View of /DecoratorTools/peak/util/decorators.py
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Experimental support for Python 3 (tested clean on 3.1 & 3.2)
from types import FunctionType
import sys, os
__all__ = [
'decorate_class', 'metaclass_is_decorator', 'metaclass_for_bases',
'frameinfo', 'decorate_assignment', 'decorate', 'struct', 'classy',
'template_function', 'rewrap', 'cache_source', 'enclosing_frame',
'synchronized',
]
def decorate(*decorators):
"""Use Python 2.4 decorators w/Python 2.3+
Example::
class Foo(object):
decorate(classmethod)
def something(cls,etc):
\"""This is a classmethod\"""
You can pass in more than one decorator, and they are applied in the same
order that would be used for ``@`` decorators in Python 2.4.
This function can be used to write decorator-using code that will work with
both Python 2.3 and 2.4 (and up).
"""
if len(decorators)>1:
decorators = list(decorators)
decorators.reverse()
def callback(frame,k,v,old_locals):
for d in decorators:
v = d(v)
return v
return decorate_assignment(callback)
def enclosing_frame(frame=None, level=3):
"""Get an enclosing frame that skips DecoratorTools callback code"""
frame = frame or sys._getframe(level)
while frame.f_globals.get('__name__')==__name__: frame = frame.f_back
return frame
def name_and_spec(func):
from inspect import formatargspec, getargspec
funcname = func.__name__
if funcname=='<lambda>':
funcname = "anonymous"
args, varargs, kwargs, defaults = getargspec(func)
return funcname, formatargspec(args, varargs, kwargs)[1:-1]
def qname(func):
m = func.__module__
return m and m+'.'+func.__name__ or func.__name__
class Bomb:
def __str__(self):
raise RuntimeError("template functions must return a static string!")
bomb = Bomb()
def getbody(func):
from inspect import getargspec
args, varargs, kwargs, defaults = getargspec(func)
return func(*[bomb] * len(args))
try:
from sys import gettrace
tracers_for = lambda f: [f.f_trace, gettrace()]
except ImportError:
tracers_for = lambda f: [f.f_trace]
def with_metaclass(meta, *bases):
"""Python 2/3-compatible metaclass spelling; internal use only"""
class tmp(type):
def __new__(cls, name, _bases, cdict):
return meta(name, bases, cdict)
return type.__new__(tmp, 'tmp', (), {})
try:
old_build_class = __build_class__
except NameError:
# Python 2
from types import ClassType
NEXT, GLOBALS, DEFAULTS = 'next', 'func_globals', 'func_defaults'
else:
# Python 3
ClassType = type
NEXT, GLOBALS, DEFAULTS = '__next__', '__globals__', '__defaults__'
def apply_decorators(cls, advice):
if metaclass_is_decorator(advice):
cls = advice.callback(
apply_decorators(cls, advice.previousMetaclass)
)
return cls
def py3_build_class(func, name, *bases, **kw):
cls = old_build_class(func, name, *bases, **kw)
advice = cls.__dict__.get('__metaclass__', None)
decorated = apply_decorators(cls, advice)
if '__metaclass__' in cls.__dict__:
try:
del cls.__metaclass__
except TypeError:
pass
return decorated
getattr(__builtins__,'__dict__',__builtins__)[
'__build_class__'
] = py3_build_class
def apply_template(wrapper, func, *args, **kw):
funcname, argspec = name_and_spec(func)
wrapname, wrapspec = name_and_spec(wrapper)
body = wrapper.__doc__ or getbody(wrapper)
if not body:
raise RuntimeError(
"Missing docstring or empty return value from"
" %s(%s) - please switch the calling code from using docstrings"
" to return values" % (wrapname, wrapspec)
)
body = body.replace('%','%%').replace('$args','%(argspec)s')
body = """
def %(wrapname)s(%(wrapspec)s):
def %(funcname)s(%(argspec)s): """+body+"""
return %(funcname)s
"""
body %= locals()
filename = "<%s wrapping %s at 0x%08X>" % (qname(wrapper), qname(func), id(func))
d ={}
exec(compile(body, filename, "exec"), getattr(func, GLOBALS), d)
f = d[wrapname](func, *args, **kw)
cache_source(filename, body, f)
setattr(f, DEFAULTS, getattr(func, DEFAULTS))
f.__doc__ = func.__doc__
f.__dict__ = func.__dict__
return f
def rewrap(func, wrapper):
"""Create a wrapper with the signature of `func` and a body of `wrapper`
Example::
def before_and_after(func):
def decorated(*args, **kw):
print "before"
try:
return func(*args, **kw)
finally:
print "after"
return rewrap(func, decorated)
The above function is a normal decorator, but when users run ``help()``
or other documentation tools on the returned wrapper function, they will
see a function with the original function's name, signature, module name,
etc.
This function is similar in use to the ``@template_function`` decorator,
but rather than generating the entire decorator function in one calling
layer, it simply generates an extra layer for signature compatibility.
NOTE: the function returned from ``rewrap()`` will have the same attribute
``__dict__`` as the original function, so if you need to set any function
attributes you should do so on the function returned from ``rewrap()``
(or on the original function), and *not* on the wrapper you're passing in
to ``rewrap()``.
"""
def rewrap(__original, __decorated):
return """return __decorated($args)"""
return apply_template(rewrap, func, wrapper)
if sys.version<"2.5":
# We'll need this for monkeypatching linecache
def checkcache(filename=None):
"""Discard cache entries that are out of date.
(This is not checked upon each call!)"""
if filename is None:
filenames = linecache.cache.keys()
else:
if filename in linecache.cache:
filenames = [filename]
else:
return
for filename in filenames:
size, mtime, lines, fullname = linecache.cache[filename]
if mtime is None:
continue # no-op for files loaded via a __loader__
try:
stat = os.stat(fullname)
except os.error:
del linecache.cache[filename]
continue
if size != stat.st_size or mtime != stat.st_mtime:
del linecache.cache[filename]
def _cache_lines(filename, lines, owner=None):
if owner is None:
owner = filename
else:
from weakref import ref
owner = ref(owner, lambda r: linecache and linecache.cache.__delitem__(filename))
global linecache; import linecache
if sys.version<"2.5" and linecache.checkcache.__module__!=__name__:
linecache.checkcache = checkcache
linecache.cache[filename] = 0, None, lines, owner
def cache_source(filename, source, owner=None):
_cache_lines(filename, source.splitlines(True), owner)
def template_function(wrapper=None):
"""Decorator that uses its wrapped function's return value as a template
Example::
def before_and_after(func):
@template_function
def wrap(__func, __message):
return '''
print "before", __message
try:
return __func($args)
finally:
print "after", __message
'''
return wrap(func, "test")
The above code will return individually-generated wrapper functions whose
signature, defaults, ``__name__``, ``__module__``, and ``func_globals``
match those of the wrapped functions.
You can use define any arguments you wish in the wrapping function, as long
as the first argument is the function to be wrapped, and the arguments are
named so as not to conflict with the arguments of the function being
wrapped. (i.e., they should have relatively unique names.)
Note that the function body will *not* have access to the globals of the
calling module, as it is compiled with the globals of the *wrapped*
function! Thus, any non-builtin values that you need in the wrapper should
be passed in as arguments to the template function.
(Also, the body text must begin with a newline as shown, and be indented
at least 2 spaces.)
"""
if wrapper is None:
return decorate_assignment(lambda f,k,v,o: template_function(v))
return apply_template.__get__(wrapper)
def struct(*mixins, **kw):
"""Turn a function into a simple data structure class
This decorator creates a tuple subclass with the same name and docstring as
the decorated function. The class will have read-only properties with the
same names as the function's arguments, and the ``repr()`` of its instances
will look like a call to the original function. The function should return
a tuple of values in the same order as its argument names, as it will be
used by the class' constructor. The function can perform validation, add
defaults, and/or do type conversions on the values.
If the function takes a ``*``, argument, it should flatten this argument
into the result tuple, e.g.::
@struct()
def pair(first, *rest):
return (first,) + rest
The ``rest`` property of the resulting class will thus return a tuple for
the ``*rest`` arguments, and the structure's ``repr()`` will reflect the
way it was created.
The ``struct()`` decorator takes optional mixin classes (as positional
arguments), and dictionary entries (as keyword arguments). The mixin
classes will be placed before ``tuple`` in the resulting class' bases, and
the dictionary entries will be placed in the class' dictionary. These
entries take precedence over any default entries (e.g. methods, properties,
docstring, etc.) that are created by the ``struct()`` decorator.
"""
def callback(frame, name, func, old_locals):
def __new__(cls, *args, **kw):
result = func(*args, **kw)
if type(result) is tuple:
return tuple.__new__(cls, (cls,)+result)
else:
return result
def __repr__(self):
return name+tuple.__repr__(self[1:])
import inspect
args, star, dstar, defaults = inspect.getargspec(func)
d = dict(
__new__ = __new__, __repr__ = __repr__, __doc__=func.__doc__,
__module__ = func.__module__, __args__ = args, __star__ = star,
__slots__ = [],
)
for p,a in enumerate(args):
if isinstance(a,str):
d[a] = property(lambda self, p=p+1: self[p])
if star:
d[star] = property(lambda self, p=len(args)+1: self[p:])
d.update(kw)
return type(name, mixins+(tuple,), d)
return decorate_assignment(callback)
def synchronized(func=None):
"""Create a method synchronized by first argument's ``__lock__`` attribute
If the object has no ``__lock__`` attribute at run-time, the wrapper will
attempt to add one by creating a ``threading.RLock`` and adding it to the
object's ``__dict__``. If ``threading`` isn't available, it will use a
``dummy_threading.RLock`` instead. Neither will be imported unless the
method is called on an object that doesn't have a ``__lock__``.
This decorator can be used as a standard decorator (e.g. ``@synchronized``)
or as a Python 2.3-compatible decorator by calling it with no arguments
(e.g. ``[synchronized()]``).
"""
if func is None:
return decorate_assignment(lambda f,k,v,o: synchronized(v))
from inspect import getargspec
first_arg = getargspec(func)[0][0]
def wrap(__func):
return '''
try:
lock = $self.__lock__
except AttributeError:
try:
from threading import RLock
except ImportError:
from dummy_threading import RLock
lock = $self.__dict__.setdefault('__lock__',RLock())
lock.acquire()
try:
return __func($args)
finally:
lock.release()'''.replace('$self', first_arg)
return apply_template(wrap, func)
def frameinfo(frame):
"""Return (kind, module, locals, globals) tuple for a frame
'kind' is one of "exec", "module", "class", "function call", or "unknown".
"""
f_locals = frame.f_locals
f_globals = frame.f_globals
sameNamespace = f_locals is f_globals
hasModule = '__module__' in f_locals
hasName = '__name__' in f_globals
sameName = hasModule and hasName
sameName = sameName and f_globals['__name__']==f_locals['__module__']
module = hasName and sys.modules.get(f_globals['__name__']) or None
namespaceIsModule = module and module.__dict__ is f_globals
if not namespaceIsModule:
# some kind of funky exec
kind = "exec"
if hasModule and not sameNamespace:
kind="class"
elif sameNamespace and not hasModule:
kind = "module"
elif sameName and not sameNamespace:
kind = "class"
elif not sameNamespace:
kind = "function call"
else:
# How can you have f_locals is f_globals, and have '__module__' set?
# This is probably module-level code, but with a '__module__' variable.
kind = "unknown"
return kind,module,f_locals,f_globals
def decorate_class(decorator, depth=2, frame=None, allow_duplicates=False):
"""Set up `decorator` to be passed the containing class upon creation
This function is designed to be called by a decorator factory function
executed in a class suite. The factory function supplies a decorator that
it wishes to have executed when the containing class is created. The
decorator will be given one argument: the newly created containing class.
The return value of the decorator will be used in place of the class, so
the decorator should return the input class if it does not wish to replace
it.
The optional `depth` argument to this function determines the number of
frames between this function and the targeted class suite. `depth`
defaults to 2, since this skips the caller's frame. Thus, if you call this
function from a function that is called directly in the class suite, the
default will be correct, otherwise you will need to determine the correct
depth value yourself. Alternately, you can pass in a `frame` argument to
explicitly indicate what frame is doing the class definition.
This function works by installing a special class factory function in
place of the ``__metaclass__`` of the containing class. Therefore, only
decorators *after* the last ``__metaclass__`` assignment in the containing
class will be executed. Thus, any classes using class decorators should
declare their ``__metaclass__`` (if any) *before* specifying any class
decorators, to ensure that all class decorators will be applied."""
frame = enclosing_frame(frame, depth+1)
kind, module, caller_locals, caller_globals = frameinfo(frame)
if kind != "class":
raise SyntaxError(
"Class decorators may only be used inside a class statement"
)
elif not allow_duplicates and has_class_decorator(decorator, None, frame):
return
previousMetaclass = caller_locals.get('__metaclass__')
defaultMetaclass = caller_globals.get('__metaclass__', ClassType)
def advise(name,bases,cdict,**kw):
if '__metaclass__' in cdict:
del cdict['__metaclass__']
if previousMetaclass is None:
if bases:
# find best metaclass or use global __metaclass__ if no bases
meta = metaclass_for_bases(bases)
else:
meta = defaultMetaclass
elif metaclass_is_decorator(previousMetaclass):
# special case: we can't compute the "true" metaclass here,
# so we need to invoke the previous metaclass and let it
# figure it out for us (and apply its own advice in the process)
meta = previousMetaclass
else:
meta = metaclass_for_bases(bases, previousMetaclass)
newClass = meta(name,bases,cdict,**kw)
# this lets the decorator replace the class completely, if it wants to
return decorator(newClass)
# introspection data only, not used by inner function
# Note: these attributes cannot be renamed or it will break compatibility
# with zope.interface and any other code that uses this decoration protocol
advise.previousMetaclass = previousMetaclass
advise.callback = decorator
# install the advisor
caller_locals['__metaclass__'] = advise
def metaclass_is_decorator(ob):
"""True if 'ob' is a class advisor function"""
return isinstance(ob,FunctionType) and hasattr(ob,'previousMetaclass')
def iter_class_decorators(depth=2, frame=None):
frame = enclosing_frame(frame, depth+1)
m = frame.f_locals.get('__metaclass__')
while metaclass_is_decorator(m):
yield getattr(m, 'callback', None)
m = m.previousMetaclass
def has_class_decorator(decorator, depth=2, frame=None):
return decorator in iter_class_decorators(0, frame or sys._getframe(depth))
def metaclass_for_bases(bases, explicit_mc=None):
"""Determine metaclass from 1+ bases and optional explicit __metaclass__"""
meta = [getattr(b,'__class__',type(b)) for b in bases]
if explicit_mc is not None:
# The explicit metaclass needs to be verified for compatibility
# as well, and allowed to resolve the incompatible bases, if any
meta.append(explicit_mc)
if len(meta)==1:
# easy case
return meta[0]
classes = [c for c in meta if c is not ClassType]
candidates = []
for m in classes:
for n in classes:
if issubclass(n,m) and m is not n:
break
else:
# m has no subclasses in 'classes'
if m in candidates:
candidates.remove(m) # ensure that we're later in the list
candidates.append(m)
if not candidates:
# they're all "classic" classes
return ClassType
elif len(candidates)>1:
# We could auto-combine, but for now we won't...
raise TypeError("Incompatible metatypes",bases)
# Just one, return it
return candidates[0]
def decorate_assignment(callback, depth=2, frame=None):
"""Invoke 'callback(frame,name,value,old_locals)' on next assign in 'frame'
The frame monitored is determined by the 'depth' argument, which gets
passed to 'sys._getframe()'. When 'callback' is invoked, 'old_locals'
contains a copy of the frame's local variables as they were before the
assignment took place, allowing the callback to access the previous value
of the assigned variable, if any. The callback's return value will become
the new value of the variable. 'name' is the name of the variable being
created or modified, and 'value' is its value (the same as
'frame.f_locals[name]').
This function also returns a decorator function for forward-compatibility
with Python 2.4 '@' syntax. Note, however, that if the returned decorator
is used with Python 2.4 '@' syntax, the callback 'name' argument may be
'None' or incorrect, if the 'value' is not the original function (e.g.
when multiple decorators are used).
"""
frame = enclosing_frame(frame, depth+1)
oldtrace = tracers_for(frame)
old_locals = frame.f_locals.copy()
def tracer(frm,event,arg):
if event=='call':
# We don't want to trace into any calls
if oldtrace[0] is not None:
# ...but give the previous tracer a chance to, if it wants
return oldtrace[0](frm,event,arg)
else:
return None
try:
if frm is frame and event !='exception':
# Aha, time to check for an assignment...
for k,v in frm.f_locals.items():
if k not in old_locals or old_locals[k] is not v:
break
else:
# No luck, keep tracing
return tracer
# Got it, fire the callback, then get the heck outta here...
frm.f_locals[k] = callback(frm,k,v,old_locals)
uninstall()
finally:
# Give the previous tracer a chance to run before we return
if oldtrace[0] is not None:
# And allow it to replace our idea of the "previous" tracer
oldtrace[0] = oldtrace[0](frm,event,arg)
return oldtrace[0]
def uninstall():
# Unlink ourselves from the trace chain.
frame.f_trace = oldtrace[0]
if installed:
sys.settrace(oldtrace[-1])
# Install the trace function
frame.f_trace = tracer
if oldtrace[-1] is None: # No need to change global if already tracing
sys.settrace(tracer)
installed = True
else:
installed = False
def do_decorate(f):
# Python 2.4 '@' compatibility; call the callback
uninstall()
frame = sys._getframe(1)
return callback(
frame, getattr(f,'__name__',None), f, frame.f_locals
)
return do_decorate
def super_next(cls, attr):
for c in cls.__mro__:
if attr in c.__dict__:
meth = getattr(c, attr)
yield getattr(meth, 'im_func', meth)
# Python 2.6 and above mix ABCMeta into various random places :-(
try:
from abc import ABCMeta as base
except ImportError:
base = type
class classy_class(base):
"""Metaclass that delegates selected operations back to the class"""
def __new__(meta, name, bases, cdict):
cls = super(classy_class, meta).__new__(meta, name, bases, cdict)
supr = getattr(super_next(cls, '__class_new__'), NEXT)
return supr()(meta, name, bases, cdict, supr)
def __init__(cls, name, bases, cdict):
supr = getattr(super_next(cls, '__class_init__'), NEXT)
return supr()(cls, name, bases, cdict, supr)
def __call__(cls, *args, **kw):
return cls.__class_call__(*args, **kw)
if base is not type:
# Our instances do not support ABC-ness
def register(*args): raise NotImplementedError
__instancecheck__ = type.__dict__['__instancecheck__']
__subclasscheck__ = type.__dict__['__subclasscheck__']
class classy(with_metaclass(classy_class)):
"""Base class for classes that want to be their own metaclass"""
__slots__ = ()
def __class_new__(meta, name, bases, cdict, supr):
return type.__new__(meta, name, bases, cdict)
def __class_init__(cls, name, bases, cdict, supr):
return type.__init__(cls, name, bases, cdict)
def __class_call__(cls, *args, **kw):
return type.__call__(cls, *args, **kw)
__class_call__ = classmethod(__class_call__)