Only 125 fails left in the integration tests.

jedi/evaluate/__init__.py

@@ -484,8 +484,7 @@ class Evaluator(object):
                 ))
 
         if tree.is_node(par, 'trailer') and par.children[0] == '.':
-            call = helpers.call_of_leaf(name, cut_own_trailer=True)
-            values = self.eval_element(context, call)
+            values = helpers.evaluate_call_of_leaf(context, name, cut_own_trailer=True)
             return unite(
                 self.find_types(value, name, is_goto=True) for value in values
             )

jedi/evaluate/context.py

@@ -47,6 +47,10 @@ class Context(object):
     def eval_trailer(self, types, trailer):
         return self.evaluator.eval_trailer(self, types, trailer)
 
+    def py__getattribute__(self, name_or_str, position=None,
+                           search_global=False, is_goto=False):
+        return self.evaluator.find_types(self, name_or_str, position, search_global, is_goto)
+
 
 class TreeContext(Context):
     def __init__(self, evaluator, parent_context=None):
@@ -62,10 +66,10 @@ class FlowContext(TreeContext):
 
 class AbstractLazyContext(object):
     def __init__(self, data):
-        self._data = data
+        self.data = data
 
     def __repr__(self):
-        return '<%s: %s>' % (self.__class__.__name__, self._data)
+        return '<%s: %s>' % (self.__class__.__name__, self.data)
 
     def infer(self):
         raise NotImplementedError
@@ -74,13 +78,13 @@ class AbstractLazyContext(object):
 class LazyKnownContext(AbstractLazyContext):
     """data is a context."""
     def infer(self):
-        yield self._data
+        yield self.data
 
 
 class LazyKnownContexts(AbstractLazyContext):
     """data is a set of contexts."""
     def infer(self):
-        return self._data
+        return self.data
 
 
 class LazyUnknownContext(AbstractLazyContext):
@@ -97,7 +101,7 @@ class LazyTreeContext(AbstractLazyContext):
         self._context = context
 
     def infer(self):
-        return self._context.eval_node(self._data)
+        return self._context.eval_node(self.data)
 
 
 def get_merged_lazy_context(lazy_contexts):
@@ -110,4 +114,4 @@ def get_merged_lazy_context(lazy_contexts):
 class MergedLazyContexts(AbstractLazyContext):
     """data is a list of lazy contexts."""
     def infer(self):
-        return unite(l.infer() for l in self._data)
+        return unite(l.infer() for l in self.data)

jedi/evaluate/stdlib.py

@@ -16,7 +16,8 @@ from jedi._compatibility import unicode
 from jedi.common import unite
 from jedi.evaluate import compiled
 from jedi.evaluate import representation as er
-from jedi.evaluate.instance import InstanceFunctionExecution, AbstractInstanceContext
+from jedi.evaluate.instance import InstanceFunctionExecution, \
+    AbstractInstanceContext, CompiledInstance
 from jedi.evaluate import iterable
 from jedi.parser import ParserWithRecovery
 from jedi import debug
@@ -148,18 +149,17 @@ 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.
-    first_arg = next(arguments.as_tuple())[0]
-    ordered = list(iterable.py__iter__(evaluator, sequences, first_arg))
+    key, lazy_context = next(arguments.unpack())
+    ordered = list(iterable.py__iter__(evaluator, sequences, lazy_context.data))
 
-    rev = [iterable.AlreadyEvaluated(o) for o in reversed(ordered)]
+    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.
-    rev = iterable.AlreadyEvaluated(
-        [iterable.FakeSequence(evaluator, rev, 'list')]
-    )
-    return set([er.Instance(evaluator, obj, param.Arguments(evaluator, [rev]))])
+    seq = iterable.FakeSequence(evaluator, 'list', rev)
+    arguments = param.ValuesArguments([[seq]])
+    return set([CompiledInstance(evaluator, evaluator.BUILTINS, obj, arguments)])
 
 
 @argument_clinic('obj, type, /', want_arguments=True)