I have 3 dataclass objects say:
class Message1:
def __init__(a):
...
class Message2:
def __init__(d,e,f):
...
class Message3:
def __init__(g,i):
...
For these 3 messages I want to make a factory type method which can return one of the three objects if it succeeds and if not it should return either the one it identified as the correct message to be created but failed at creation or it should notify the user that it could not create any of the messages. Are there any OOP patterns for this?
My initial thought was to do a:
def factory_method(**parameters):
try:
Message1(**parameters)
except TypeError:
try:
Message2(**parameters)
except:
try:
Message3(**parameters)
except:
print("Could not deduce message type")
My issue with this idea is that:
It's not a dynamically scalable solution, with each new message class I introduce I need to add a new try catch block
If the whole nested block structure fails, I have no feedback as to why, was the parameters correct for one of the message but wrong value, or was it plain gibberish?
I realize this might be a bit opinion based on what the best outcome is. At the same time it might be the solution is not too elegant and the simplest way is to just tell the factory_method what kind of message to initialize. Any suggestions or ideas would be appreciated.
If you can't join them all in a single class and you can't point a call to a single class, i would match the arguments to the posible class. To make it work a type hint and a "proxy" class is required. This example asumes that any of the classes wont contain a __init__(*args, **kwargs), and to add a new class you just add it to Message.msg_cls, you can eval the global scope if you don't want to add manually each class.
class Message1:
def __init__(self, a: int, alt=None, num=10):
print('Message 1')
class Message2:
def __init__(self, d: str, e: str, f: int):
print('Message 2')
class Message3:
def __init__(self, g: int, i: any):
print('Message 3')
class Message:
msg_cls = (
Message1,
Message2,
Message3
)
#staticmethod
def eq_kwargs(cls, kwargs):
cls_kwargs = cls.__init__.__defaults__
if cls_kwargs is None:
if len(kwargs) > 0:
return False
else:
return True
cls_astr = cls.__init__.__code__
kw_types = [type(t) for t in cls_kwargs]
for k in kwargs:
if k in cls_astr.co_varnames:
if type(kwargs[k]) in kw_types:
kw_types.remove(type(kwargs[k]))
else:
if type(None) in kw_types:
kw_types.remove(type(None))
else:
return False
else:
return False
return True
#staticmethod
def eq_args(cls, args):
cls_args = cls.__init__.__annotations__
if len(cls_args) != len(args):
return False
for a, b in zip(args, cls_args):
if type(a) != cls_args[b] and cls_args[b] != any:
return False
return True
def __new__(cls, *args, **kwargs):
for mc in Message.msg_cls:
if Message.eq_args(mc, args):
if Message.eq_kwargs(mc, kwargs):
return mc(*args, **kwargs)
raise ValueError('Message.__new__, no match')
if __name__ == '__main__':
ms_1_a = Message(1, alt='a')
ms_1_b = Message(2, alt='a', num=5)
ms_2 = Message('X', 'Y', 5)
ms_3_a = Message(1, [1, 4])
ms_3_b = Message(2, Message(10))
Related
What's the correct way to convert a string to a corresponding instance of an Enum subclass? Seems like getattr(YourEnumType, str) does the job, but I'm not sure if it's safe enough.
As an example, suppose I have an enum like
class BuildType(Enum):
debug = 200
release = 400
Given the string 'debug', how can I get BuildType.debug as a result?
This functionality is already built in to Enum:
>>> from enum import Enum
>>> class Build(Enum):
... debug = 200
... build = 400
...
>>> Build['debug']
<Build.debug: 200>
The member names are case sensitive, so if user-input is being converted you need to make sure case matches:
an_enum = input('Which type of build?')
build_type = Build[an_enum.lower()]
Another alternative (especially useful if your strings don't map 1-1 to your enum cases) is to add a staticmethod to your Enum, e.g.:
class QuestionType(enum.Enum):
MULTI_SELECT = "multi"
SINGLE_SELECT = "single"
#staticmethod
def from_str(label):
if label in ('single', 'singleSelect'):
return QuestionType.SINGLE_SELECT
elif label in ('multi', 'multiSelect'):
return QuestionType.MULTI_SELECT
else:
raise NotImplementedError
Then you can do question_type = QuestionType.from_str('singleSelect')
def custom_enum(typename, items_dict):
class_definition = """
from enum import Enum
class {}(Enum):
{}""".format(typename, '\n '.join(['{} = {}'.format(k, v) for k, v in items_dict.items()]))
namespace = dict(__name__='enum_%s' % typename)
exec(class_definition, namespace)
result = namespace[typename]
result._source = class_definition
return result
MyEnum = custom_enum('MyEnum', {'a': 123, 'b': 321})
print(MyEnum.a, MyEnum.b)
Or do you need to convert string to known Enum?
class MyEnum(Enum):
a = 'aaa'
b = 123
print(MyEnum('aaa'), MyEnum(123))
Or:
class BuildType(Enum):
debug = 200
release = 400
print(BuildType.__dict__['debug'])
print(eval('BuildType.debug'))
print(type(eval('BuildType.debug')))
print(eval(BuildType.__name__ + '.debug')) # for work with code refactoring
My Java-like solution to the problem. Hope it helps someone...
from enum import Enum, auto
class SignInMethod(Enum):
EMAIL = auto(),
GOOGLE = auto()
#classmethod
def value_of(cls, value):
for k, v in cls.__members__.items():
if k == value:
return v
else:
raise ValueError(f"'{cls.__name__}' enum not found for '{value}'")
sim = SignInMethod.value_of('EMAIL')
assert sim == SignInMethod.EMAIL
assert sim.name == 'EMAIL'
assert isinstance(sim, SignInMethod)
# SignInMethod.value_of("invalid sign-in method") # should raise `ValueError`
An improvement to the answer of #rogueleaderr :
class QuestionType(enum.Enum):
MULTI_SELECT = "multi"
SINGLE_SELECT = "single"
#classmethod
def from_str(cls, label):
if label in ('single', 'singleSelect'):
return cls.SINGLE_SELECT
elif label in ('multi', 'multiSelect'):
return cls.MULTI_SELECT
else:
raise NotImplementedError
Change your class signature to this:
class BuildType(str, Enum):
Since MyEnum['dontexist'] will result in error KeyError: 'dontexist', you might like to fail silently (eg. return None). In such case you can use the following static method:
class Statuses(enum.Enum):
Unassigned = 1
Assigned = 2
#staticmethod
def from_str(text):
statuses = [status for status in dir(
Statuses) if not status.startswith('_')]
if text in statuses:
return getattr(Statuses, text)
return None
Statuses.from_str('Unassigned')
class LogLevel(IntEnum):
critical = logging.CRITICAL
fatal = logging.FATAL
error = logging.ERROR
warning = logging.WARNING
info = logging.INFO
debug = logging.DEBUG
notset = logging.NOTSET
def __str__(self):
return f'{self.__class__.__name__}.{self.name}'
#classmethod
def _missing_(cls, value):
if type(value) is str:
value = value.lower()
if value in dir(cls):
return cls[value]
raise ValueError("%r is not a valid %s" % (value, cls.__name__))
Example:
print(LogLevel('Info'))
print(LogLevel(logging.WARNING))
print(LogLevel(10)) # logging.DEBUG
print(LogLevel.fatal)
print(LogLevel(550))
Output:
LogLevel.info
LogLevel.warning
LogLevel.debug
LogLevel.critical
ValueError: 550 is not a valid LogLevel
I just want to notify this does not work in python 3.6
class MyEnum(Enum):
a = 'aaa'
b = 123
print(MyEnum('aaa'), MyEnum(123))
You will have to give the data as a tuple like this
MyEnum(('aaa',))
EDIT:
This turns out to be false. Credits to a commenter for pointing out my mistake
I'm wondering how could one create a program to detect the following cases in the code, when comparing a variable to hardcoded values, instead of using enumeration, dynamically?
class AccountType:
BBAN = '000'
IBAN = '001'
UBAN = '002'
LBAN = '003'
I would like the code to report (drop a warning into the log) in the following case:
payee_account_type = self.get_payee_account_type(rc) # '001' for ex.
if payee_account_type in ('001', '002'): # Report on unsafe lookup
print 'okay, but not sure about the codes, man'
To encourage people to use the following approach:
payee_account_type = self.get_payee_account_type(rc)
if payee_account_type in (AccountType.IBAN, AccountType.UBAN):
print 'do this for sure'
Which is much safer.
It's not a problem to verify the == and != checks like below:
if payee_account_type == '001':
print 'codes again'
By wrapping payee_account_type into a class, with the following __eq__ implemented:
class Variant:
def __init__(self, value):
self._value = value
def get_value(self):
return self._value
class AccountType:
BBAN = Variant('000')
IBAN = Variant('001')
UBAN = Variant('002')
LBAN = Variant('003')
class AccountTypeWrapper(object):
def __init__(self, account_type):
self._account_type = account_type
def __eq__(self, other):
if isinstance(other, Variant):
# Safe usage
return self._account_type == other.get_value()
# The value is hardcoded
log.warning('Unsafe comparison. Use proper enumeration object')
return self._account_type == other
But what to do with tuple lookups?
I know, I could create a convention method wrapping the lookup, where the check can be done:
if IbanUtils.account_type_in(account_type, AccountType.IBAN, AccountType.UBAN):
pass
class IbanUtils(object):
def account_type_in(self, account_type, *types_to_check):
for type in types_to_check:
if not isinstance(type, Variant):
log.warning('Unsafe usage')
return account_type in types_to_check
But it's not an option for me, because I have a lot of legacy code I cannot touch, but still need to report on.
I have an object that encapsulate a network profile that have some characteristics. For example, my profile has a Connection and depending on it, it could or couldn't have an IP option (static or dhcp).
So, my first attempt was using a normal class that extends from dict and add some helper functions:
class Profile(dict):
IP_CONNECTIONS = ('ethernet', 'wireless', 'pppoe')
def is_ethernet(self): return self['Connection'] == 'ethernet'
def is_wireless(self): return self['Connection'] == 'wireless'
def is_wireless_adhoc(self): return self.is_wireless() and 'AdHoc' in self
def has_ip(self)
return self['Connection'] in self.IP_CONNECTIONS
def has_ip_static(self)
if not self.has_ip():
return False
if self.is_ipv4():
return self['IP'] == 'static'
if self.is_ipv6():
return self['IP6'] == 'static'
return False
def has_ip_dhcp(self):
if not self.has_ip():
return False
if self.is_ipv4():
return self['IP'] == 'dhcp'
if self.is_ipv6():
return self['IP6'] == 'dhcp' or self['IP6'] == 'dhcp-noaddr'
return False
def is_ipv4(self): return self.has_ip() and 'IP' in self
def is_ipv6(self): return self.has_ip() and 'IP6' in self
def get_client(self):
if self.has_ip_dhcp() and 'DHCPClient' in self:
return self['DHCPClient']
return None
This worked, but I had a enormous class with a lot of is_* and has_* characteristic functions. Most of them would be only used for a very specific profile, and return False most of the time.
Then it crossed my mind that I can use inheritance to describe characteristics.
After trying and failed to implement a metaclass because the data was not yet available when the __new__ method was called. I came up with something like this:
def load_profile(filename):
data = _read_profile(filename)
bases = _classify_profile(data)
baseclass = type('Profile', bases, {})
return baseclass(data)
class IP:
CONNECTIONS = ('ethernet', 'wireless')
class IPv4(IP):
def is_static(self):
return self['IP'] == 'static'
class IPv6(IP):
def is_static(self):
return self['IP6'] == 'static'
class DHCP:
def get_client(self):
return self['DHCPClient'] if 'DHCPClient' in self else None
class Wireless:
def is_adhoc(self):
return 'AdHoc' in self
def _classify_profile(data):
classes = [dict]
if data['Connection'] == 'wireless':
classes.append(Wireless)
if data['Connection'] in IP.CONNECTIONS:
if 'IP' in data:
classes.append(IPv4)
if data['IP'] == 'dhcp':
classes.append(DHCP)
if 'IP6' in data:
classes.append(IPv6)
if data['IP6'] == 'dhcp' or data['IP6'] == 'dhcp-noaddr':
classes.append(DHCP)
return tuple(classes)
When before I was doing profile.has_ip(), now I just test it with isinstance(profile, IP). This seems to me more clear with good separation of responsibility.
Question: Is this a good way of implementing dynamic inheritance? What would be the pythonic way of doing this?
Thanks in advance!
I do not really know what you mean by dynamic inheritance but I would write it this way:
base_classes = []
class IP(dict):
CONNECTIONS = ('ethernet', 'wireless')
def is_static(self):
raise NotImplementedError('To be implemented in subclasses.')
#classmethod
def wants_the_meaningful_named_data(cls, data):
return False
base_classes.append(IP)
class IPv4(IP):
def is_static(self):
return self['IP'] == 'static'
#classmethod
def wants_the_meaningful_named_data(cls, data):
return data['Connection'] in cls.CONNECTIONS and 'IP' in data
base_classes.append(IPv4)
class IPv6(IP):
def is_static(self):
return self['IP6'] == 'static'
#classmethod
def wants_the_meaningful_named_data(cls, data):
return data['Connection'] in cls.CONNECTIONS and 'IP6' in data
base_classes.append(IPv6)
def load_profile(filename):
data = _read_profile(filename)
for base_class in base_classes:
if base_class.wants_the_meaningful_named_data(data):
return base_class(data)
return dict(data)
Something like this would be what I like. I do not see the need to go into metaclasses.
I'm a python noob and I'm trying to solve my problems the 'pythonic' way. I have a class, who's __init__ method takes 6 parameters. I need to validate each param and throw/raise an Exception if any fails to validate.
Is this the right way?
class DefinitionRunner:
def __init__(self, canvasSize, flightId, domain, definitionPath, harPath):
self.canvasSize = canvasSize
self.flightId = flightId
self.domain = domain
self.harPath = harPath
self.definitionPath = definitionPath
... bunch of validation checks...
... if fails, raise ValueError ...
If you want the variables to be settable independently of __init__, you could use properties to implement validations in separate methods.
They work only for new style classes though, so you need to define the class as class DefinitionRunner(object)
So for example,
#property
def canvasSize(self):
return self._canvasSize
#canvasSize.setter
def canvasSize(self, value):
# some validation here
self._canvasSize = value
Broadly speaking, that looks like the way you'd do it. Though strictly speaking, you might as well do validation before rather than after assignment, especially if assignment could potentially be time or resource intensive. Also, style convention says not to align assignment blocks like you are.
I would do it like you did it. Except the validating stuff. I would validate in a setter method and use it to set the attributes.
You could do something like this. Make a validator for each type of input. Make a helper function to run validation:
def validate_and_assign(obj, items_d, validators):
#validate all entries
for key, validator in validators.items():
if not validator[key](items_d[key]):
raise ValueError("Validation for %s failed" % (key,))
#set all entries
for key, val in items_d.items():
setattr(obj, key, val)
Which you'd use like this:
class DefinitionRunner:
validators = {
'canvasSize': canvasSize_validator,
'flightId': flightId_validator,
'domain': domain_validator,
'definitionPath': definitionPath_validator,
'harPath': harPath_validator,
}
def __init__(self, canvasSize, flightId, domain, definitionPath, harPath):
validate_and_assign(self, {
'canvasSize': canvasSize,
'flightId': flightId,
'domain': domain,
'definitionPath': definitionPath,
'harPath': harPath,
}, DefinitionRunner.validators)
The validators might be the same function, of course, if the data type is the same.
I'm not sure if this is exactly "Pythonic", but I've defined a function decorator called require_type. (To be honest, I think I found it somewhere online.)
def require_type(my_arg, *valid_types):
'''
A simple decorator that performs type checking.
#param my_arg: string indicating argument name
#param valid_types: list of valid types
'''
def make_wrapper(func):
if hasattr(func, 'wrapped_args'):
wrapped = getattr(func, 'wrapped_args')
else:
body = func.func_code
wrapped = list(body.co_varnames[:body.co_argcount])
try:
idx = wrapped.index(my_arg)
except ValueError:
raise(NameError, my_arg)
def wrapper(*args, **kwargs):
def fail():
all_types = ', '.join(str(typ) for typ in valid_types)
raise(TypeError, '\'%s\' was type %s, expected to be in following list: %s' % (my_arg, all_types, type(arg)))
if len(args) > idx:
arg = args[idx]
if not isinstance(arg, valid_types):
fail()
else:
if my_arg in kwargs:
arg = kwargs[my_arg]
if not isinstance(arg, valid_types):
fail()
return func(*args, **kwargs)
wrapper.wrapped_args = wrapped
return wrapper
return make_wrapper
Then, to use it:
class SomeObject(object):
#require_type("prop1", str)
#require_type("prop2", numpy.complex128)
def __init__(self, prop1, prop2):
pass
I've been working on a way to get tests produced from a generator in nose to have descriptions that are customized for the specific iteration being tested. I have something that works, as long as my generator target method never tries to access self from my generator class. I'm seeing that all my generator target instances have a common test class instance while nose is generating a one-offed instance of the test class for each test run from the generator. This is resulting in setUp being run on each test instance nose creates, but never running on the instance the generator target is bound to (of course, the real problem is that I can't see how to bind the nose-created instance to the generator target). Here's the code I'm using to try to figure this all out (yes, I know the decorator would probably be better as a callable class, but nose, at least version 1.2.1 that I have, explicitly checks that tests are either functions or methods, so a callable class won't run at all):
import inspect
def labelable_yielded_case(case):
argspec = inspect.getargspec(case)
if argspec.defaults is not None:
defaults_list = [''] * (len(argspec.args) - len(argspec.defaults)) + argspec.defaults
else:
defaults_list = [''] * len(argspec.args)
argument_defaults_list = zip(argspec.args, defaults_list)
case_wrappers = []
def add_description(wrapper_id, argument_dict):
case_wrappers[wrapper_id].description = case.__doc__.format(**argument_dict)
def case_factory(*factory_args, **factory_kwargs):
def case_wrapper_wrapper():
wrapper_id = len(case_wrappers)
def case_wrapper(*args, **kwargs):
args = factory_args + args
argument_list = []
for argument in argument_defaults_list:
argument_list.append(list(argument))
for index, value in enumerate(args):
argument_list[index][1] = value
argument_dict = dict(argument_list)
argument_dict.update(factory_kwargs)
argument_dict.update(kwargs)
add_description(wrapper_id, argument_dict)
return case(*args, **kwargs)
case_wrappers.append(case_wrapper)
case_wrapper.__name__ = case.__name__
return case_wrapper
return case_wrapper_wrapper()
return case_factory
class TestTest(object):
def __init__(self):
self.data = None
def setUp(self):
print 'setup', self
self.data = (1,2,3)
def test_all(self):
for index, value in enumerate((1,2,3)):
yield self.validate_equality(), index, value
def test_all_again(self):
for index, value in enumerate((1,2,3)):
yield self.validate_equality_again, index, value
#labelable_yielded_case
def validate_equality(self, index, value):
'''element {index} equals {value}'''
print 'test', self
assert self.data[index] == value, 'expected %d got %d' % (value, self.data[index])
def validate_equality_again(self, index, value):
print 'test', self
assert self.data[index] == value, 'expected %d got %d' % (value, self.data[index])
validate_equality_again.description = 'again'
When run through nose, the again tests work just fine, but the set of tests using the decorated generator target all fail because self.data is None (because setUp is never run because the instance of TestTest stored in the closures is not the instances run by nose). I tried making the decorator an instance member of a base class for TestTest, but then nose threw errors about having too few arguments (no self) passed to the unbound labelable_yielded_case. Is there any way I can make this work (short of hacking nose), or am I stuck choosing between either not being able to have the yield target be an instance member or not having per-test labeling for each yielded test?
Fixed it (at least for the case here, though I think I got it for all cases). I had to fiddle with case_wrapper_wrapper and case_wrapper to get the factory to return the wrapped cases attached to the correct class, but not bound to any given instance in any way. I also had another code issue because I was building the argument dict in wrapper wrapper, but then not passing it to the case. Working code:
import inspect
def labelable_yielded_case(case):
argspec = inspect.getargspec(case)
if argspec.defaults is not None:
defaults_list = [''] * (len(argspec.args) - len(argspec.defaults)) + argspec.defaults
else:
defaults_list = [''] * len(argspec.args)
argument_defaults_list = zip(argspec.args, defaults_list)
case_wrappers = []
def add_description(wrapper_id, argument_dict):
case_wrappers[wrapper_id].description = case.__doc__.format(**argument_dict)
def case_factory(*factory_args, **factory_kwargs):
def case_wrapper_wrapper():
wrapper_id = len(case_wrappers)
def case_wrapper(*args, **kwargs):
argument_list = []
for argument in argument_defaults_list:
argument_list.append(list(argument))
for index, value in enumerate(args):
argument_list[index][1] = value
argument_dict = dict(argument_list)
argument_dict.update(kwargs)
add_description(wrapper_id, argument_dict)
return case(**argument_dict)
case_wrappers.append(case_wrapper)
case_name = case.__name__ + str(wrapper_id)
case_wrapper.__name__ = case_name
if factory_args:
setattr(factory_args[0].__class__, case_name, case_wrapper)
return getattr(factory_args[0].__class__, case_name)
else:
return case_wrapper
return case_wrapper_wrapper()
return case_factory
class TestTest(object):
def __init__(self):
self.data = None
def setUp(self):
self.data = (1,2,3)
def test_all(self):
for index, value in enumerate((1,2,3)):
yield self.validate_equality(), index, value
#labelable_yielded_case
def validate_equality(self, index, value):
'''element {index} equals {value}'''
assert self.data[index] == value, 'expected %d got %d' % (value, self.data[index])