我想在我的插件钩子规范中添加类型注释,以便可以对钩子实现进行类型检查。使用pluggy documentation中的这个简化示例:
import pluggy # type: ignore
hookspec = pluggy.HookspecMarker("myproject")
hookimpl = pluggy.HookimplMarker("myproject")
class MySpec(object):
"""A hook specification namespace."""
@hookspec
def myhook(self, arg1, arg2):
"""My special little hook that you can customize."""
class Plugin_1(object):
"""A hook implementation namespace."""
@hookimpl
def myhook(self, arg1, arg2):
print("inside Plugin_1.myhook()")
return arg1 + arg2 + "a" # intentional error
# create a manager and add the spec
pm = pluggy.PluginManager("myproject")
pm.add_hookspecs(MySpec)
# register plugins
pm.register(Plugin_1())
# call our `myhook` hook
# intentional incompatible type for parameter arg2
results = pm.hook.myhook(arg1=1, arg2="1")
print(results)
我相信正确有效的注释将是:
def myhook(self, arg1: int, arg2: int) -> int: ...
我尝试将此注释添加到hookspec。正如我所料,这不起作用。我相信这是因为插件实现的间接是动态的。必须运行代码,以便add_hookspecs()
的PluginManager
方法可以定义可用的钩子。
我看到pm.hook
是pluggy.hooks._HookRelay
类型,而pm.hook.myhook
是pluggy.hooks._HookCaller
的一个例子,它有__call__()
方法。
我尝试使用stubgen
为插件制作一组.pyi
文件,然后以两种不同的方式将注释添加到pluggy.hooks._HookCaller
:
class _HookCaller:
def __init__(self, trace: Any) -> None: ...
def myhook(self, arg1: int, arg2: int) -> int: ...
def __call__(self, arg1: int, arg2: int) -> int: ...
当我执行MYPYPATH=./stubs mypy --verboes example.py
时,我可以看到hooks.pyi
被解析但是没有检测到参数类型不匹配。即使我从# type: ignore
中删除import pluggy
注释,此行为也是一致的。
问题:
.pyi
文件,是否可以定义myhook()
钩子的类型注释?.pyi
文件包含什么以及我在哪里存储它以便mypy
在运行类型检查时选择它?第一个问题是@hookspec
删除了myhook
方法的类型提示:
from typing import TypeVar, Callable, Any, cast
# Improvement suggested by @oremanj on python/typing gitter
F = TypeVar("F", bound=Callable[..., Any])
hookspec = cast(Callable[[F], F], pluggy.HookspecMarker("myproject"))
该解决方法否定了对外部.pyi
文件的要求。只需使用现有的钩子规范来定义类型提示。这解决了Q1和Q2:你不需要.pyi
文件。只需使用typing.cast()
给mypy一个提示,它无法从静态分析中学到:
# Add cast so that mypy knows that pm.hook
# is actually a MySpec instance. Without this
# hint there really is no way for mypy to know
# this.
pm.hook = cast(MySpec, pm.hook)
可以通过添加注释来检查:
# Uncomment these when running through mypy to see
# how mypy regards the type
reveal_type(pm.hook)
reveal_type(pm.hook.myhook)
reveal_type(MySpec.myhook)
通过mypy运行:
plug.py:24: error: Unsupported operand types for + ("int" and "str")
plug.py:42: error: Revealed type is 'plug.MySpec'
plug.py:43: error: Revealed type is 'def (arg1: builtins.int, arg2: builtins.int) -> builtins.int'
plug.py:44: error: Revealed type is 'def (self: plug.MySpec, arg1: builtins.int, arg2: builtins.int) -> builtins.int'
plug.py:47: error: Argument "arg2" to "myhook" of "MySpec" has incompatible type "str"; expected "int"
现在mypy
捕获了钩子调用者和钩子实现的类型问题(Q3)!
完整代码:
import pluggy # type: ignore
from typing import TypeVar, Callable, Any, cast
# Improvement suggested by @oremanj on python/typing gitter
F = TypeVar("F", bound=Callable[..., Any])
hookspec = cast(Callable[[F], F], pluggy.HookspecMarker("myproject"))
hookimpl = pluggy.HookimplMarker("myproject")
class MySpec(object):
"""A hook specification namespace."""
@hookspec
def myhook(self, arg1: int, arg2: int) -> int:
"""My special little hook that you can customize."""
class Plugin_1(object):
"""A hook implementation namespace."""
@hookimpl
def myhook(self, arg1: int, arg2: int) -> int:
print("inside Plugin_1.myhook()")
return arg1 + arg2 + 'a'
# create a manager and add the spec
pm = pluggy.PluginManager("myproject")
pm.add_hookspecs(MySpec)
# register plugins
pm.register(Plugin_1())
# Add cast so that mypy knows that pm.hook
# is actually a MySpec instance. Without this
# hint there really is no way for mypy to know
# this.
pm.hook = cast(MySpec, pm.hook)
# Uncomment these when running through mypy to see
# how mypy regards the type
# reveal_type(pm.hook)
# reveal_type(pm.hook.myhook)
# reveal_type(MySpec.myhook)
# this will now be caught by mypy
results = pm.hook.myhook(arg1=1, arg2="1")
print(results)