Private Attribute (c++ implementation)
Introduction
This package provide a way to create the private attribute like "C++" does.
All Base API
from private_attribute import (PrivateAttrBase, PrivateWrapProxy) # 1 Import public API
def my_generate_func(obj_id, attr_name): # 2 Optional: custom name generator
return f"_hidden_{obj_id}_{attr_name}"
class MyClass(PrivateAttrBase, private_func=my_generate_func): # 3 Inherit + optional custom generator
__private_attrs__ = ['a', 'b', 'c', 'result', 'conflicted_name'] # 4 Must declare all private attrs
def __init__(self):
self.a = 1
self.b = 2
self.c = 3
self.result = 42 # deliberately conflicts with internal names
# Normal methods can freely access private attributes
def public_way(self):
print(self.a, self.b, self.c)
# Real-world case: method wrapped by multiple decorators
@PrivateWrapProxy(memoize()) # 5 Apply any decorator safely
@PrivateWrapProxy(login_required()) # 5 Stack as many as needed
@PrivateWrapProxy(rate_limit(calls=10)) # 5
def expensive_api_call(self, x): # First definition (will be wrapped)
def inner(...):
return some_implementation(self.a, self.b, self.c, x)
inner(...)
return heavy_computation(self.a, self.b, self.c, x)
# Fix decorator order + resolve name conflicts
@PrivateWrapProxy(expensive_api_call.result.name2, expensive_api_call) # 6 Chain .result to push decorators down
@PrivateWrapProxy(expensive_api_call.result.name1, expensive_api_call) # 6 Resolve conflict with internal names
def expensive_api_call(self, x): # Final real implementation
return heavy_computation(self.a, self.b, self.c, x)
# ====================== Usage ======================
obj = MyClass()
obj.public_way() # prints: 1 2 3
print(hasattr(obj, 'a')) # False – truly hidden from outside
print(obj.expensive_api_call(10)) # works with all decorators applied
| # | API | Purpose | Required? |
|---|---|---|---|
| 1 | PrivateAttrBase | Base class – must inherit | Yes |
| 1 | PrivateWrapProxy | Decorator wrapper for arbitrary decorators | When needed |
| 2 | private_func=callable | Custom hidden-name generator | Optional |
| 3 | Pass private_func in class definition | Same as above | Optional |
| 4 | __private_attrs__ list | Declare which attributes are private | Optional (changed in 2.1.4) |
| 5 | @PrivateWrapProxy(...) | Make any decorator compatible with private attributes | When needed |
| 6 | method.result.xxx chain + dummy wrap | Fix decorator order and name conflicts | When needed |
Usage
This is a simple usage about the module:
from private_attribute import PrivateAttrBase
class MyClass(PrivateAttrBase):
__private_attrs__ = ['a', 'b', 'c']
def __init__(self):
self.a = 1
self.b = 2
self.c = 3
def public_way(self):
print(self.a, self.b, self.c)
obj = MyClass()
obj.public_way() # (1, 2, 3)
print(hasattr(obj, 'a')) # False
print(hasattr(obj, 'b')) # False
print(hasattr(obj, 'c')) # False
All of the attributes in __private_attrs__ will be hidden from the outside world, and stored by another name.
You can use your function to generate the name. It needs the id of the obj and the name of the attribute:
def my_generate_func(obj_id, attr_name):
return some_string
class MyClass(PrivateAttrBase, private_func=my_generate_func):
__private_attrs__ = ['a', 'b', 'c']
def __init__(self):
self.a = 1
self.b = 2
self.c = 3
def public_way(self):
print(self.a, self.b, self.c)
obj = MyClass()
obj.public_way() # (1, 2, 3)
If the method will be decorated, the property, classmethod and staticmethod will be supported.
For the other, you can use the PrivateWrapProxy to wrap the function:
from private_attribute import PrivateAttrBase, PrivateWrapProxy
class MyClass(PrivateAttrBase):
__private_attrs__ = ['a', 'b', 'c']
@PrivateWrapProxy(decorator1())
@PrivateWrapProxy(decorator2())
def method1(self):
...
@PrivateWrapProxy(method1.attr_name, method1) # Use the argument "method1" to save old func
def method1(self):
...
@PrivateWrapProxy(decorator3())
def method2(self):
...
@PrivateWrapProxy(method2.attr_name, method2) # Use the argument "method2" to save old func
def method2(self):
...
The PrivateWrapProxy is a decorator, and it will wrap the function with the decorator. When it decorates the method, it returns a _PrivateWrap object.
The _PrivateWrap has the public api result and funcs. result returns the original decoratored result and funcs returns the tuple of the original functions.
from private_attribute import PrivateAttrBase, PrivateWrapProxy
class MyClass(PrivateAttrBase):
__private_attrs__ = ['a', 'b', 'c']
@PrivateWrapProxy(decorator1())
@PrivateWrapProxy(decorator2())
def method1(self):
...
@PrivateWrapProxy(method1.result.conflict_attr_name1, method1) # Use the argument "method1" to save old func
def method1(self):
...
@PrivateWrapProxy(method1.result.conflict_attr_name2, method1)
def method1(self):
...
@PrivateWrapProxy(decorator3())
def method2(self):
Advanced API
define your metaclass based on one metaclass
You can define your metaclass based on one metaclass:
from abc import ABCMeta, abstractmethod
import private_attribute
class PrivateAbcMeta(ABCMeta):
def __new__(cls, name, bases, attrs, **kwargs):
with private_attribute.prepare(name, bases, attrs, **kwargs) as tmp: # In 2.2.3 it support using "with"
typ = super().__new__(cls, temp.name, temp.bases, temp.attrs, **temp.kwds)
private_attribute.postprocess(typ, temp) # or tmp.postprocess(typ)
return typ
private_attribute.register_metaclass(PrivateAbcMeta)
By this way you create a metaclass both can behave as ABC and private attribute:
class MyClass(metaclass=PrivateAbcMeta):
__private_attrs__ = ()
__slots__ = ()
@abstractmethod
def my_function(self): ...
class MyImplement(MyClass):
__private_attrs__ = ("_a",)
def __init__(self, value=1):
self._a = value
def my_function(self):
return self._a
Finally:
>>> a = MyImplement(1)
>>> a.my_function()
1
>>> a._a
Traceback (most recent call last):
File "<pyshell#2>", line 1, in <module>
a._a
AttributeError: private attribute
>>> MyClass()
Traceback (most recent call last):
File "<pyshell#3>", line 1, in <module>
MyClass()
TypeError: Can't instantiate abstract class MyClass without an implementation for abstract method 'my_function'
Notes
All of the private attributes class must contain the(changed in 2.1.4)__private_attrs__attribute.- The
__private_attrs__attribute must be a sequence of strings or just one string. - You cannot define the name which in
__slots__to__private_attrs__. - When you define
__slots__and__private_attrs__in one class, the attributes in__private_attrs__can also be defined in the methods, even though they are not in__slots__. - All of the object that is the instance of the class "PrivateAttrBase" or its subclass are default to be unable to be pickled.
- Finally the attributes' names in
__private_attrs__will be change to a tuple with two hash. - Finally the
_PrivateWrapobject will be recoveried to the original object. - Don't use a decorator which will return the
_PrivateWrapinPrivateWrapProxywhich will raiseTypeError. - One class defined in another class cannot use another class's private attribute.
- One parent class defined an attribute which not in
__private_attrs__or not aPrivateAttrTypeinstance, the child class shouldn't contain the attribute in its__private_attrs__. - Since 2.1.0: the code of a subclass can no longer access the private attributes of its parent classes - a parent's private attribute is only reachable from the parent's own code, or from a class that declares the same name in its own
__private_attrs__. - Since 2.1.0: if a subclass declares a name in its own
__private_attrs__that is also private to a parent, the two are stored separately (instance attributes per declaring class, class-level attributes per class). Class-level resolution is per-subject through the parent's code: reading the name on a subclass subject returns the subclass's own value, and the parent's own value is untouched. - Since 2.2.0: a subclass must NOT define an attribute in its namespace (class body) whose name is private to a parent class, unless that name is declared in its own
__private_attrs__or the class opts in withuse_parents=True. - Since 2.2.0: pass
use_parents=Truein the class definition to inherit all parent classes' private attribute names into the subclass's own private-attribute set. The subclass's code can then read/write those names, but the values are stored in the subclass's own storage (they never overwrite the parent's own values). The Python-level__private_attrs__tuple is left unchanged; only the internal private-attribute name set is merged. Default isFalse. - CPython may change "tp_getattro", "tp_setattro" and so on when you change the attribute "__getattribute__", "__setattr__" and so on. If you are fear about it, you can use
ensure_typeto reset those tp slots. For the other metaclasses, you can useensure_metaclassto reset those tp slots. Also, don't set those methods on these classes in your code. private_attribute.register_metaclassmust be called with the metaclass which supports weakref.- Don't set
__static_attributes__in private attribute class, or it will be removed. - After 2.2.1, when
preparewas called, it will lock the creation of new private attribute type. There will be only one private attribute type in building (type.__new__) at the same time. Callpostprocessto unlock it. If build failed, the lock will be released automatically. - After 2.2.3, it is recommend to use "with" on
private_attribute.prepareandprivate_attribute.postprocessto ensure the lock is released.
License
MIT
Requirement
This package require the c++ module "picosha2" to compute the sha256 hash.
Support
Now it only support Cpython.
1 maintainer
Metadata
1 maintainer
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