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, position)
string_name = name_or_str.value if isinstance(name_or_str,
Name) else name_or_str
# This paragraph is currently needed for proper branch type inference
# (static analysis).
found_predefined_types = None
if self.predefined_names and isinstance(name_or_str, Name):
node = name_or_str
while node is not None and not parser_utils.is_scope(node):
node = node.parent
if node.type in ("if_stmt", "for_stmt", "comp_for",
'sync_comp_for'):
try:
name_dict = self.predefined_names[node]
types = name_dict[string_name]
except KeyError:
continue
else:
found_predefined_types = types
break
if found_predefined_types is not None and names:
from medi.inference import flow_analysis
check = flow_analysis.reachability_check(
context=self,
value_scope=self.tree_node,
node=name_or_str,
)
if check is flow_analysis.UNREACHABLE:
values = NO_VALUES
else:
values = found_predefined_types
else:
values = ValueSet.from_sets(name.infer() for name in names)
if not names and not values and analysis_errors:
if isinstance(name_or_str, Name):
from medi.inference import analysis
message = ("NameError: name '%s' is not defined." %
string_name)
analysis.add(name_context, 'name-error', name_or_str, message)
debug.dbg('context.names_to_types: %s -> %s', names, values)
if values:
return values
return self._check_for_additional_knowledge(name_or_str, name_context,
position)
def parent_scope(node):
while True:
node = node.parent
if parser_utils.is_scope(node):
return node
elif node.type in ('argument', 'testlist_comp'):
if node.children[1].type in ('comp_for', 'sync_comp_for'):
return node.children[1]
elif node.type == 'dictorsetmaker':
for n in node.children[1:4]:
# In dictionaries it can be pretty much anything.
if n.type in ('comp_for', 'sync_comp_for'):
return n
def check_flow_information(value, flow, search_name, pos):
""" Try to find out the type of a variable just with the information that
is given by the flows: e.g. It is also responsible for assert checks.::
if isinstance(k, str):
k. # <- completion here
ensures that `k` is a string.
"""
if not settings.dynamic_flow_information:
return None
result = None
if is_scope(flow):
# Check for asserts.
module_node = flow.get_root_node()
try:
names = module_node.get_used_names()[search_name.value]
except KeyError:
return None
names = reversed([
n for n in names
if flow.start_pos <= n.start_pos < (pos or flow.end_pos)
])
for name in names:
ass = search_ancestor(name, 'assert_stmt')
if ass is not None:
result = _check_isinstance_type(value, ass.assertion,
search_name)
if result is not None:
return result
if flow.type in ('if_stmt', 'while_stmt'):
potential_ifs = [c for c in flow.children[1::4] if c != ':']
for if_test in reversed(potential_ifs):
if search_name.start_pos > if_test.end_pos:
return _check_isinstance_type(value, if_test, search_name)
return result
def infer_node(context, element):
if isinstance(context, CompForContext):
return _infer_node(context, element)
if_stmt = element
while if_stmt is not None:
if_stmt = if_stmt.parent
if if_stmt.type in ('if_stmt', 'for_stmt'):
break
if parser_utils.is_scope(if_stmt):
if_stmt = None
break
predefined_if_name_dict = context.predefined_names.get(if_stmt)
# TODO there's a lot of issues with this one. We actually should do
# this in a different way. Caching should only be active in certain
# cases and this all sucks.
if predefined_if_name_dict is None and if_stmt \
and if_stmt.type == 'if_stmt' and context.inference_state.is_analysis:
if_stmt_test = if_stmt.children[1]
name_dicts = [{}]
# If we already did a check, we don't want to do it again -> If
# value.predefined_names is filled, we stop.
# We don't want to check the if stmt itself, it's just about
# the content.
if element.start_pos > if_stmt_test.end_pos:
# Now we need to check if the names in the if_stmt match the
# names in the suite.
if_names = get_names_of_node(if_stmt_test)
element_names = get_names_of_node(element)
str_element_names = [e.value for e in element_names]
if any(i.value in str_element_names for i in if_names):
for if_name in if_names:
definitions = context.inference_state.infer(context, if_name)
# Every name that has multiple different definitions
# causes the complexity to rise. The complexity should
# never fall below 1.
if len(definitions) > 1:
if len(name_dicts) * len(definitions) > 16:
debug.dbg('Too many options for if branch inference %s.', if_stmt)
# There's only a certain amount of branches
# Medi can infer, otherwise it will take to
# long.
name_dicts = [{}]
break
original_name_dicts = list(name_dicts)
name_dicts = []
for definition in definitions:
new_name_dicts = list(original_name_dicts)
for i, name_dict in enumerate(new_name_dicts):
new_name_dicts[i] = name_dict.copy()
new_name_dicts[i][if_name.value] = ValueSet([definition])
name_dicts += new_name_dicts
else:
for name_dict in name_dicts:
name_dict[if_name.value] = definitions
if len(name_dicts) > 1:
result = NO_VALUES
for name_dict in name_dicts:
with context.predefine_names(if_stmt, name_dict):
result |= _infer_node(context, element)
return result
else:
return _infer_node_if_inferred(context, element)
else:
if predefined_if_name_dict:
return _infer_node(context, element)
else:
return _infer_node_if_inferred(context, element)
def _get_flow_scopes(node):
while True:
node = get_parent_scope(node, include_flows=True)
if node is None or is_scope(node):
return
yield node