测试开发技术网站

[TOC]

![](https://redrose2100.oss-cn-hangzhou.aliyuncs.com/img/7cd47362-951c-11ee-986a-0242ac110004.png)

从pluggy模块应用方法实例可以看出，首先是对HookspecMarker类和HookimplMarker类进行了实例化，因此这里首先解读一下此两个类的源码。
HookspecMarker类和HookimplMarker的定义如下所示，首先看HookspecMarker类的定义，类中只有一个__init__函数和__call__函数，__init__函数很简单，就是一个赋值的操作，即在HookspecMarker实例化的时候传入一个名称，然后对象就拥有了一个project_name的属性，属性值即为传入的值。HookimplMarker同样也是只有一个__init__函数和一个__call__函数，__init__函数同样也是给实例的project_name赋值的。
```python
class HookspecMarker:
    """Decorator helper class for marking functions as hook specifications.

You can instantiate it with a project_name to get a decorator.
    Calling :py:meth:`.PluginManager.add_hookspecs` later will discover all marked functions
    if the :py:class:`.PluginManager` uses the same project_name.
    """

def __init__(self, project_name):
        self.project_name = project_name

def __call__(
        self, function=None, firstresult=False, historic=False, warn_on_impl=None
    ):
        """if passed a function, directly sets attributes on the function
        which will make it discoverable to :py:meth:`.PluginManager.add_hookspecs`.
        If passed no function, returns a decorator which can be applied to a function
        later using the attributes supplied.

If ``firstresult`` is ``True`` the 1:N hook call (N being the number of registered
        hook implementation functions) will stop at I<=N when the I'th function
        returns a non-``None`` result.

If ``historic`` is ``True`` calls to a hook will be memorized and replayed
        on later registered plugins.

"""

def setattr_hookspec_opts(func):
            if historic and firstresult:
                raise ValueError("cannot have a historic firstresult hook")
            setattr(
                func,
                self.project_name + "_spec",
                dict(
                    firstresult=firstresult,
                    historic=historic,
                    warn_on_impl=warn_on_impl,
                ),
            )
            return func

if function is not None:
            return setattr_hookspec_opts(function)
        else:
            return setattr_hookspec_opts

class HookimplMarker:
    """Decorator helper class for marking functions as hook implementations.

You can instantiate with a ``project_name`` to get a decorator.
    Calling :py:meth:`.PluginManager.register` later will discover all marked functions
    if the :py:class:`.PluginManager` uses the same project_name.
    """

def __init__(self, project_name):
        self.project_name = project_name

def __call__(
        self,
        function=None,
        hookwrapper=False,
        optionalhook=False,
        tryfirst=False,
        trylast=False,
        specname=None,
    ):

"""if passed a function, directly sets attributes on the function
        which will make it discoverable to :py:meth:`.PluginManager.register`.
        If passed no function, returns a decorator which can be applied to a
        function later using the attributes supplied.

If ``optionalhook`` is ``True`` a missing matching hook specification will not result
        in an error (by default it is an error if no matching spec is found).

If ``tryfirst`` is ``True`` this hook implementation will run as early as possible
        in the chain of N hook implementations for a specification.

If ``trylast`` is ``True`` this hook implementation will run as late as possible
        in the chain of N hook implementations.

If ``hookwrapper`` is ``True`` the hook implementations needs to execute exactly
        one ``yield``.  The code before the ``yield`` is run early before any non-hookwrapper
        function is run.  The code after the ``yield`` is run after all non-hookwrapper
        function have run.  The ``yield`` receives a :py:class:`.callers._Result` object
        representing the exception or result outcome of the inner calls (including other
        hookwrapper calls).

If ``specname`` is provided, it will be used instead of the function name when
        matching this hook implementation to a hook specification during registration.

"""

def setattr_hookimpl_opts(func):
            setattr(
                func,
                self.project_name + "_impl",
                dict(
                    hookwrapper=hookwrapper,
                    optionalhook=optionalhook,
                    tryfirst=tryfirst,
                    trylast=trylast,
                    specname=specname,
                ),
            )
            return func

if function is None:
            return setattr_hookimpl_opts
        else:
            return setattr_hookimpl_opts(function)
```
因此在应用实例中如下两行代码实际就是hookspec这个对象有一个属性project_name，而此属性的值就是myproject，而hookimpl对象也有一个属性project_name，而此属性的值也是myproject
```python
hookspec = pluggy.HookspecMarker("myproject")
hookimpl = pluggy.HookimplMarker("myproject")
```
而应用实例中的如下定义接口的代码，这里使用hookspec作为装饰器作用在myhook方法上，其实就是调用HookspecMarker中的__call__方法，而此方法中的function参数就是myhook方法，其他几个参数默认为None，而在HookspecMarker中的__call__方法中可以看出，当function存在值时，实际是为function设置了一个属性，即为myhook方法设置了一个self.project_name + "_spec"即myproject_spec属性，值就是代码中的这个dict字典。
```python
class MySpec:
    @hookspec
    def myhook(self, arg1, arg2):
        pass
```
同理，对于在插件定义即实现接口的类中，比如如下代码，也是同样的原理，即调用HookimplMarker中的__call__方法，而此方法中同样function参数的值在这里为myhook，function不为空值的时候，就是给function即给myhook设置一个self.project_name + "_impl"即myhook_impl的属性，同样属性值是这里的dict字典数据。
```python
class Plugin_1:
    @hookimpl
    def myhook(self, arg1, arg2):
        print("in Plugin_1.myhook()")
        return arg1 + arg2
```
至此HookspecMarker类和HookimplMarker类的源码就解析完了，这里需要注意的是需要理解python语言中__call__魔法函数用来做装饰器的用法，掌握了这一点那么这两个类的代码定义就很容易理解了。

测试开发技术网站

博客