目录
- 定义插件管理器
- 定义元类
- 定义元类的一个抽象派生类
- 定义装饰器
- 单元测试
- 参考
本文提供了一种插件类的实现方案。
定义插件管理器
插件管理器用于注册、销毁、执行插件。
import abc
from functools import wraps
from typing import Callable, Dict
from pydantic import (
BaseModel,
validate_arguments,
ValidationError as PydanticValidationError,
)
def import_string(dotted_path: str) -> Callable:
\”\”\”Import a dotted module path and return the attribute/class designated by the
last name in the path. Raise ImportError if the import failed.
Args:
dotted_path: 字符串表示的模块类，module.class
Returns:
返回加载的模块中的对象
\”\”\”
try:
module_path, class_name = dotted_path.rsplit(\”.\”, 1)
except ValueError:
raise ImportError(\”{} doesn\’t look like a module path\”.format(dotted_path))
module: ModuleType = import_module(module_path)
try:
# 返回模块中的类
return getattr(module, class_name)
except AttributeError:
raise ImportError(
\’Module \”{}\” does not define a \”{}\” attribute/class\’.format(
module_path, class_name
)
)
class FunctionsManager:
\”\”\”函数管理器 .\”\”\”
# 存放注册的可执行对象
__hub = {} # type: ignore
@classmethod
def register_invocation_cls(cls, invocation_cls: InvocationMeta, name=None) -> None:
if not name:
func_name = invocation_cls.Meta.func_name
else:
func_name = name
if not isinstance(func_name, str):
raise ValueError(f\”func_name {func_name} should be string\”)
existed_invocation_cls = cls.__hub.get(func_name)
if existed_invocation_cls:
raise RuntimeError(
\”func register error, {}\’s func_name {} conflict with {}\”.format(
existed_invocation_cls, func_name, invocation_cls
)
)
# 存放类的实例
cls.__hub[func_name] = invocation_cls()
@classmethod
def register_funcs(cls, func_dict) -> None:
for func_name, func_obj in func_dict.items():
if not isinstance(func_name, str):
raise ValueError(f\”func_name {func_name} should be string\”)
if func_name in cls.__hub:
raise ValueError(
\”func register error, {}\’s func_name {} conflict with {}\”.format(
func_obj, func_name, cls.__hub[func_name]
)
)
if isinstance(func_obj, str):
func = import_string(func_obj)
elif isinstance(func_obj, Callable):
func = func_obj
else:
raise ValueError(
\”func register error, {} is not be callable\”.format(
func_obj, func_name
)
)
cls.__hub[func_name] = func
@classmethod
def clear(cls) -> None:
\”\”\”清空注册信息 .\”\”\”
cls.__hub = {}
@classmethod
def all_funcs(cls) -> Dict:
\”\”\”获得所有的注册信息. \”\”\”
return cls.__hub
@classmethod
def get_func(cls, func_name: str) -> Callable:
\”\”\”获得注册的函数 .\”\”\”
func_obj = cls.__hub.get(func_name)
if not func_obj:
raise ValueError(\”func object {} not found\”.format(func_name))
return func_obj
@classmethod
def func_call(cls, func_name: str, *args, **kwargs):
\”\”\”根据函数名执行注册的函数 .\”\”\”
func = cls.get_func(func_name)
return func(*args, **kwargs)
定义元类
派生的类可自行注册到插件管理器。
class InvocationMeta(type):
\”\”\”
Metaclass for function invocation
\”\”\”
def __new__(cls, name, bases, dct):
# ensure initialization is only performed for subclasses of Plugin
parents = [b for b in bases if isinstance(b, InvocationMeta)]
if not parents:
return super().__new__(cls, name, bases, dct)
new_cls = super().__new__(cls, name, bases, dct)
# meta validation
meta_obj = getattr(new_cls, \”Meta\”, None)
if not meta_obj:
raise AttributeError(\”Meta class is required\”)
func_name = getattr(meta_obj, \”func_name\”, None)
if not func_name:
raise AttributeError(\”func_name is required in Meta\”)
desc = getattr(meta_obj, \”desc\”, None)
if desc is not None and not isinstance(desc, str):
raise AttributeError(\”desc in Meta should be str\”)
# register func
FunctionsManager.register_invocation_cls(new_cls)
return new_cls
定义元类的一个抽象派生类
支持参数验证。
class BaseInvocation(metaclass=InvocationMeta):
\”\”\”
Base class for function invocation
\”\”\”
class Inputs(BaseModel):
\”\”\”
输入校验器
\”\”\”
pass
@validate_arguments # type: ignore
def __call__(self, *args, **kwargs):
# 输入参数校验, 仅可能是 args 或 kwargs 之一
try:
params = {}
if args:
inputs_meta = getattr(self.Inputs, \”Meta\”, None)
inputs_ordering = getattr(inputs_meta, \”ordering\”, None)
if isinstance(inputs_ordering, list):
if len(args) > len(inputs_ordering):
raise Exception(f\”Too many arguments for inputs: {args}\”)
params = dict(zip(inputs_ordering, args))
elif kwargs:
params = kwargs
# 参数校验
if params:
self.Inputs(**params)
except PydanticValidationError as e:
raise Exception(e)
# 执行自定义业务逻辑
return self.invoke(*args, **kwargs)
@abc.abstractmethod
def invoke(self, *args, **kwargs):
\”\”\”自定义业务逻辑 .\”\”\”
raise NotImplementedError()
定义装饰器
def register_class(name: str):
def _register_class(cls: BaseInvocation):
FunctionsManager.register_invocation_cls(cls, name=name)
@wraps(cls)
def wrapper():
return cls()
return wrapper
return _register_class
def register_func(name: str):
def _register_func(func: Callable):
FunctionsManager.register_funcs({name: func})
@wraps(func)
def wrapper(*args, **kwargs):
return func(*args, **kwargs)
return wrapper
return _register_func
单元测试
from pydantic import BaseModel
from .register import FunctionsManager, register_func, register_class, BaseInvocation
@register_func(\”add\”)
def add(x: int, y: int) -> int:
return x + y
class Add(BaseInvocation):
class Meta:
func_name = \”multiply\”
class Inputs(BaseModel):
\”\”\”
输入校验器
\”\”\”
x: int
y: int
class Meta:
ordering = [\”x\”, \”y\”]
def invoke(self, x: int, y: int) -> int:
return x * y
@register_class(\”subtract\”)
class Subtract:
class Inputs(BaseModel):
\”\”\”
输入校验器
\”\”\”
x: int
y: int
class Meta:
ordering = [\”x\”, \”y\”]
def __call__(self, x: int, y: int) -> int:
return x – y
class TestFunctionsManager:
def test_register_func(self):
func = FunctionsManager.get_func(\”add\”)
assert func(2, 3) == 5
def test_register_class(self):
func = FunctionsManager.get_func(\”subtract\”)
assert func(2, 3) == -1
def test_metaclass(self):
func = FunctionsManager.get_func(\”multiply\”)
assert func(2, 3) == 6
参考
https://github.com/TencentBlueKing/bkflow-feel/blob/main/bkflow_feel/utils.py
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