I am creating a simple game that contains classes called 'Player' and 'Strategy'. I want to assign a Strategy instance to the Player instance when the Player is created.
class Player(object):
def __init__(self):
self.Strategy = None
def Decision(self, InputA, InputB):
Result = self.Strategy(InputA, InputB)
return Result
def SetStrategy(self):
# Sets a strategy instance to the Player instance
class Strategy(object):
def Strategy1(self, InputA, InputB):
return InputA * InputB
def Strategy2(self, InputA, InputB):
return (InputA - InputB) / 2
def Strategy3(self, InputA, InputB):
return 0
What I'm trying to achieve:
in[0] Player1 = Player()
in[1] Player2 = Player()
in[2]: Player1.SetStrategy('Strategy1')
in[3]: Player2.SetStrategy('Strategy3')
in[4]: Player1.Decision(2,5)
out[0]: 10
in[5]: Player2.Decision(3,6)
out[1]: 0
Searching here and via google shows me ways of doing it with monkey patching but the approach looks a little inelegant (and although I'm a beginner I think there's a better way to do it) - is there a way to do this with inheritance that I'm not seeing?
def strategy1(inputA, inputB): # 2
return inputA * inputB
def strategy2(inputA, inputB):
return (inputA - inputB) / 2
def strategy3(inputA, inputB):
return 0
strategy = {
'mul': strategy1,
'diff': strategy2,
'zero': strategy3
}
class Player(object):
def __init__(self, strategy_name='mul'): # 1
self.strategy_name = strategy_name # 5
def decision(self, inputA, inputB): # 4
result = strategy[self.strategy_name](inputA, inputB)
return result
player1 = Player()
player2 = Player()
player1.strategy_name = 'mul' # 3
player2.strategy_name = 'zero'
print(player1.decision(2, 5))
# 10
print(player2.decision(3, 6))
# 0
Every player has a strategy, so don't allow instantiation of Player
without assigning some strategy. You could use a default strategy
(as shown below), or make strategy a mandatory argument.
The strategies could be plain functions; I don't see a reason to
bundle them as methods of a Strategy class. Always keep code as
simple as possible; don't use a class when a function would suffice;
use a class when it provides some feature (such as inheritance) which
makes the class-based solution simpler.
In Python there is no need for getters/setters like setStrategy.
You can use plain attributes for simple values, and properties to
implement more complicated behavior. Attributes and properties use
the same syntax, so you can switch from one to the other without
having to change have the class is used.
There is a convention (recommended in PEP8) that classes be named in
CamelCase, and instances, functions and variables in lowercase. The
convention is used ubiquitously, and following it will help other
understand your code more easily.
To make it easy to store the strategy in a database, you could store
the strategy_name in the database, and use a lookup dict (such as
strategy) to associate the name with the actual function.
Related
Given a class with class methods that contain only self input:
class ABC():
def __init__(self, input_dict)
self.variable_0 = input_dict['variable_0']
self.variable_1 = input_dict['variable_1']
self.variable_2 = input_dict['variable_2']
self.variable_3 = input_dict['variable_3']
def some_operation_0(self):
return self.variable_0 + self.variable_1
def some_operation_1(self):
return self.variable_2 + self.variable_3
First question: Is this very bad practice? Should I just refactor some_operation_0(self) to explicitly take the necessary inputs, some_operation_0(self, variable_0, variable_1)? If so, the testing is very straightforward.
Second question: What is the correct way to setup my unit test on the method some_operation_0(self)?
Should I setup a fixture in which I initialize input_dict, and then instantiate the class with a mock object?
#pytest.fixture
def generator_inputs():
f = open('inputs.txt', 'r')
input_dict = eval(f.read())
f.close()
mock_obj = ABC(input_dict)
def test_some_operation_0():
assert mock_obj.some_operation_0() == some_value
(I am new to both python and general unit testing...)
Those methods do take an argument: self. There is no need to mock anything. Instead, you can simply create an instance, and verify that the methods return the expected value when invoked.
For your example:
def test_abc():
a = ABC({'variable_0':0, 'variable_1':1, 'variable_2':2, 'variable_3':3))
assert a.some_operation_0() == 1
assert a.some_operation_1() == 5
If constructing an instance is very difficult, you might want to change your code so that the class can be instantiated from standard in-memory data structures (e.g. a dictionary). In that case, you could create a separate function that reads/parses data from a file and uses the "data-structure-based" __init__ method, e.g. make_abc() or a class method.
If this approach does not generalize to your real problem, you could imagine providing programmatic access to the key names or other metadata that ABC recognizes or cares about. Then, you could programmatically construct a "defaulted" instance, e.g. an instance where every value in the input dict is a default-constructed value (such as 0 for int):
class ABC():
PROPERTY_NAMES = ['variable_0', 'variable_1', 'variable_2', 'variable_3']
def __init__(self, input_dict):
# implementation omitted for brevity
pass
def some_operation_0(self):
return self.variable_0 + self.variable_1
def some_operation_1(self):
return self.variable_2 + self.variable_3
def test_abc():
a = ABC({name: 0 for name in ABC.PROPERTY_NAMES})
assert a.some_operation_0() == 0
assert a.some_operation_1() == 0
I am currently designing a software which needs to manage a certain hardware setup.
The hardware setup is as following :
System - The system contains two identical devices, and has certain functionality relative to the entire system.
Device - Each device contains two identical sub devices, and has certain functionality relative to both sub devices.
Sub device - Each sub device has 4 configurable entities (Controlled via the same hardware command - thus I don't count them as a sub-sub device).
What I want to achieve :
I want to control all configurable entities via the system manager (the entities are counted in a serial way), meaning I would be able to do the following :
system_instance = system_manager_class(some_params)
system_instance.some_func(0) # configure device_manager[0].sub_device_manager[0].entity[0]
system_instance.some_func(5) # configure device_manager[0].sub_device_manager[1].entity[1]
system_instance.some_func(8) # configure device_manager[1].sub_device_manager[1].entity[0]
What I have thought of doing :
I was thinking of creating an abstract class, which contains all sub device functions (with a call to a conversion function) and have the system_manager, device_manager and sub_device_manager inherit it. Thus all classes will have the same function name and I will be able to access them via the system manager.
Something around these lines :
class abs_sub_device():
#staticmethod
def convert_entity(self):
sub_manager = None
sub_entity_num = None
pass
def set_entity_to_2(entity_num):
sub_manager, sub_manager_entity_num = self.convert_entity(entity_num)
sub_manager.some_func(sub_manager_entity_num)
class system_manager(abs_sub_device):
def __init__(self):
self.device_manager_list = [] # Initiliaze device list
self.device_manager_list.append(device_manager())
self.device_manager_list.append(device_manager())
def convert_entity(self, entity_num):
relevant_device_manager = self.device_manager_list[entity_num // 4]
relevant_entity = entity_num % 4
return relevant_device_manage, relevant_entity
class device_manager(abs_sub_device):
def __init__(self):
self.sub_device_manager_list = [] # Initiliaze sub device list
self.sub_device_manager_list.append(sub_device_manager())
self.sub_device_manager_list.append(sub_device_manager())
def convert_entity(self, entity_num):
relevant_sub_device_manager = self.sub_device_manager_list[entity_num // 4]
relevant_entity = entity_num % 4
return relevant_sub_device_manager, relevant_entity
class sub_device_manager(abs_sub_device):
def __init__(self):
self.entity_list = [0] * 4
def set_entity_to_2(self, entity_num):
self.entity_list[entity_num] = 2
The code is for generic understanding of my design, not for actual functionality.
The problem :
It seems to me that the system I am trying to design is really generic and that there must be a built-in python way to do this, or that my entire object oriented look at it is wrong.
I would really like to know if some one has a better way of doing this.
After much thinking, I think I found a pretty generic way to solve the issue, using a combination of decorators, inheritance and dynamic function creation.
The main idea is as following :
1) Each layer dynamically creates all sub layer relevant functions for it self (Inside the init function, using a decorator on the init function)
2) Each function created dynamically converts the entity value according to a convert function (which is a static function of the abs_container_class), and calls the lowers layer function with the same name (see make_convert_function_method).
3) This basically causes all sub layer function to be implemented on the higher level with zero code duplication.
def get_relevant_class_method_list(class_instance):
method_list = [func for func in dir(class_instance) if callable(getattr(class_instance, func)) and not func.startswith("__") and not func.startswith("_")]
return method_list
def make_convert_function_method(name):
def _method(self, entity_num, *args):
sub_manager, sub_manager_entity_num = self._convert_entity(entity_num)
function_to_call = getattr(sub_manager, name)
function_to_call(sub_manager_entity_num, *args)
return _method
def container_class_init_decorator(function_object):
def new_init_function(self, *args):
# Call the init function :
function_object(self, *args)
# Get all relevant methods (Of one sub class is enough)
method_list = get_relevant_class_method_list(self.container_list[0])
# Dynamically create all sub layer functions :
for method_name in method_list:
_method = make_convert_function_method(method_name)
setattr(type(self), method_name, _method)
return new_init_function
class abs_container_class():
#staticmethod
def _convert_entity(self):
sub_manager = None
sub_entity_num = None
pass
class system_manager(abs_container_class):
#container_class_init_decorator
def __init__(self):
self.device_manager_list = [] # Initiliaze device list
self.device_manager_list.append(device_manager())
self.device_manager_list.append(device_manager())
self.container_list = self.device_manager_list
def _convert_entity(self, entity_num):
relevant_device_manager = self.device_manager_list[entity_num // 4]
relevant_entity = entity_num % 4
return relevant_device_manager, relevant_entity
class device_manager(abs_container_class):
#container_class_init_decorator
def __init__(self):
self.sub_device_manager_list = [] # Initiliaze sub device list
self.sub_device_manager_list.append(sub_device_manager())
self.sub_device_manager_list.append(sub_device_manager())
self.container_list = self.sub_device_manager_list
def _convert_entity(self, entity_num):
relevant_sub_device_manager = self.sub_device_manager_list[entity_num // 4]
relevant_entity = entity_num % 4
return relevant_sub_device_manager, relevant_entity
class sub_device_manager():
def __init__(self):
self.entity_list = [0] * 4
def set_entity_to_value(self, entity_num, required_value):
self.entity_list[entity_num] = required_value
print("I set the entity to : {}".format(required_value))
# This is used for auto completion purposes (Using pep convention)
class auto_complete_class(system_manager, device_manager, sub_device_manager):
pass
system_instance = system_manager() # type: auto_complete_class
system_instance.set_entity_to_value(0, 3)
There is still a little issue with this solution, auto-completion would not work since the highest level class has almost no static implemented function.
In order to solve this I cheated a bit, I created an empty class which inherited from all layers and stated to the IDE using pep convention that it is the type of the instance being created (# type: auto_complete_class).
Does this solve your Problem?
class EndDevice:
def __init__(self, entities_num):
self.entities = list(range(entities_num))
#property
def count_entities(self):
return len(self.entities)
def get_entity(self, i):
return str(i)
class Device:
def __init__(self, sub_devices):
self.sub_devices = sub_devices
#property
def count_entities(self):
return sum(sd.count_entities for sd in self.sub_devices)
def get_entity(self, i):
c = 0
for index, sd in enumerate(self.sub_devices):
if c <= i < sd.count_entities + c:
return str(index) + " " + sd.get_entity(i - c)
c += sd.count_entities
raise IndexError(i)
SystemManager = Device # Are the exact same. This also means you can stack that infinite
sub_devices1 = [EndDevice(4) for _ in range(2)]
sub_devices2 = [EndDevice(4) for _ in range(2)]
system_manager = SystemManager([Device(sub_devices1), Device(sub_devices2)])
print(system_manager.get_entity(0))
print(system_manager.get_entity(5))
print(system_manager.get_entity(15))
I can't think of a better way to do this than OOP, but inheritance will only give you one set of low-level functions for the system manager, so it wil be like having one device manager and one sub-device manager. A better thing to do will be, a bit like tkinter widgets, to have one system manager and initialise all the other managers like children in a tree, so:
system = SystemManager()
device1 = DeviceManager(system)
subDevice1 = SubDeviceManager(device1)
device2 = DeviceManager(system)
subDevice2 = SubDeviceManager(device2)
#to execute some_func on subDevice1
system.some_func(0, 0, *someParams)
We can do this by keeping a list of 'children' of the higher-level managers and having functions which reference the children.
class SystemManager:
def __init__(self):
self.children = []
def some_func(self, child, *params):
self.children[child].some_func(*params)
class DeviceManager:
def __init__(self, parent):
parent.children.append(self)
self.children = []
def some_func(self, child, *params):
self.children[child].some_func(*params)
class SubDeviceManager:
def __init__(self, parent):
parent.children.append(self)
#this may or may not have sub-objects, if it does we need to make it its own children list.
def some_func(self, *params):
#do some important stuff
Unfortunately, this does mean that if we want to call a function of a sub-device manager from the system manager without having lots of dots, we will have to define it again again in the system manager. What you can do instead is use the built-in exec() function, which will take in a string input and run it using the Python interpreter:
class SystemManager:
...
def execute(self, child, function, *args):
exec("self.children[child]."+function+"(*args)")
(and keep the device manager the same)
You would then write in the main program:
system.execute(0, "some_func", 0, *someArgs)
Which would call
device1.some_func(0, someArgs)
Here's what I'm thinking:
SystemManager().apply_to_entity(entity_num=7, lambda e: e.value = 2)
class EntitySuperManagerMixin():
"""Mixin to handle logic for managing entity managers."""
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs) # Supports any kind of __init__ call.
self._entity_manager_list = []
def apply_to_entity(self, entity_num, action):
relevant_entity_manager = self._entity_manager_list[index // 4]
relevant_entity_num = index % 4
return relevant_entity_manager.apply_to_entity(
relevant_entity_num, action)
class SystemManager(EntitySuperManagerMixin):
def __init__(self):
super().__init__()
# An alias for _entity_manager_list to improve readability.
self.device_manager_list = self._entity_manager_list
self.device_manager_list.extend(DeviceManager() for _ in range(4))
class DeviceManager(EntitySuperManagerMixin):
def __init__(self):
super().__init__()
# An alias for _entity_manager_list to improve readability.
self.sub_device_manager_list = self._entity_manager_list
self.sub_device_manager_list.extend(SubDeviceManager() for _ in range(4))
class SubDeviceManager():
"""Manages entities, not entity managers, thus doesn't inherit the mixin."""
def __init__(self):
# Entities need to be classes for this idea to work.
self._entity_list = [Entity() for _ in range(4)]
def apply_to_entity(self, entity_num, action):
return action(self._entity_list[entity_num])
class Entity():
def __init__(self, initial_value=0):
self.value = initial_value
With this structure:
Entity-specific functions can stay bound to the Entity class (where it belongs).
Manager-specific code needs to be updated in two places: EntitySuperManagerMixin and the lowest level manager (which would need custom behavior anyway since it deals with the actual entities, not other managers).
The way i see it if you want to dynamically configure different part of system you need some sort of addressing so if you input an ID or address with some parameter the system will know with address on which sub sistem you are talking about and then configure that system with parameter.
OOP is quite ok for that and then you can easily manipulate such data via bitwise operators.
So basic addressing is done via binary system , so to do that in python you need first to implement an address static attribute to your class with perhaps some basic further detailing if system grows.
Basic implementation of addres systems is as follows:
bin(71)
1010 1011
and if we divide it into nibbles
1010 - device manager 10
1011 - sub device manager 11
So in this example we have system of 15 device managers and 15 sub device menagers, and every device and sub device manager has its integer address.So let's say you want to access device manager no10 with sub device manager no11. You would need their address which is in binary 71 and you would go with:
system.config(address, parameter )
Where system.config funcion would look like this:
def config(self,address, parameter):
device_manager = (address&0xF0)>>4 #10
sub_device_manager = address&0xf # 11
if device_manager not in range(self.devices): raise LookupError("device manager not found")
if sub_device_manager not in range(self.devices[device_manager].device): raise LookupError("sub device manager not found")
self.devices[device_manager].device[sub_device_manager].implement(parameter)
In layman you would tell system that sub_device 11 from device 10 needs configuration with this parameter.
So how would this setup look in python inheritance class of some base class of system that could be then composited/inherited to different classes:
class systems(object):
parent = None #global parent element, defaults to None well for simplicity
def __init__(self):
self.addrMASK = 0xf # address mask for that nibble
self.addr = 0x1 # default address of that element
self.devices = [] # list of instances of device
self.data = { #some arbitrary data
"param1":"param_val",
"param2":"param_val",
"param3":"param_val",
}
def addSubSystem(self,sub_system): # connects elements to eachother
# checks for valiability
if not isinstance(sub_system,systems):
raise TypeError("defined input is not a system type") # to prevent passing an integer or something
# appends a device to system data
self.devices.append(sub_system)
# search parent variables from sub device manager to system
obj = self
while 1:
if obj.parent is not None:
obj.parent.addrMASK<<=4 #bitshifts 4 bits
obj.parent.addr <<=4 #bitshifts 4 bits
obj = obj.parent
else:break
#self management , i am lazy guy so i added this part so i wouldn't have to reset addresses manualy
self.addrMASK <<=4 #bitshifts 4 bits
self.addr <<=4 #bitshifts 4 bits
# this element is added so the obj address is coresponding to place in list, this could be done more eloquently but i didn't know what are your limitations
if not self.devices:
self.devices[ len(self.devices)-1 ].addr +=1
self.devices[ len(self.devices)-1 ].parent = self
# helpful for checking data ... gives the address of system
def __repr__(self):
return "system at {0:X}, {1:0X}".format(self.addr,self.addrMASK)
# extra helpful lists data as well
def __str__(self):
data = [ '{} : {}\n'.format(k,v) for k,v in self.data.items() ]
return " ".join([ repr(self),'\n',*data ])
#checking for data, skips looping over sub systems
def __contains__(self,system_index):
return system_index-1 in range(len(self.data))
# applying parameter change -- just an example
def apply(self,par_dict):
if not isinstance(par_dict,dict):
raise TypeError("parameter must be a dict type")
if any( key in self.data.keys() for key in par_dict.keys() ):
for k,v in par_dict.items():
if k in self.data.keys():
self.data[k]=v
else:pass
else:pass
# implementing parameters trough addresses
def implement(self,address,parameter_dictionary):
if address&self.addrMASK==self.addr:
if address-self.addr!=0:
item = (address-self.addr)>>4
self.devices[item-1].implement( address-self.addr,parameter_dictionary )
else:
self.apply(parameter_dictionary)
a = systems()
b = systems()
a.addSubSystem(b)
c = systems()
b.addSubSystem(c)
print('a')
print(a)
print('')
print('b')
print(b)
print('')
print('c')
print(c)
print('')
a.implement(0x100,{"param1":"a"})
a.implement(0x110,{"param1":"b"})
a.implement(0x111,{"param1":"c"})
print('a')
print(a)
print('')
print('b')
print(b)
print('')
print('c')
print(c)
print('')
I've just recently wrapped my head around the self convention in Python and have begun making more complex code. However, an experienced programmer and friend of mine told me that to use self for every variable in a class method is wasteful.
I understand that self will cause the variable to become attributed to that class. So would it be true that, unless the need arises, it is good practice to avoid using self?
Below is some code that fetches League of Legends information from an API and stores each variable in self.var_name to illustrate how I'm (perhaps unnecessarily) using self.
async def getChampInfo(self, *args):
""" Return play, ban, and win rate for a champ """
self.uri = "http://api.champion.gg/v2/champions/{}?api_key={}"
self.champ = " ".join(args)
self.champID = lu.getChampID(self.champ)
self.res = requests.get(self.uri.format(
self.champID, League.champion_gg_api_key)).json()
self.role = self.res[0]["role"]
self.role_rate = self.res[0]["percentRolePlayed"]
self.play_rate = self.res[0]["playRate"]
self.win_rate = self.res[0]["winRate"]
self.ban_rate = self.res[0]["banRate"]
There are cases where using self is not needed.
Off the top of my head:
when the variable is only used in 1 function, or is created inside a function/method and only used in that function/method
when the variable doesn't need to be shared between methods
when the variable doesn't need to be exposed to other classes/scopes/contexts
Another partial answer is that when creating metaclass/factories/composition something like this might make more sense to move away from the convention of using self like:
class Factory(object):
def __init__(cls, *args, **kwargs):
thing = cls(args, kwargs)
I might be missing some stuff here, but those are what i can think of at the moment.
related:
https://stackoverflow.com/a/7722353/2026508
What is the purpose of self?
self will cause a variable to become attributed to an instance of the class, not the class itself. I don't know if you meant that or not, but it's certainly worth thinking about.
Variables in the class-wide scope can be divided into two categories: class and instance variables. Class variables are defined at the beginning of the class definition, outside of any method. If a variable is constant for all instances, or it is only used in class/static methods, it should be a class variable. Often, such variables are true constants, though there are numerous cases where they aren't. Instance variables are generally defined in __init__, but there are numerous cases where they should be defined elsewhere. That being said, if you don't have a good reason not to, define instance variables in __init__, as this keeps your code (and class) organized. It is perfectly acceptable to give them placeholder values (such as None), if you know the variable is essential to the state of the instance but its value is not determined until a certain method is called.
Here's a good example:
class BaseGame:
"""Base class for all game classes."""
_ORIGINAL_BOARD = {(0,0): 1, (2,0): 1, (4,0): 1, (6,0): 1, (8,0): 1,
(1,2): 1, (3,2): 1, (5,2): 1, (7,2): 1, (2,4): 1,
(4,4): 1, (6,4): 1, (3,6): 1, (5,6): 1, (4,8): 0}
_POSSIBLE_MOVES = {(0,0): ((4,0),(2,4)),
(2,0): ((4,0),(2,4)),
(4,0): ((-4,0),(4,0),(2,4),(-2,4)),
(6,0): ((-4,0),(-2,4)),
(8,0): ((-4,0),(-2,4)),
(1,2): ((4,0),(2,4)),
(3,2): ((4,0),(2,4)),
(5,2): ((-4,0),(-2,4)),
(7,2): ((-4,0),(-2,4)),
(2,4): ((4,0),(2,4),(-2,-4),(2,-4)),
(4,4): ((-2,-4,),(2,-4)),
(6,4): ((-4,0),(-2,4),(-2,-4),(2,-4)),
(3,6): ((-2,-4),(2,-4)),
(5,6): ((-2,-4),(2,-4)),
(4,8): ((-2,-4),(2,-4))}
started = False
def __call__(self):
"""Call self as function."""
self.started = True
self.board = __class__._ORIGINAL_BOARD.copy()
self.peg_count = 14
self.moves = []
#staticmethod
def _endpoint(peg, move):
"""Finds the endpoint of a move vector."""
endpoint = tuple(map(add, peg, move))
return endpoint
#staticmethod
def _midpoint(peg, move):
"""Finds the midpoint of a move vector."""
move = tuple(i//2 for i in move)
midpoint = tuple(map(add, peg, move))
return midpoint
def _is_legal(self, peg, move):
"""Determines if a move is legal or not."""
endpoint = self._endpoint(peg, move)
midpoint = self._midpoint(peg, move)
try:
if not self.board[midpoint] or self.board[endpoint]:
return False
else:
return True
except KeyError:
return False
def find_legal_moves(self):
"""Finds all moves that are currently legal.
Returns a dictionary whose keys are the locations of holes with
pegs in them and whose values are movement vectors that the pegs
can legally move along.
"""
pegs = [peg for peg in self.board if self.board[peg]]
legal_moves = {}
for peg in pegs:
peg_moves = []
for move in __class__._POSSIBLE_MOVES[peg]:
if self._is_legal(peg, move):
peg_moves.append(move)
if len(peg_moves):
legal_moves[peg] = peg_moves
return legal_moves
def move(self, peg, move):
"""Makes a move."""
self.board[peg] = 0
self.board[self._midpoint(peg, move)] = 0
self.board[self._endpoint(peg, move)] = 1
self.peg_count -= 1
self.moves.append((peg, move))
def undo(self):
"""Undoes a move."""
peg, move = self.moves.pop()
self.board[peg] = 1
self.board[self._midpoint(peg, move)] = 1
self.board[self._endpoint(peg, move)] = 0
self.peg_count += 1
def restart(self):
"""Restarts the game."""
self.board = __class__._ORIGINAL_BOARD.copy()
self.peg_count = 14
self.moves.clear()
_ORIGINAL_BOARD and _POSSIBLE_MOVES are true constants. While started is not a constant, as its value depends on whether the __call__ method was invoked or not, its default value, False, IS constant for all instances, so I declared it as a class variable. Notice that in __call__ (don't worry about why I used __call__ instead of __init__), I redefined it as an instance variable, as __call__ starts the game, and therefore when it is invoked, the instance's state has changed from the class default, "not started", to "started".
Also notice that the other methods besides __call__ regularly change the value of the instance variables, but that they are not initially defined in said methods, as there is no compelling reason for them to be.
I want to create a function within a class that can access two different members with the same function. For example in the code below, I want both of the lines below to use the 'apply' function on different variables in the class
print(state.apply(rate))
print(state.apply(wage))
I had thought if I put in a dummy variable in the function definition (called exposure), it would replace it with the variables passed to the function (rate and wage in the example below). What is the correct way of doing this in python 3?
class State():
def __init__(self):
self.rate = 0
self.wage = 0
def apply(self, exposure):
self.exposure = self.exposure - 1
return self.exposure
state = State()
rate = State.rate
wage = State.wage
print(state.apply(rate))
print(state.apply(wage))
EDIT: I had made a typo where I had State instead of state in each print statement. I have now corrected this
This would be the only way:
class State:
def __init__ (self):
self.rate = 0
self.wage = 0
def apply (self, exposure):
setattr(self, exposure, getattr(self, exposure) - 1)
return getattr(self, exposure)
>>> state = State()
>>> print(state.apply('rate'))
-1
>>> print(state.apply('wage'))
-1
>>> print(state.apply('wage'))
-2
Note that those are instance variables, so you cannot access them using the type, State, but only using the object, state.
However, I would say, that whatever you are trying, you’re doing it wrong. If you describe your actual problem, we may be able to suggest a way better solution for it instead.
I am trying to simply get the value out of my class using a simple function with a return value, I'm sure its a trivial error, but im pretty new to python
I have a simply class set up like this:
class score():
#initialize the score info
def __init__(self):
self.score = 0
self.num_enemies = 5
self.num_lives = 3
# Score Info
def setScore(num):
self.score = num
# Enemy Info
def getEnemies():
return self.num_enemies
# Lives Info
def getLives():
return self.getLives
etc.....
Than I create an instance of the class as such:
scoreObj = score()
for enemies in range(0, scoreObj.getEnemies):
enemy_sprite.add(enemy())
I get the error saying that an integer is expected, but it got an instancemethod
What is the correct way to get this information?
Thanks!
scoreObj.getEnemies is a reference to the method. If you want to call it you need parentheses: scoreObj.getEnemies().
You should think about why you are using a method for this instead of just reading self.num_enemies directly. There is no need for trivial getter/setter methods like this in Python.
The first parameter for a member function in python is a reference back to the Object.
Traditionally you call it "self", but no matter what you call the first parameter, it refers back to the "self" object:
Anytime I get weird errors about the type of a parameter in python, I check to see if I forgot the self param. Been bit by this bug a few times.
class score():
#initialize the score info
def __init__(self):
self.score = 0
self.num_enemies = 5
self.num_lives = 3
# Score Info
def setScore(self, num):
self.score = num
# Enemy Info
def getEnemies(self):
return self.num_enemies
# Lives Info
def getLives(foo): #foo is still the same object as self!!
return foo.num_lives
#Works but don't do this because it is confusing
This code works:
class score():
def __init__(self):
self.score = 0
self.num_enemies = 5
self.num_lives = 3
def setScore(self, num):
self.score = num
def getEnemies(self):
return self.num_enemies
def getLives(self):
return self.getLives
scoreObj = score()
for enemy_num in range(0, scoreObj.getEnemies()):
print enemy_num
# I don't know what enemy_sprite is, but
# I commented it out and just print the enemy_num result.
# enemy_sprite.add(enemy())
Lesson Learned:
Class functions must always take one parameter, self.
That's because when you call a function within the class, you always call it with the class name as the calling object, such as:
scoreObj = score()
scoreObj.getEnemies()
Where x is the class object, which will be passed to getEnemies() as the root object, meaning the first parameter sent to the class.
Secondly, when calling functions within a class (or at all), always end with () since that's the definition of calling something in Python.
Then, ask yourself, "Why am I not fetching 'scoreObj.num_lives' just like so instead? Am I saving processing power?" Do as you choose, but it would go faster if you get the values directly from the class object, unless you want to calculate stuff at the same time. Then your logic makes perfect sense!
You made a simple mistake:
scoreObj.getEnemies()
getEnemies is a function, so call it like any other function scoreObj.getEnemies()