You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
ORPA-pyOpenRPA/WPy32-3720/python-3.7.2/Lib/site-packages/jedi/evaluate/dynamic.py

232 lines
8.4 KiB

"""
One of the really important features of |jedi| is to have an option to
understand code like this::
def foo(bar):
bar. # completion here
foo(1)
There's no doubt wheter bar is an ``int`` or not, but if there's also a call
like ``foo('str')``, what would happen? Well, we'll just show both. Because
that's what a human would expect.
It works as follows:
- |Jedi| sees a param
- search for function calls named ``foo``
- execute these calls and check the input.
"""
from parso.python import tree
from jedi import settings
from jedi import debug
from jedi.evaluate.cache import evaluator_function_cache
from jedi.evaluate import imports
from jedi.evaluate.arguments import TreeArguments
from jedi.evaluate.param import create_default_params
from jedi.evaluate.helpers import is_stdlib_path
from jedi.evaluate.utils import to_list
from jedi.parser_utils import get_parent_scope
from jedi.evaluate.context import ModuleContext, instance
from jedi.evaluate.base_context import ContextSet, NO_CONTEXTS
from jedi.evaluate import recursion
MAX_PARAM_SEARCHES = 20
class DynamicExecutedParams(object):
"""
Simulates being a parameter while actually just being multiple params.
"""
def __init__(self, evaluator, executed_params):
self.evaluator = evaluator
self._executed_params = executed_params
def infer(self):
with recursion.execution_allowed(self.evaluator, self) as allowed:
# We need to catch recursions that may occur, because an
# anonymous functions can create an anonymous parameter that is
# more or less self referencing.
if allowed:
return ContextSet.from_sets(p.infer() for p in self._executed_params)
return NO_CONTEXTS
@debug.increase_indent
def search_params(evaluator, execution_context, funcdef):
"""
A dynamic search for param values. If you try to complete a type:
>>> def func(foo):
... foo
>>> func(1)
>>> func("")
It is not known what the type ``foo`` without analysing the whole code. You
have to look for all calls to ``func`` to find out what ``foo`` possibly
is.
"""
if not settings.dynamic_params:
return create_default_params(execution_context, funcdef)
evaluator.dynamic_params_depth += 1
try:
path = execution_context.get_root_context().py__file__()
if path is not None and is_stdlib_path(path):
# We don't want to search for usages in the stdlib. Usually people
# don't work with it (except if you are a core maintainer, sorry).
# This makes everything slower. Just disable it and run the tests,
# you will see the slowdown, especially in 3.6.
return create_default_params(execution_context, funcdef)
if funcdef.type == 'lambdef':
string_name = _get_lambda_name(funcdef)
if string_name is None:
return create_default_params(execution_context, funcdef)
else:
string_name = funcdef.name.value
debug.dbg('Dynamic param search in %s.', string_name, color='MAGENTA')
try:
module_context = execution_context.get_root_context()
function_executions = _search_function_executions(
evaluator,
module_context,
funcdef,
string_name=string_name,
)
if function_executions:
zipped_params = zip(*list(
function_execution.get_executed_params()
for function_execution in function_executions
))
params = [DynamicExecutedParams(evaluator, executed_params) for executed_params in zipped_params]
# Evaluate the ExecutedParams to types.
else:
return create_default_params(execution_context, funcdef)
finally:
debug.dbg('Dynamic param result finished', color='MAGENTA')
return params
finally:
evaluator.dynamic_params_depth -= 1
@evaluator_function_cache(default=None)
@to_list
def _search_function_executions(evaluator, module_context, funcdef, string_name):
"""
Returns a list of param names.
"""
compare_node = funcdef
if string_name == '__init__':
cls = get_parent_scope(funcdef)
if isinstance(cls, tree.Class):
string_name = cls.name.value
compare_node = cls
found_executions = False
i = 0
for for_mod_context in imports.get_modules_containing_name(
evaluator, [module_context], string_name):
if not isinstance(module_context, ModuleContext):
return
for name, trailer in _get_possible_nodes(for_mod_context, string_name):
i += 1
# This is a simple way to stop Jedi's dynamic param recursion
# from going wild: The deeper Jedi's in the recursion, the less
# code should be evaluated.
if i * evaluator.dynamic_params_depth > MAX_PARAM_SEARCHES:
return
random_context = evaluator.create_context(for_mod_context, name)
for function_execution in _check_name_for_execution(
evaluator, random_context, compare_node, name, trailer):
found_executions = True
yield function_execution
# If there are results after processing a module, we're probably
# good to process. This is a speed optimization.
if found_executions:
return
def _get_lambda_name(node):
stmt = node.parent
if stmt.type == 'expr_stmt':
first_operator = next(stmt.yield_operators(), None)
if first_operator == '=':
first = stmt.children[0]
if first.type == 'name':
return first.value
return None
def _get_possible_nodes(module_context, func_string_name):
try:
names = module_context.tree_node.get_used_names()[func_string_name]
except KeyError:
return
for name in names:
bracket = name.get_next_leaf()
trailer = bracket.parent
if trailer.type == 'trailer' and bracket == '(':
yield name, trailer
def _check_name_for_execution(evaluator, context, compare_node, name, trailer):
from jedi.evaluate.context.function import FunctionExecutionContext
def create_func_excs():
arglist = trailer.children[1]
if arglist == ')':
arglist = None
args = TreeArguments(evaluator, context, arglist, trailer)
if value_node.type == 'classdef':
created_instance = instance.TreeInstance(
evaluator,
value.parent_context,
value,
args
)
for execution in created_instance.create_init_executions():
yield execution
else:
yield value.get_function_execution(args)
for value in evaluator.goto_definitions(context, name):
value_node = value.tree_node
if compare_node == value_node:
for func_execution in create_func_excs():
yield func_execution
elif isinstance(value.parent_context, FunctionExecutionContext) and \
compare_node.type == 'funcdef':
# Here we're trying to find decorators by checking the first
# parameter. It's not very generic though. Should find a better
# solution that also applies to nested decorators.
params = value.parent_context.get_executed_params()
if len(params) != 1:
continue
values = params[0].infer()
nodes = [v.tree_node for v in values]
if nodes == [compare_node]:
# Found a decorator.
module_context = context.get_root_context()
execution_context = next(create_func_excs())
for name, trailer in _get_possible_nodes(module_context, params[0].string_name):
if value_node.start_pos < name.start_pos < value_node.end_pos:
random_context = evaluator.create_context(execution_context, name)
iterator = _check_name_for_execution(
evaluator,
random_context,
compare_node,
name,
trailer
)
for function_execution in iterator:
yield function_execution