def emit_yield(builder: IRBuilder, val: Value, line: int) -> Value:
retval = builder.coerce(val, builder.ret_types[-1], line)
cls = builder.fn_info.generator_class
# Create a new block for the instructions immediately following the yield expression, and
# set the next label so that the next time '__next__' is called on the generator object,
# the function continues at the new block.
next_block = BasicBlock()
next_label = len(cls.continuation_blocks)
cls.continuation_blocks.append(next_block)
builder.assign(cls.next_label_target, builder.add(LoadInt(next_label)), line)
builder.add(Return(retval))
builder.activate_block(next_block)
add_raise_exception_blocks_to_generator_class(builder, line)
assert cls.send_arg_reg is not None
return cls.send_arg_reg
def gen_func_item(builder: IRBuilder,
fitem: FuncItem,
name: str,
sig: FuncSignature,
cdef: Optional[ClassDef] = None,
) -> Tuple[FuncIR, Optional[Value]]:
"""Generate and return the FuncIR for a given FuncDef.
If the given FuncItem is a nested function, then we generate a
callable class representing the function and use that instead of
the actual function. if the given FuncItem contains a nested
function, then we generate an environment class so that inner
nested functions can access the environment of the given FuncDef.
Consider the following nested function:
def a() -> None:
def b() -> None:
def c() -> None:
return None
return None
return None
The classes generated would look something like the following.
has pointer to +-------+
+--------------------------> | a_env |
| +-------+
| ^
| | has pointer to
+-------+ associated with +-------+
| b_obj | -------------------> | b_env |
+-------+ +-------+
^
|
+-------+ has pointer to |
| c_obj | --------------------------+
+-------+
"""
# TODO: do something about abstract methods.
func_reg = None # type: Optional[Value]
# We treat lambdas as always being nested because we always generate
# a class for lambdas, no matter where they are. (It would probably also
# work to special case toplevel lambdas and generate a non-class function.)
is_nested = fitem in builder.nested_fitems or isinstance(fitem, LambdaExpr)
contains_nested = fitem in builder.encapsulating_funcs.keys()
is_decorated = fitem in builder.fdefs_to_decorators
in_non_ext = False
class_name = None
if cdef:
ir = builder.mapper.type_to_ir[cdef.info]
in_non_ext = not ir.is_ext_class
class_name = cdef.name
builder.enter(FuncInfo(fitem, name, class_name, gen_func_ns(builder),
is_nested, contains_nested, is_decorated, in_non_ext))
# Functions that contain nested functions need an environment class to store variables that
# are free in their nested functions. Generator functions need an environment class to
# store a variable denoting the next instruction to be executed when the __next__ function
# is called, along with all the variables inside the function itself.
if builder.fn_info.contains_nested or builder.fn_info.is_generator:
setup_env_class(builder)
if builder.fn_info.is_nested or builder.fn_info.in_non_ext:
setup_callable_class(builder)
if builder.fn_info.is_generator:
# Do a first-pass and generate a function that just returns a generator object.
gen_generator_func(builder)
blocks, env, ret_type, fn_info = builder.leave()
func_ir, func_reg = gen_func_ir(builder, blocks, sig, env, fn_info, cdef)
# Re-enter the FuncItem and visit the body of the function this time.
builder.enter(fn_info)
setup_env_for_generator_class(builder)
load_outer_envs(builder, builder.fn_info.generator_class)
if builder.fn_info.is_nested and isinstance(fitem, FuncDef):
setup_func_for_recursive_call(builder, fitem, builder.fn_info.generator_class)
create_switch_for_generator_class(builder)
add_raise_exception_blocks_to_generator_class(builder, fitem.line)
else:
load_env_registers(builder)
gen_arg_defaults(builder)
if builder.fn_info.contains_nested and not builder.fn_info.is_generator:
finalize_env_class(builder)
builder.ret_types[-1] = sig.ret_type
# Add all variables and functions that are declared/defined within this
# function and are referenced in functions nested within this one to this
# function's environment class so the nested functions can reference
# them even if they are declared after the nested function's definition.
# Note that this is done before visiting the body of this function.
env_for_func = builder.fn_info # type: Union[FuncInfo, ImplicitClass]
if builder.fn_info.is_generator:
env_for_func = builder.fn_info.generator_class
elif builder.fn_info.is_nested or builder.fn_info.in_non_ext:
env_for_func = builder.fn_info.callable_class
if builder.fn_info.fitem in builder.free_variables:
# Sort the variables to keep things deterministic
for var in sorted(builder.free_variables[builder.fn_info.fitem],
key=lambda x: x.name):
if isinstance(var, Var):
rtype = builder.type_to_rtype(var.type)
builder.add_var_to_env_class(var, rtype, env_for_func, reassign=False)
if builder.fn_info.fitem in builder.encapsulating_funcs:
for nested_fn in builder.encapsulating_funcs[builder.fn_info.fitem]:
if isinstance(nested_fn, FuncDef):
# The return type is 'object' instead of an RInstance of the
# callable class because differently defined functions with
# the same name and signature across conditional blocks
# will generate different callable classes, so the callable
# class that gets instantiated must be generic.
builder.add_var_to_env_class(
nested_fn, object_rprimitive, env_for_func, reassign=False
)
builder.accept(fitem.body)
builder.maybe_add_implicit_return()
if builder.fn_info.is_generator:
populate_switch_for_generator_class(builder)
blocks, env, ret_type, fn_info = builder.leave()
if fn_info.is_generator:
add_methods_to_generator_class(builder, fn_info, sig, env, blocks, fitem.is_coroutine)
else:
func_ir, func_reg = gen_func_ir(builder, blocks, sig, env, fn_info, cdef)
calculate_arg_defaults(builder, fn_info, env, func_reg)
return (func_ir, func_reg)
