Toolset for Dynamic Design Patterns in Python.
Project description
A set of tools for Dynamic Design Patterns in Python.
Install
Dyndesign is on the Python Package Index (PyPI):
pip install dyndesign
Overview
Merge two or more classes:
from dyndesign import mergeclasses
MergedClass = mergeclasses(Base, Ext1, Ext2, ...)
Decorate a method with one or more instance methods loaded at runtime:
from dyndesign import decoratewith
@decoratewith("decorator_1", "component.decorator_2", ...)
def decorated_method(self, ...):
...
Safely invoke functions or methods from a safezone context manager:
from dyndesign import safezone
with safezone():
...
function_possibly_non_existent()
...
Create and destroy Singleton classes:
from dyndesign import SingletonMeta
class Singleton(metaclass=SingletonMeta):
...
singleton_instance = Singleton(...)
same_singleton_instance = Singleton()
Singleton().destroy_singleton()
new_singleton_instance = Singleton(...)
Import classes dynamically using the path:
from dyndesign import importclass
ImportedClass = importclass("directory.module.class_name")
Merging Classes
Dyndesign provides API mergeclasses to merge two or more classes as if they were dictionaries, so that the merged class has the attributes and methods of the base class and of the extension classes. If two or more classes have the same attributes/methods, the attributes/methods from the rightmost classes (in the order in which the classes are passed to mergeclasses) overload the ones from the leftmost classes, similarly to what happens when merging dictionaries.
from dyndesign import mergeclasses
class Base:
def __init__(self, init_value):
self.param = init_value
def m1(self):
print(f"Method `m1` of class `Base`, and {self.param=}")
def m2(self):
print(f"Method `m2` of class `Base`")
class Ext:
def m1(self):
print(f"Method `m1` of class `Ext`, and {self.param=}")
MergedClass = mergeclasses(Base, Ext)
merged_instance = MergedClass("INITIAL VALUE")
merged_instance.m1()
merged_instance.m2()
# Method `m1` of class `Ext`, and self.param='INITIAL VALUE'
# Method `m2` of class `Base`
When a merged class is instantiated with arguments, the constructor of each merging class is invoked, since constructors are excluded from being overloaded. Also, arguments passed to each constructor are adaptively filtered based on the constructor signature so that each constructor takes just the arguments it requires, and no exception is raised for the exceeding arguments passed:
class A:
def __init__(self):
print("No argument passed to class `A`")
class B:
def __init__(self, a):
print(f"Argument {a=} passed to class `B`")
class C:
def __init__(self, a, b, kw1=None):
print(f"Argument {a=}, {b=} and {kw1=} passed to class `C`")
class D:
def __init__(self, kw2=None):
print(f"Argument {kw2=} passed to class `D`")
MergedClass = mergeclasses(A, B, C, D)
MergedClass("Alpha", "Beta", kw1="kwarg #1", kw2="kwarg #2")
# No argument passed to class `A`
# Argument a='Alpha' passed to class `B`
# Argument a='Alpha', b='Beta' and kw1='kwarg #1' passed to class `C`
# Argument kw2='kwarg #2' passed to class `D`
It is also possible to extend the same behavior of the constructor __init__ (i.e., all the methods from all the merged classes are invoked rather than being overloaded by the same name method from the rightmost class) to other methods. A list of method names whose instances have to be all invoked can be specified in the invoke_all argument of mergeclasses. Adaptive filtering of the arguments of the method instances is performed as well.
class E:
def method(self):
print("No argument passed to `method` of class `E`")
class F:
def method(self, a):
print(f"Argument {a=} passed to `method` of class `F`")
MergedClass = mergeclasses(E, F, invoke_all=["method"])
MergedClass().method("Alpha")
# No argument passed to `method` of class `E`
# Argument a='Alpha' passed to `method` of class `F`
Dynamic Decorators
Meta decorator decoratewith decorates a class method with one or more pipelined instance decorators (regardless whether they statically exist or not). The syntax of the dynamic decorators aims to get rid of the boilerplate for wrapping and returning the decorator code, leaving just the wrapper’s code. For example, dynamic decorators can be used to decorate a method from a base class with a method from an extension class:
from dyndesign import decoratewith
class Base:
@decoratewith("decorator")
def m(self):
print(f"Method `m` of class `Base`")
class Ext:
def decorator(self, func):
print("Beginning of method decoration from Ext.")
func(self)
print("End of method decoration from Ext.")
merged = mergeclasses(Base, Ext)()
merged.m()
# Beginning of method decoration from Ext.
# Method `m` of class `Base`
# End of method decoration from Ext.
If a decorator name is passed in the invoke_all argument of mergeclasses, then multiple decorator instances with the same name from different extension classes may be used in pipeline:
class Ext2:
def decorator(self, func):
print("Beginning of method decoration from Ext2.")
func(self)
print("End of method decoration from Ext2.")
merged = mergeclasses(Base, Ext, Ext2, invoke_all=["decorator"])()
merged.m()
# Beginning of method decoration from Ext.
# Beginning of method decoration from Ext2.
# Method `m` of class `Base`
# End of method decoration from Ext2.
# End of method decoration from Ext.
Arguments of decoratewith are loaded at runtime as properties of the variable ‘self’: a dynamic decorator can be, for example, a method of a component class. In case of dynamic decoration from a sub-instance of ‘self’, the instance object of the decorated method is passed to the decorator as the argument decorated_self. If a dynamic decorator is not found at runtime (e.g., because it is a method of an optional class that has not been merged), then the code execution proceeds normally, as shown below with the decorator non_existent_decorator:
class Base:
def __init__(self):
self.comp = Component()
@decoratewith("comp.decorator1", "comp.decorator2", "non_existent_decorator")
def m(self):
print("Method `m` of class `Base`")
class Component:
def __init__(self):
self.value = "Initial"
def decorator1(self, func, decorated_self):
print(f"Beginning of method decoration #1 ({self.value=})")
self.value = "Processed"
func(decorated_self)
print("End of method decoration #1")
def decorator2(self, func, decorated_self):
print(f"Beginning of method decoration #2 ({self.value=})")
func(decorated_self)
print("End of method decoration #2")
base = Base()
base.m()
# Beginning of method decoration #1 (self.value='Initial')
# Beginning of method decoration #2 (self.value='Processed')
# Method `m` of class `Base`
# End of method decoration #2
# End of method decoration #1
Safezone Context Manager
Any function or method that may or may not exist at runtime (e.g., methods of merged classes) can be invoked from Context Manager safezone in order to suppress the possible exceptions raised if the function or method is not found at runtime. Optionally, a fallback function/method can be also passed. If no function name(s) is passed as argument of safezone, then each function in the safe zone’s code is protected; if any function name(s) is passed, the protection is restricted to the functions having that/those name(s). For example, safezone can be used to safely call functions that may or may not exist at runtime:
from dyndesign import safezone
def fallback():
print("Fallback function")
def function_a():
print("Function `a`")
with safezone(fallback=fallback):
function_a()
non_existent_function()
# Function `a`
# Fallback function
A further example shows that safezone can be used to safely invoke methods of classes that may or may not be merged with other classes:
class Base:
def fallback(self):
print("Fallback method")
def m(self, class_desc):
print(f"Method `m` of {class_desc}")
with safezone("optional_method", fallback=self.fallback):
self.optional_method()
class ExtOptional:
def optional_method(self):
print("Optional method from class `ExtOptional`")
merged = mergeclasses(Base, ExtOptional)()
merged.m("merged class")
base = Base()
base.m("class `Base` standalone")
# Method `m` of merged class
# Optional method from class `ExtOptional`
# Method `m` of class `Base` standalone
# Fallback method
Invoking methods safely
As alternative to safezone context manager, safeinvoke can be used to safely invoke methods that may or may not exist at runtime. To this end, method m of class Base of the example above can be replaced as follows:
from dyndesign import safeinvoke
...
def m(self, class_desc):
print(f"Method `m` of {class_desc}")
safeinvoke("optional_method", self, fallback=self.fallback)
Singleton classes
Singleton classes can be swiftly created and destroyed with destroy_singleton:
from dyndesign import SingletonMeta
class Singleton(metaclass=SingletonMeta):
def __init__(self, instance_id = None):
if instance_id:
self.instance_id = instance_id
print(f"Created a {instance_id} instance of `Singleton`")
def where_points(self, object_name):
print(f"Object `{object_name}` points to the {self.instance_id} instance")
s_A = Singleton("first")
s_A.where_points("s_A")
s_B = Singleton()
s_B.where_points("s_B")
Singleton().destroy_singleton()
s_C = Singleton("second")
s_C.where_points("s_C")
# Created a first instance of `Singleton`
# Object `s_A` points to the first instance
# Object `s_B` points to the first instance
# Created a second instance of `Singleton`
# Object `s_C` points to the second instance
The class method destroy of SingletonMeta can be invoked to destroy all the Singleton classes at once. As a further alternative to the instance call destroy_singleton, the names of the Singleton classes to destroy can be passed to the class method destroy:
Singleton().destroy_singleton() # Destroy only `Singleton`
SingletonMeta.destroy() # Destroy all the singleton classes
SingletonMeta.destroy('Singleton1', 'Singleton2', 'Singleton3') # Destroy selectively
Importing classes dynamically
Classes can be imported dynamically using the package/class names or the path in dot-notation as shown below:
from dyndesign import importclass
ClassA = importclass('package_A', 'ClassA')
ClassB = importclass('directory_B.package_B.ClassB')
Running tests
To run the tests using your default python:
pip install -U pytest python3 -m pytest test
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