# [ExprNode or [ExprNode or None] or None]
# Cached result of subexpr_nodes()
# use_managed_ref boolean use ref-counted temps/assignments/etc.
+ # result_is_used boolean indicates that the result will be dropped and the
+ # result_code/temp_result can safely be set to None
result_ctype = None
type = None
temp_code = None
old_temp = None # error checker for multiple frees etc.
use_managed_ref = True # can be set by optimisation transforms
+ result_is_used = True
# The Analyse Expressions phase for expressions is split
# into two sub-phases:
def release_temp_result(self, code):
if not self.temp_code:
+ if not self.result_is_used:
+ # not used anyway, so ignore if not set up
+ return
if self.old_temp:
raise RuntimeError("temp %s released multiple times in %s" % (
self.old_temp, self.__class__.__name__))
def generate_disposal_code(self, code):
if self.is_temp:
- if self.type.is_pyobject:
+ if self.type.is_pyobject and self.result():
code.put_decref_clear(self.result(), self.ctype())
else:
# Already done if self.is_temp
# is used for the pointer to the type they represent.
return type_type
elif self.entry.type.is_cfunction:
- # special case: referring to a C function must return it's pointer
+ # special case: referring to a C function must return its pointer
return PyrexTypes.CPtrType(self.entry.type)
else:
return self.entry.type
#print "...RHS type", rhs.type, "ctype", rhs.ctype() ###
if self.use_managed_ref:
rhs.make_owned_reference(code)
- if entry.is_cglobal:
- code.put_gotref(self.py_result())
+ is_external_ref = entry.is_cglobal or self.entry.in_closure or self.entry.from_closure
if not self.lhs_of_first_assignment:
+ if is_external_ref:
+ code.put_gotref(self.py_result())
if entry.is_local and not Options.init_local_none:
initialized = entry.scope.control_flow.get_state((entry.name, 'initialized'), self.pos)
if initialized is True:
code.put_xdecref(self.result(), self.ctype())
else:
code.put_decref(self.result(), self.ctype())
- if entry.is_cglobal:
+ if is_external_ref:
code.put_giveref(rhs.py_result())
code.putln('%s = %s;' % (self.result(),
elif self.analyse_as_unbound_cmethod(env):
return self.entry.type
else:
- self.analyse_attribute(env, obj_type = self.obj.infer_type(env))
+ obj_type = self.obj.infer_type(env)
+ self.analyse_attribute(env, obj_type = obj_type)
+ if obj_type.is_builtin_type and self.type.is_cfunction:
+ # special case: C-API replacements for C methods of
+ # builtin types cannot be inferred as C functions as
+ # that would prevent their use as bound methods
+ self.type = py_object_type
+ return py_object_type
return self.type
def analyse_target_declaration(self, env):
self.value_expr.annotate(code)
-class GeneratorExpressionNode(ScopedExprNode):
- # A generator expression, e.g. (i for i in range(10))
- #
- # Result is a generator.
+class InlinedGeneratorExpressionNode(ScopedExprNode):
+ # An inlined generator expression for which the result is
+ # calculated inside of the loop. This will only be created by
+ # transforms when replacing builtin calls on generator
+ # expressions.
#
- # loop ForStatNode the for-loop, containing a YieldExprNode
+ # loop ForStatNode the for-loop, not containing any YieldExprNodes
+ # result_node ResultRefNode the reference to the result value temp
+ # orig_func String the name of the builtin function this node replaces
child_attrs = ["loop"]
-
+ loop_analysed = False
type = py_object_type
def analyse_scoped_declarations(self, env):
self.loop.analyse_expressions(env)
self.is_temp = True
- def analyse_scoped_expressions(self, env):
- if self.has_local_scope:
- self.loop.analyse_expressions(env)
-
def may_be_none(self):
return False
def annotate(self, code):
self.loop.annotate(code)
-
-class InlinedGeneratorExpressionNode(GeneratorExpressionNode):
- # An inlined generator expression for which the result is
- # calculated inside of the loop. This will only be created by
- # transforms when replacing builtin calls on generator
- # expressions.
- #
- # loop ForStatNode the for-loop, not containing any YieldExprNodes
- # result_node ResultRefNode the reference to the result value temp
- # orig_func String the name of the builtin function this node replaces
-
- child_attrs = ["loop"]
- loop_analysed = False
-
def infer_type(self, env):
return self.result_node.infer_type(env)
def analyse_scoped_expressions(self, env):
self.loop_analysed = True
- GeneratorExpressionNode.analyse_scoped_expressions(self, env)
+ if self.has_local_scope:
+ self.loop.analyse_expressions(env)
def coerce_to(self, dst_type, env):
if self.orig_func == 'sum' and dst_type.is_numeric and not self.loop_analysed:
# assignments.
self.result_node.type = self.type = dst_type
return self
- return GeneratorExpressionNode.coerce_to(self, dst_type, env)
+ return super(InlinedGeneratorExpressionNode, self).coerce_to(dst_type, env)
def generate_result_code(self, code):
self.result_node.result_code = self.result()
self.pymethdef_cname = self.def_node.entry.pymethdef_cname
env.add_lambda_def(self.def_node)
+
+class GeneratorExpressionNode(LambdaNode):
+ # A generator expression, e.g. (i for i in range(10))
+ #
+ # Result is a generator.
+ #
+ # loop ForStatNode the for-loop, containing a YieldExprNode
+ # def_node DefNode the underlying generator 'def' node
+
+ name = StringEncoding.EncodedString('genexpr')
+ binding = False
+
+ def analyse_declarations(self, env):
+ self.def_node.no_assignment_synthesis = True
+ self.def_node.analyse_declarations(env)
+ env.add_lambda_def(self.def_node)
+
+ def generate_result_code(self, code):
+ code.putln(
+ '%s = %s(%s, NULL); %s' % (
+ self.result(),
+ self.def_node.entry.func_cname,
+ self.self_result_code(),
+ code.error_goto_if_null(self.result(), self.pos)))
+ code.put_gotref(self.py_result())
+
+
class YieldExprNode(ExprNode):
# Yield expression node
#
# arg ExprNode the value to return from the generator
# label_name string name of the C label used for this yield
+ # label_num integer yield label number
subexprs = ['arg']
type = py_object_type
+ label_num = 0
def analyse_types(self, env):
+ if not self.label_num:
+ error(self.pos, "'yield' not supported here")
self.is_temp = 1
if self.arg is not None:
self.arg.analyse_types(env)
if not self.arg.type.is_pyobject:
self.arg = self.arg.coerce_to_pyobject(env)
- error(self.pos, "Generators are not supported")
+ env.use_utility_code(generator_utility_code)
- def generate_result_code(self, code):
+ def generate_evaluation_code(self, code):
self.label_name = code.new_label('resume_from_yield')
code.use_label(self.label_name)
- code.putln("/* FIXME: save temporary variables */")
- code.putln("/* FIXME: return from function, yielding value */")
+ if self.arg:
+ self.arg.generate_evaluation_code(code)
+ self.arg.make_owned_reference(code)
+ code.putln(
+ "%s = %s;" % (
+ Naming.retval_cname,
+ self.arg.result_as(py_object_type)))
+ self.arg.generate_post_assignment_code(code)
+ #self.arg.generate_disposal_code(code)
+ self.arg.free_temps(code)
+ else:
+ code.put_init_to_py_none(Naming.retval_cname, py_object_type)
+ saved = []
+ code.funcstate.closure_temps.reset()
+ for cname, type, manage_ref in code.funcstate.temps_in_use():
+ save_cname = code.funcstate.closure_temps.allocate_temp(type)
+ saved.append((cname, save_cname, type))
+ if type.is_pyobject:
+ code.put_xgiveref(cname)
+ code.putln('%s->%s = %s;' % (Naming.cur_scope_cname, save_cname, cname))
+
+ code.put_xgiveref(Naming.retval_cname)
+ code.put_finish_refcount_context()
+ code.putln("/* return from generator, yielding value */")
+ code.putln("%s->%s.resume_label = %d;" % (Naming.cur_scope_cname, Naming.obj_base_cname, self.label_num))
+ code.putln("return %s;" % Naming.retval_cname);
code.put_label(self.label_name)
- code.putln("/* FIXME: restore temporary variables and */")
- code.putln("/* FIXME: extract sent value from closure */")
-
+ for cname, save_cname, type in saved:
+ code.putln('%s = %s->%s;' % (cname, Naming.cur_scope_cname, save_cname))
+ if type.is_pyobject:
+ code.putln('%s->%s = 0;' % (Naming.cur_scope_cname, save_cname))
+ if type.is_pyobject:
+ code.put_xgotref(cname)
+ if self.result_is_used:
+ self.allocate_temp_result(code)
+ code.putln('%s = %s; %s' %
+ (self.result(), Naming.sent_value_cname,
+ code.error_goto_if_null(self.result(), self.pos)))
+ code.put_incref(self.result(), py_object_type)
+ else:
+ code.putln(code.error_goto_if_null(Naming.sent_value_cname, self.pos))
#-------------------------------------------------------------------
#
}
""" % Naming.__dict__)
+
+generator_utility_code = UtilityCode(
+proto="""
+static PyObject *__Pyx_Generator_Next(PyObject *self);
+static PyObject *__Pyx_Generator_Send(PyObject *self, PyObject *value);
+static PyObject *__Pyx_Generator_Close(PyObject *self);
+static PyObject *__Pyx_Generator_Throw(PyObject *gen, PyObject *args, CYTHON_UNUSED PyObject *kwds);
+
+typedef PyObject *(*__pyx_generator_body_t)(PyObject *, PyObject *);
+""",
+impl="""
+static CYTHON_INLINE PyObject *__Pyx_Generator_SendEx(struct __pyx_Generator_object *self, PyObject *value)
+{
+ PyObject *retval;
+
+ if (self->is_running) {
+ PyErr_SetString(PyExc_ValueError,
+ "generator already executing");
+ return NULL;
+ }
+
+ if (self->resume_label == 0) {
+ if (value && value != Py_None) {
+ PyErr_SetString(PyExc_TypeError,
+ "can't send non-None value to a "
+ "just-started generator");
+ return NULL;
+ }
+ }
+
+ if (self->resume_label == -1) {
+ PyErr_SetNone(PyExc_StopIteration);
+ return NULL;
+ }
+
+ self->is_running = 1;
+ retval = self->body((PyObject *) self, value);
+ self->is_running = 0;
+
+ return retval;
+}
+
+static PyObject *__Pyx_Generator_Next(PyObject *self)
+{
+ return __Pyx_Generator_SendEx((struct __pyx_Generator_object *) self, Py_None);
+}
+
+static PyObject *__Pyx_Generator_Send(PyObject *self, PyObject *value)
+{
+ return __Pyx_Generator_SendEx((struct __pyx_Generator_object *) self, value);
+}
+
+static PyObject *__Pyx_Generator_Close(PyObject *self)
+{
+ struct __pyx_Generator_object *generator = (struct __pyx_Generator_object *) self;
+ PyObject *retval;
+#if PY_VERSION_HEX < 0x02050000
+ PyErr_SetNone(PyExc_StopIteration);
+#else
+ PyErr_SetNone(PyExc_GeneratorExit);
+#endif
+ retval = __Pyx_Generator_SendEx(generator, NULL);
+ if (retval) {
+ Py_DECREF(retval);
+ PyErr_SetString(PyExc_RuntimeError,
+ "generator ignored GeneratorExit");
+ return NULL;
+ }
+#if PY_VERSION_HEX < 0x02050000
+ if (PyErr_ExceptionMatches(PyExc_StopIteration))
+#else
+ if (PyErr_ExceptionMatches(PyExc_StopIteration)
+ || PyErr_ExceptionMatches(PyExc_GeneratorExit))
+#endif
+ {
+ PyErr_Clear(); /* ignore these errors */
+ Py_INCREF(Py_None);
+ return Py_None;
+ }
+ return NULL;
+}
+
+static PyObject *__Pyx_Generator_Throw(PyObject *self, PyObject *args, CYTHON_UNUSED PyObject *kwds)
+{
+ struct __pyx_Generator_object *generator = (struct __pyx_Generator_object *) self;
+ PyObject *typ;
+ PyObject *tb = NULL;
+ PyObject *val = NULL;
+
+ if (!PyArg_UnpackTuple(args, "throw", 1, 3, &typ, &val, &tb))
+ return NULL;
+ __Pyx_Raise(typ, val, tb);
+ return __Pyx_Generator_SendEx(generator, NULL);
+}
+""",
+proto_block='utility_code_proto_before_types',
+requires=[Nodes.raise_utility_code],
+)
projects / cython.git / blobdiff