Python pluggy framework using sample code

#!/usr/bin/env python
# -*- coding:utf-8 -*-
import pluggy
hookspec = ("myproject")  # hook tags are used to mark hooks
hookimpl = ("myproject")  # hook implementation tag Used to mark one or more implementations of a hook
class MySpec(object):
    """hook collection"""
    @hookspec
    def myhook(self, arg1, arg2):
        pass
    @hookspec
    def my_hook_func1(self, arg1, arg2):
        pass
    @hookspec
    def my_hook_func2(self, arg1, arg2):
        pass
# Plugin Classes
class Plugin_1(object):
    """hook implementation class 1"""
    @hookimpl
    def myhook(self, arg1, arg2):
        print("Plugin_1.myhook called")
        return arg1 + arg2
    @hookimpl
    def my_hook_func2(self, arg1, arg2):
        print("Plugin_1.my_hook_func2 called, args:", arg1, arg2)
    def my_hook_func3(self, arg1, arg2):
        print("Plugin_1.my_hook_func3 called, args:", arg1, arg2)
class Plugin_2(object):
    """hook implementation class 2"""
    @hookimpl
    def myhook(self, arg1, arg2):
        print("Plugin_2.myhook called")
        return arg1 - arg2
    @hookimpl
    def my_hook_func2(self, arg1, arg2):
        print("Plugin_2.my_hook_func2, args:", arg1, arg2)
# Initialize the PluginManager
pm = ("myproject")
# Register a collection of hooks (hook function declarations)
pm.add_hookspecs(MySpec)
# Register the plugin (hook function implementation)
(Plugin_1())
(Plugin_2())
# Calling a custom hook
results = (arg1=1, arg2=2) # Call a hook function with the same name in both plugin classes # The function in the later registered plugin will be called first
print(results) # Output [-1, 3]
results = .my_hook_func1(arg1="name", arg2="shouke")
print(results)
.my_hook_func2(arg1="addr", arg2="sz")

import pluggy
hookspec = ("myproject")  # hook tags are used to mark hooks
hookimpl = ("myproject")  # hook implementation tag Used to mark one or more implementations of a hook
@hookspec
def global_hook_func1(arg1, arg2):
    pass

import pluggy
from myhookspec import hookimpl
@hookimpl
def global_hook_func1(arg1, arg2):
    print("global_hook_func1 in , args:", arg1, arg2)
    return ""

from myhookspec import hookimpl
@hookimpl
def global_hook_func1(arg1, arg2):
    print("global_hook_func1 in , args:", arg1, arg2)
    return ""

#!/usr/bin/env python
# -*- coding:utf-8 -*-
import sys
import pluggy
import myhookspec
import myhookimpl
import other
# Initialize the PluginManager
pm = ("myproject")
# Registered hook collections
pm.add_hookspecs(myhookspec)
# Registration hook implementation
(myhookimpl) # Plug-ins can also be modules
(other)
print(.global_hook_func1(arg1="name", arg2="shouke"))

import pluggy
hookspec = ("myproject")
@hookspec
def mytest_hook_func1(arg1, arg2):
    pass

def mytest_hook_func1(arg1, arg2):
    print("global_hook_func1 in , args:", arg1, arg2)
    return ""

#!/usr/bin/env python
# -*- coding:utf-8 -*-
import inspect
import pluggy
import myhookspec
import other
class PytestPluginManager():
    """
    Plugin class that implements functions that don't use @HookimplMarkerInstance decoration can also be used as function bodies
    """
    def parse_hookimpl_opts(self, plugin, name):
        # Specify that hooks functions that are not decorated by @hookimpl always start with mytest_ to avoid accessing non-readable properties.
        if not ("mytest_"):
            return
        method = getattr(plugin, name)
        opts = super().parse_hookimpl_opts(plugin, name)
        # think overhookCan only be a function(consider only actual functions for hooks)
        if not (method):
            return
        # Collection of untagged，in order tomytestheadlinerhookfunction (math.)，(collect unmarked hooks as long as they have the `pytest_' prefix)
        if opts is None and ("mytest_"):
            opts = {}
        return opts
# Initialize the PluginManager
pm = PytestPluginManager("myproject")
# Registered hook collections
pm.add_hookspecs(myhookspec)
# Registration hook implementation
(other)
.mytest_hook_func1(arg1="addr", arg2="sz")