说,我们在Scheme
中有以下代码(define cc #f)
(define bar 0)
(define (func)
(print "This should show only once")
(call/cc (lambda (k) (set! cc k)))
(print bar)
(set! bar (+ bar 1)))
(define (g)
(func)
(print "This should show multiple times"))
(g)
(cc)
打印类似
的内容This should show only once
0
This should show multiple times
1
This should show multiple times
假设我们想在Python中做同样的事情。 http://wiki.c2.com/?ContinuationsInPython这种方法不起作用,因为它们只保存代码而不保存堆栈。我试图在Python中实现我的call/cc
版本,保存并恢复堆栈上下文。我并非100%确定我已正确实施了延续逻辑,但现在这并不重要。
我的想法是在callcc
构造函数中保存调用Continuation
及其调用者的函数的堆栈和指令指针,然后在继续的__call__
方法中重置指令保存的堆栈帧中的指针,指向当前堆栈帧f_back
指向已保存堆栈帧的指针,并返回神奇地出现在调用callcc
的函数中。
问题在于,即使traceback.print_stack()
的输出显示当前堆栈已被替换,代码仍然执行,好像我根本没有触及当前堆栈。这是我的实施https://ideone.com/kGchEm
import inspect
import types
import ctypes
import sys
import traceback
frameobject_fields = [
# PyObject_VAR_HEAD
("ob_refcnt", ctypes.c_int64),
("ob_type", ctypes.py_object),
("ob_size", ctypes.c_ssize_t),
# struct _frame *f_back; /* previous frame, or NULL */
("f_back", ctypes.c_void_p),
# PyCodeObject *f_code; /* code segment */
("f_code", ctypes.c_void_p),
# PyObject *f_builtins; /* builtin symbol table (PyDictObject) */
("f_builtins", ctypes.py_object),
# PyObject *f_globals; /* global symbol table (PyDictObject) */
("f_globals", ctypes.py_object),
####
("f_locals", ctypes.py_object),
("f_valuestack", ctypes.POINTER(ctypes.py_object)),
("f_stacktop", ctypes.POINTER(ctypes.py_object)),
("f_trace", ctypes.py_object),
("f_exc_type", ctypes.py_object),
("f_exc_value", ctypes.py_object),
("f_exc_traceback", ctypes.py_object),
("f_tstate", ctypes.c_void_p),
("f_lasti", ctypes.c_int),
]
if hasattr(sys, "getobjects"):
# This python was compiled with debugging enabled.
frameobject_fields = [
("_ob_next", ctypes.c_void_p),
("_ob_prev", ctypes.c_void_p),
] + frameobject_fields
class PyFrameObject(ctypes.Structure):
_fields_ = frameobject_fields
class Continuation:
def __init__(self, frame):
self.frame = frame
self.lasti = frame.f_lasti
self.lastis = []
frame = frame.f_back
while frame is not None:
self.lastis.append(frame.f_lasti)
frame = frame.f_back
def __call__(self):
print('\nbefore')
traceback.print_stack()
cur_frame = PyFrameObject.from_address(id(inspect.currentframe()))
PyFrameObject.from_address(cur_frame.f_back).ob_refcnt -= 1
cur_frame.f_back = id(self.frame)
PyFrameObject.from_address(id(self.frame)).ob_refcnt += 1
frame = self.frame
_frame = PyFrameObject.from_address(id(frame))
_frame.f_lasti = self.lasti + 4
frame = frame.f_back
for lasti in self.lastis:
if len(frame.f_code.co_code) != frame.f_lasti + 2:
break
_frame = PyFrameObject.from_address(id(frame))
_frame.f_lasti = lasti + 4
frame = frame.f_back
print('\nafter')
traceback.print_stack()
def callcc(f):
f(Continuation(inspect.currentframe().f_back))
cc = None
def func():
bar = 0
print("This should show only once")
def save_cont(k):
global cc
cc = k
callcc(save_cont)
print(bar)
bar += 1
def g():
func()
print("This should show multiple times")
sys.stderr = sys.stdout
g()
cc()
答案 0 :(得分:0)
问题是标准解释器 - CPython - 是一个堆栈解释器,即每次调用Python函数都会导致解释器内的递归调用。因此,Python .f_back
对象只是视图(f_back
是一个只读属性,有充分理由)C堆栈帧,没有必要更改{ {1}}指针。
如果你真的想操纵堆栈,你必须编写一个C模块,就像greenlet模块一样。
Goog运气好!
答案 1 :(得分:0)
This answer很好地解释了为什么很难捕获Python解释器的状态。 This package为您做到了。它没有实现call / cc,但确实实现了longjmp和setjmp,这只是远离call / cc的语法。