I have 3 classes defined this way:
class Device:
Some method
class SSH:
def connect(self,type):
# code
def execute(self,cmd):
# code
class Netconf:
def connect(self,type):
# code
def execute(self,cmd):
# code
Note SSH and Netconf classes have same method names but they do things differently.
I have an instance of class Device and would like to access methods like this-
d = Device()
d.connect('cli') # <-- This should call SSH method and subsequently
# d.execute(cmd) should call execute method from SSH class
# too.
d.connect('netconf') # <-- This should call Netconf method and subsequently
# d.execute(cmd) should call execute method from
# Netconf class too.
The question is - how do I make it happen? I want to be able to use methods of SSH/Netconf class on Device class instance 'd' based on the input.
You can do this by storing the type of device connected in a private Device attribute and then forwarding most method calls to it by adding a custom __getattr__() method. This is a little tricky in the connect() method because that's were the target device is defined (as opposed to in the Device.__init__() initializer).
I also changed the variable you had named type to kind to avoid colliding with the built-in module of the same name.
class Device(object):
def connect(self, kind):
if kind == 'cli':
target = self._target = SSH()
elif kind == 'netconf':
target = self._target = Netconf()
else:
raise ValueError('Unknown device {!r}'.format(kind))
return target.connect(kind)
def __getattr__(self, name):
return getattr(self._target, name)
class SSH(object):
def connect(self, kind):
print('SSH.connect called with kind {!r}'.format(kind))
def execute(self, cmd):
print('SSH.execute called with cmd {!r}'.format(cmd))
class Netconf(object):
def connect(self, kind):
print('Netconf.connect called with kind {!r}'.format(kind))
def execute(self, cmd):
print('Netconf.execute called with cmd {!r}'.format(cmd))
d = Device()
d.connect('cli')
d.execute('cmd1')
d.connect('netconf')
d.execute('cmd2')
Output:
SSH.connect called with kind 'cli'
SSH.execute called with cmd 'cmd1'
Netconf.connect called with kind 'netconf'
Netconf.execute called with cmd 'cmd2'
You should implement the Strategy Pattern. The connect() method should instantiate the appropriate class (detach()ing from the previous if required) and store it, and then other methods should delegate to the stored object.
Related
I am performing load test using locust and have implemented RPS based load generation using a custom class from LoadTestShape.
This custom class holds methods for different load shapes like _tick_step_increase, _tick_rps_based, etc.:
class CustomLoadShape:
# factory class that holds different shape methods #
def __init__(self, step_interval=5, max_rps=500):
self.step_interval = step_interval
self.max_rps = max_rps
def _tick_step_increase(self):
# use self.interval here #
pass
def _tick_square_wave(self):
# use self.max_rps here #
pass
class MyCustomLoadShape(LoadTestShape, CustomLoadShape):
# this class is present in locustfile #
def __init__(self):
CustomLoadShape.__init__()
setattr(self, "tick", self._tick_rps_based) # this is how i make sure the `tick` method is defined
I am accepting some cli args, say, max-rps and wish to pass them to MyCustomLoadShape (eventually to CustomLoadShape).
I know that in the task functions, we can access cli args as self.environment.parsed_options.max_rps.
Intuitively, I tried to do the same in __init__ but it does not have self.environment and self.runner is None (somehow it appears as an object in the tick method).
Although we can access cli args in the tick method using self.runner.environment.parsed_options.max_rps, I was wondering if there was a way to do this in __init__ so that we could play around with attributes in a more OOP way.
I answered another similar question recently:
How to create and use custom command line parameters in locust
If you can't access the environment inside the LoadShape class, I'd recommend just setting a global variable with another function that runs on init like so:
max_rps = None
step_interval = None
#events.init.add_listener
def set_max_rps(environment, **kw):
global max_rps
max_rps = environment.parsed_options.max_rps
global step_interval = None
step_interval = None
Then you could access it from your other classes:
class CustomLoadShape:
# factory class that holds different shape methods #
def _tick_step_increase(self):
# use interval here #
step_interval
pass
def _tick_square_wave(self):
# use max rps here #
max_rps
pass
I have a large Python 3.6 system where multiple processes and threads interact with each other and the user. Simplified, there is a Scheduler instance (subclasses threading.Thread) and a Worker instance (subclasses multiprocessing.Process). Both objects run for the entire duration of the program.
The user interacts with the Scheduler by adding Task instances and the Scheduler passes the task to the Worker at the correct moment in time. The worker uses the information contained in the task to do its thing.
Below is some stripped out and simplified code out of the project:
class Task:
def __init__(self, name:str):
self.name = name
self.state = 'idle'
class Scheduler(threading.Thread):
def __init__(self, worker:Worker):
super().init()
self.worker = worker
self.start()
def run(self):
while True:
# Do stuff until the user schedules a new task
task = Task() # <-- In reality the Task intance is not created here but the thread gets it from elsewhere
task.state = 'scheduled'
self.worker.change_task(task)
# Do stuff until the task.state == 'finished'
class Worker(multiprocessing.Process):
def __init__(self):
super().init()
self.current_task = None
self.start()
def change_task(self, new_task:Task):
self.current_task = new_task
self.current_task.state = 'accepted-idle'
def run(self):
while True:
# Do stuff until the current task is updated
self.current_task.state = 'accepted-running'
# Task is running
self.current_task.state = 'finished'
The system used to be structured so that the task contained multiple multiprocessing.Events indicating each of its possible states. Then, not the whole Task instance was passed to the worker, but each of the task's attributes was. As they were all multiprocessing safe, it worked, with a caveat. The events changed in worker.run had to be created in worker.run and back passed to the task object for it work. Not only is this a less than ideal solution, it no longer works with some changes I am making to the project.
Back to the current state of the project, as described by the python code above. As is, this will never work because nothing makes this multiprocessing safe at the moment. So I implemented a Proxy/BaseManager structure so that when a new Task is needed, the system gets it from the multiprocessing manager. I use this structure in a sightly different way elsewhere in the project as well. The issue is that the worker.run never knows that the self.current_task is updated, it remains None. I expected this to be fixed by using the proxy but clearly I am mistaken.
def Proxy(target: typing.Type) -> typing.Type:
"""
Normally a Manager only exposes only object methods. A NamespaceProxy can be used when registering the object with
the manager to expose all the attributes. This also works for attributes created at runtime.
https://stackoverflow.com/a/68123850/8353475
1. Instead of exposing all the attributes manually, we effectively override __getattr__ to do it dynamically.
2. Instead of defining a class that subclasses NamespaceProxy for each specific object class that needs to be
proxied, this method is used to do it dynamically. The target parameter should be the class of the object you want
to generate the proxy for. The generated proxy class will be returned.
Example usage: FooProxy = Proxy(Foo)
:param target: The class of the object to build the proxy class for
:return The generated proxy class
"""
# __getattr__ is called when an attribute 'bar' is called from 'foo' and it is not found eg. 'foo.bar'. 'bar' can
# be a class method as well as a variable. The call gets rerouted from the base object to this proxy, were it is
# processed.
def __getattr__(self, key):
result = self._callmethod('__getattribute__', (key,))
# If attr call was for a method we need some further processing
if isinstance(result, types.MethodType):
# A wrapper around the method that passes the arguments, actually calls the method and returns the result.
# Note that at this point wrapper() does not get called, just defined.
def wrapper(*args, **kwargs):
# Call the method and pass the return value along
return self._callmethod(key, args, kwargs)
# Return the wrapper method (not the result, but the method itself)
return wrapper
else:
# If the attr call was for a variable it can be returned as is
return result
dic = {'types': types, '__getattr__': __getattr__}
proxy_name = target.__name__ + "Proxy"
ProxyType = type(proxy_name, (NamespaceProxy,), dic)
# This is a tuple of all the attributes that are/will be exposed. We copy all of them from the base class
ProxyType._exposed_ = tuple(dir(target))
return ProxyType
class TaskManager(BaseManager):
pass
TaskProxy = Proxy(Task)
TaskManager.register('get_task', callable=Task, proxytype=TaskProxy)
This question already has an answer here:
How to access outer attribute class within inner class?
(1 answer)
Closed 3 years ago.
As a title, I have a versatility function in parent class that will share use in child class A.k.A inner class. In below, I need to pass outer_send function from parent class. then, use it with call inner_send function inside Identify class alias child class. The result will output Test.
class Device:
def __init__(self):
self.identify = self.Identify(self.outer_send())
def outer_send(message):
print(message)
def last_error(self):
return self.identify.error_info
class Identify:
def __init__(self, send):
self.inner_send() = send()
def set_error(self, error):
self.error_info = error
device = Device()
device.identify.inner_send('test')
I don't like the pattern and I would recommend designing it differently. However, this does what I think you want to do:
class Device:
def __init__(self):
self.identify = self.Identify(self._send)
def _send(self, message):
print(message)
class Identify:
def __init__(self, _send):
self.send = _send
device = Device()
device.identify.send('test')
A few notes: I renamed outer_send to _send, as I assume you don't want people calling that directly on the Device object - if you do, just rename it send and it still works; the error bit seemed superfluous, so left it out; your outer_send was missing self as a parameter - it doesn't need it, but if you do want to leave it out, annotate the method with #staticmethod to avoid warnings.
How do I re-initialize the base class using self.__init__?
In the following example my goal is to inherit eComm which is a socket derived driver. This handles connect/disconnect. If it disconnects we need to reinitialize it using __init__, however it appears to refer to the comDriver when self.__init__ is called.
How do I properly initialize the superclass to allow for this?
(else: self.__init__ in connect() is referring to comDriver, not eComm like it should)
The following is a simple case to reproduce the error in Python 3.x
class eComm():
def __init__(self):
self.s = "example object"
self.initialized = True
self.connected = False
def connect(self, IP_ADDRESS, PORT):
if self.initialized:
print(IP_ADDRESS, PORT)
else:
print("REINITIALIZING")
self.__init__()
self.connected = True
return(True)
class comDriver(eComm):
def __init__(self, IP_ADDRESS, PORT):
self.IP = IP_ADDRESS
self.PORT = PORT
super().__init__()
pass
def getTemp(self):
print("EXAMPLE FUNCTION")
return(1)
x = comDriver("192", 7)
x.connect("161", 6)
x.initialized = False
x.connect("111", 5)
IMO you're using the special method __init__ wrongly. It's meant to initialize a Python object, not anything outside that scope.
With your intention, I recommend that you create a separate initializer function, and call it from __init__. Here's an example:
class eComm():
def __init__(self):
self.initialize_eComm()
def initialize_eComm(self):
self.s = "example object"
self.initialized = True
self.connected = False
And then you can replace self.__init__() with self.initialize_eComm() to avoid name conflict in subclasses.
self.__init__ in connect() is referring to comDriver, not eComm like it should
This doesn't quite hold -- self refers to the calling object, which is comDriver. If you want to call to the __init__ method on eComm regardless of what classes extend it, you will have to reference in explicitly.
eComm.__init__(self)
But, the other answers and comments are right that this is not a good use of __init__.
I'm trying to override the DaemonRunner in the python standard daemon process library (found here https://pypi.python.org/pypi/python-daemon/)
The DaemonRunner responds to command line arguments for start, stop, and restart, but I want to add a fourth option for status.
The class I want to override looks something like this:
class DaemonRunner(object):
def _start(self):
...etc
action_funcs = {'start': _start}
I've tried to override it like this:
class StatusDaemonRunner(DaemonRunner):
def _status(self):
...
DaemonRunner.action_funcs['status'] = _status
This works to some extent, but the problem is that every instance of DaemonRunner now have the new behaviour. Is it possible to override it without modifying every instance of DaemonRunner?
I would override action_functs to make it a non-static member of class StatusDaemonRunner(DaemonRunner).
In terms of code I would do:
class StatusDaemonRunner(runner.DaemonRunner):
def __init__(self, app):
self.action_funcs = runner.DaemonRunner.action_funcs.copy()
self.action_funcs['status'] = StatusDaemonRunner._status
super(StatusDaemonRunner, self).__init__(app)
def _status(self):
pass # do your stuff
Indeed, if we look at the getter in the implementation of DaemonRunner (here) we can see that it acess the attribute using self
def _get_action_func(self):
""" Return the function for the specified action.
Raises ``DaemonRunnerInvalidActionError`` if the action is
unknown.
"""
try:
func = self.action_funcs[self.action]
except KeyError:
raise DaemonRunnerInvalidActionError(
u"Unknown action: %(action)r" % vars(self))
return func
Hence the previous code should do the trick.