) except KeyError: pass raise NotInStdLib() def _follow_param(evaluator, arguments, index): try: key, values = list(arguments.unpack())[index] except IndexError: return [] else: return iterable.unite(evaluator.eval_element(v) for v in values) def argument_clinic(string, want_obj=False, want_scope=False, want_arguments=False): """ Works like Argument Clinic (PEP 436), to validate function params. """ clinic_args = [] allow_kwargs = False optional = False while string: # Optional arguments have to begin with a bracket. And should always be # at the end of the arguments. This is therefore not a proper argument # clinic implementation. `range()` for exmple allows an optional start # value at the beginning. match = re.match('(?:(?:(\[),? ?|, ?|)(\w+)|, ?/)\]*', string) string = string[len(match.group(0)):] if not match.group(2): # A slash -> allow named arguments allow_kwargs = True continue optional = optional or bool(match.group(1)) word = match.group(2) clinic_args.append((word, optional, allow_kwargs)) def f(func): def wrapper(evaluator, obj, arguments): debug.dbg('builtin start %s' % obj, color='MAGENTA') try: lst = list(arguments.eval_argument_clinic(clinic_args)) except ValueError: return set() else: kwargs = {} if want_scope: kwargs['scope'] = arguments.scope() if want_obj: kwargs['obj'] = obj if want_arguments: kwargs['arguments'] = arguments return func(evaluator, *lst, **kwargs) finally: debug.dbg('builtin end', color='MAGENTA') return wrapper return f @argument_clinic('object, name[, default], /') def builtins_getattr(evaluator, objects, names, defaults=None): # follow the first param for obj in objects: if not isinstance(obj, (er.Instance, er.Class, tree.Module, compiled.CompiledObject)): debug.warning('getattr called without instance') continue for name in names: if precedence.is_string(name): return evaluator.find_types(obj, name.obj) else: debug.warning('getattr called without str') continue return set() @argument_clinic('object[, bases, dict], /') def builtins_type(evaluator, objects, bases, dicts): if bases or dicts: # It's a type creation... maybe someday... return set() else: return set([o.py__class__(evaluator) for o in objects]) class SuperInstance(er.Instance): """To be used like the object ``super`` returns.""" def __init__(self, evaluator, cls): su = cls.py_mro()[1] super().__init__(evaluator, su and su[0] or self) @argument_clinic('[type[, obj]], /', want_scope=True) def builtins_super(evaluator, types, objects, scope): # TODO make this able to detect multiple inheritance super accept = (tree.Function, er.FunctionExecution) if scope.isinstance(*accept): wanted = (tree.Class, er.Instance) cls = scope.get_parent_until(accept + wanted, include_current=False) if isinstance(cls, wanted): if isinstance(cls, tree.Class): cls = er.Class(evaluator, cls) elif isinstance(cls, er.Instance): cls = cls.base su = cls.py__bases__(evaluator) if su: return evaluator.execute(su[0]) return set() def get_iterable_content(evaluator, arguments, argument_index): nodes = list(arguments.unpack())[argument_index][1] return set(iterable.unite(iterable.get_iterator_types(evaluator, node) for node in nodes)) @argument_clinic('sequence, /', want_obj=True, want_arguments=True) def builtins_reversed(evaluator, sequences, obj, arguments): # While we could do without this variable (just by using sequences), we # want static analysis to work well. Therefore we need to generated the # values again. all_sequence_types = get_iterable_content(evaluator, arguments, 0) ordered = iterable.ordered_elements_of_iterable(evaluator, sequences, all_sequence_types) rev = [iterable.AlreadyEvaluated(o) for o in reversed(ordered)] # Repack iterator values and then run it the normal way. This is # necessary, because `reversed` is a function and autocompletion # would fail in certain cases like `reversed(x).__iter__` if we # just returned the result directly. rev = iterable.AlreadyEvaluated( [iterable.FakeSequence(evaluator, rev, 'list')] ) return set([er.Instance(evaluator, obj, param.Arguments(evaluator, [rev]))]) @argument_clinic('obj, type, /', want_arguments=True) def builtins_isinstance(evaluator, objects, types, arguments): bool_results = set([]) for o in objects: try: mro_func = o.py__class__(evaluator).py__mro__ except AttributeError: # This is temporary. Everything should have a class attribute in # Python?! Maybe we'll leave it here, because some numpy objects or # whatever might not. return set([compiled.true_obj, compiled.false_obj]) mro = mro_func(evaluator) for cls_or_tup in types: if cls_or_tup.is_class(): bool_results.add(cls_or_tup in mro) else: # Check for tuples. classes = get_iterable_content(evaluator, arguments, 1) bool_results.add(any(cls in mro for cls in classes)) return set(compiled.keyword_from_value(x) for x in bool_results) def collections_namedtuple(evaluator, obj, arguments): """ Implementation of the namedtuple function. This has to be done by processing the namedtuple class template and evaluating the result. .. note:: |jedi| only supports namedtuples on Python >2.6. """ # Namedtuples are not supported on Python 2.6 if not hasattr(collections, '_class_template'): return set() # Process arguments name = _follow_param(evaluator, arguments, 0)[0].obj _fields = _follow_param(evaluator, arguments, 1)[0] if isinstance(_fields, compiled.CompiledObject): fields = _fields.obj.replace(',', ' ').split() elif isinstance(_fields, iterable.Array): try: fields = [v.obj for v in _fields.values()] except AttributeError: return set() else: return set() # Build source source = collections._class_template.format( typename=name, field_names=fields, num_fields=len(fields), arg_list=', '.join(fields), repr_fmt=', '.join(collections._repr_template.format(name=name) for name in fields), field_defs='\n'.join(collections._field_template.format(index=index, name=name) for index, name in enumerate(fields)) ) # Parse source generated_class = Parser(evaluator.grammar, unicode(source)).module.subscopes[0] return set([er.Class(evaluator, generated_class)]) @argument_clinic('first, /') def _return_first_param(evaluator, firsts): return firsts _implemented = { 'builtins': { 'getattr': builtins_getattr, 'type': builtins_type, 'super': builtins_super, 'reversed': builtins_reversed, 'isinstance': builtins_isinstance, }, 'copy': { 'copy': _return_first_param, 'deepcopy': _return_first_param, }, 'json': { 'load': lambda *args: set(), 'loads': lambda *args: set(), }, 'collections': { 'namedtuple': collections_namedtuple, }, }