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ORPA-pyOpenRPA/WPy32-3720/python-3.7.2/Lib/site-packages/jedi/evaluate/stdlib.py

322 lines
11 KiB

"""
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.
Note that this module exists only to implement very specific functionality in
the standard library. The usual way to understand the standard library is the
compiled module that returns the types for C-builtins.
"""
import parso
from jedi._compatibility import force_unicode
from jedi import debug
from jedi.evaluate.arguments import ValuesArguments, repack_with_argument_clinic
from jedi.evaluate import analysis
from jedi.evaluate import compiled
from jedi.evaluate.context.instance import \
AbstractInstanceContext, CompiledInstance, BoundMethod, InstanceArguments
from jedi.evaluate.base_context import ContextualizedNode, \
NO_CONTEXTS, ContextSet
from jedi.evaluate.context import ClassContext, ModuleContext, FunctionExecutionContext
from jedi.evaluate.context import iterable
from jedi.evaluate.lazy_context import LazyTreeContext
from jedi.evaluate.syntax_tree import is_string
# Now this is all part of fake tuples in Jedi. However super doesn't work on
# __init__ and __new__ doesn't work at all. So adding this to nametuples is
# just the easiest way.
_NAMEDTUPLE_INIT = """
def __init__(_cls, {arg_list}):
'A helper function for namedtuple.'
self.__iterable = ({arg_list})
def __iter__(self):
for i in self.__iterable:
yield i
def __getitem__(self, y):
return self.__iterable[y]
"""
class NotInStdLib(LookupError):
pass
def execute(evaluator, obj, arguments):
if isinstance(obj, BoundMethod):
raise NotInStdLib()
try:
obj_name = obj.name.string_name
except AttributeError:
pass
else:
if obj.parent_context == evaluator.builtins_module:
module_name = 'builtins'
elif isinstance(obj.parent_context, ModuleContext):
module_name = obj.parent_context.name.string_name
else:
module_name = ''
# for now we just support builtin functions.
try:
func = _implemented[module_name][obj_name]
except KeyError:
pass
else:
return func(evaluator, obj, arguments=arguments)
raise NotInStdLib()
def _follow_param(evaluator, arguments, index):
try:
key, lazy_context = list(arguments.unpack())[index]
except IndexError:
return NO_CONTEXTS
else:
return lazy_context.infer()
def argument_clinic(string, want_obj=False, want_context=False, want_arguments=False):
"""
Works like Argument Clinic (PEP 436), to validate function params.
"""
def f(func):
@repack_with_argument_clinic(string, keep_arguments_param=True)
def wrapper(evaluator, obj, *args, **kwargs):
arguments = kwargs.pop('arguments')
assert not kwargs # Python 2...
debug.dbg('builtin start %s' % obj, color='MAGENTA')
result = NO_CONTEXTS
if want_context:
kwargs['context'] = arguments.context
if want_obj:
kwargs['obj'] = obj
if want_arguments:
kwargs['arguments'] = arguments
result = func(evaluator, *args, **kwargs)
debug.dbg('builtin end: %s', result, color='MAGENTA')
return result
return wrapper
return f
@argument_clinic('iterator[, default], /')
def builtins_next(evaluator, iterators, defaults):
"""
TODO this function is currently not used. It's a stab at implementing next
in a different way than fake objects. This would be a bit more flexible.
"""
if evaluator.environment.version_info.major == 2:
name = 'next'
else:
name = '__next__'
context_set = NO_CONTEXTS
for iterator in iterators:
if isinstance(iterator, AbstractInstanceContext):
context_set = ContextSet.from_sets(
n.infer()
for filter in iterator.get_filters(include_self_names=True)
for n in filter.get(name)
).execute_evaluated()
if context_set:
return context_set
return defaults
@argument_clinic('object, name[, default], /')
def builtins_getattr(evaluator, objects, names, defaults=None):
# follow the first param
for obj in objects:
for name in names:
if is_string(name):
return obj.py__getattribute__(force_unicode(name.get_safe_value()))
else:
debug.warning('getattr called without str')
continue
return NO_CONTEXTS
@argument_clinic('object[, bases, dict], /')
def builtins_type(evaluator, objects, bases, dicts):
if bases or dicts:
# It's a type creation... maybe someday...
return NO_CONTEXTS
else:
return objects.py__class__()
class SuperInstance(AbstractInstanceContext):
"""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_context=True)
def builtins_super(evaluator, types, objects, context):
# TODO make this able to detect multiple inheritance super
if isinstance(context, FunctionExecutionContext):
if isinstance(context.var_args, InstanceArguments):
su = context.var_args.instance.py__class__().py__bases__()
return su[0].infer().execute_evaluated()
return NO_CONTEXTS
@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.
key, lazy_context = next(arguments.unpack())
cn = None
if isinstance(lazy_context, LazyTreeContext):
# TODO access private
cn = ContextualizedNode(lazy_context._context, lazy_context.data)
ordered = list(sequences.iterate(cn))
rev = list(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.
seq = iterable.FakeSequence(evaluator, u'list', rev)
arguments = ValuesArguments([ContextSet(seq)])
return ContextSet(CompiledInstance(evaluator, evaluator.builtins_module, obj, arguments))
@argument_clinic('obj, type, /', want_arguments=True)
def builtins_isinstance(evaluator, objects, types, arguments):
bool_results = set()
for o in objects:
cls = o.py__class__()
try:
mro_func = cls.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.
bool_results = set([True, False])
break
mro = mro_func()
for cls_or_tup in types:
if cls_or_tup.is_class():
bool_results.add(cls_or_tup in mro)
elif cls_or_tup.name.string_name == 'tuple' \
and cls_or_tup.get_root_context() == evaluator.builtins_module:
# Check for tuples.
classes = ContextSet.from_sets(
lazy_context.infer()
for lazy_context in cls_or_tup.iterate()
)
bool_results.add(any(cls in mro for cls in classes))
else:
_, lazy_context = list(arguments.unpack())[1]
if isinstance(lazy_context, LazyTreeContext):
node = lazy_context.data
message = 'TypeError: isinstance() arg 2 must be a ' \
'class, type, or tuple of classes and types, ' \
'not %s.' % cls_or_tup
analysis.add(lazy_context._context, 'type-error-isinstance', node, message)
return ContextSet.from_iterable(
compiled.builtin_from_name(evaluator, force_unicode(str(b)))
for b 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.
"""
collections_context = obj.parent_context
_class_template_set = collections_context.py__getattribute__(u'_class_template')
if not _class_template_set:
# Namedtuples are not supported on Python 2.6, early 2.7, because the
# _class_template variable is not defined, there.
return NO_CONTEXTS
# Process arguments
# TODO here we only use one of the types, we should use all.
# TODO this is buggy, doesn't need to be a string
name = list(_follow_param(evaluator, arguments, 0))[0].get_safe_value()
_fields = list(_follow_param(evaluator, arguments, 1))[0]
if isinstance(_fields, compiled.CompiledObject):
fields = _fields.get_safe_value().replace(',', ' ').split()
elif isinstance(_fields, iterable.Sequence):
fields = [
v.get_safe_value()
for lazy_context in _fields.py__iter__()
for v in lazy_context.infer() if is_string(v)
]
else:
return NO_CONTEXTS
def get_var(name):
x, = collections_context.py__getattribute__(name)
return x.get_safe_value()
base = next(iter(_class_template_set)).get_safe_value()
base += _NAMEDTUPLE_INIT
# Build source code
code = base.format(
typename=name,
field_names=tuple(fields),
num_fields=len(fields),
arg_list=repr(tuple(fields)).replace("u'", "").replace("'", "")[1:-1],
repr_fmt=', '.join(get_var(u'_repr_template').format(name=name) for name in fields),
field_defs='\n'.join(get_var(u'_field_template').format(index=index, name=name)
for index, name in enumerate(fields))
)
# Parse source code
module = evaluator.grammar.parse(code)
generated_class = next(module.iter_classdefs())
parent_context = ModuleContext(
evaluator, module, None,
code_lines=parso.split_lines(code, keepends=True),
)
return ContextSet(ClassContext(evaluator, parent_context, 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 evaluator, obj, arguments: NO_CONTEXTS,
'loads': lambda evaluator, obj, arguments: NO_CONTEXTS,
},
'collections': {
'namedtuple': collections_namedtuple,
},
}