Print values of class from superclass
I am using a class structure in python to keep and easily remember constants.
Here is an example of a constants hierarchy:
class classification:
class baseline:
nb, logreg = "nb", "logreg"
class neural:
perceptron, mlp = "perceptron", "mlp"
This way I can check parameters like if classifier == classification.neural.mlp: #...
I want a function to return all possible values from a given level.
If I have the class in a variable, this is achievable like this:
> [v for (k,v) in dict(vars(classification.neural)).items()
if not k.startswith("__")]
['perceptron', 'mlp']
Is there a way to do it via a common base class?
i.e. like
class def_level:
def available():
class_var = "somehow_get_this"
[v for (k,v) in dict(vars(class_var)).items() if not k.startswith("__")]
class classification:
class baseline(def_level):
nb, logreg = "nb", "logreg"
class neural(def_level):
perceptron, mlp = "perceptron", "mlp"
so that I can call classification.neural.available() from the code.
Keep in mind that no instantiation is performed.
Thanks.
python-3.x class constants
asked Nov 13 '18 at 13:14
npitnpit
4891414
add a comment |
I am using a class structure in python to keep and easily remember constants.
Here is an example of a constants hierarchy:
class classification:
class baseline:
nb, logreg = "nb", "logreg"
class neural:
perceptron, mlp = "perceptron", "mlp"
This way I can check parameters like if classifier == classification.neural.mlp: #...
I want a function to return all possible values from a given level.
If I have the class in a variable, this is achievable like this:
> [v for (k,v) in dict(vars(classification.neural)).items()
if not k.startswith("__")]
['perceptron', 'mlp']
Is there a way to do it via a common base class?
i.e. like
class def_level:
def available():
class_var = "somehow_get_this"
[v for (k,v) in dict(vars(class_var)).items() if not k.startswith("__")]
class classification:
class baseline(def_level):
nb, logreg = "nb", "logreg"
class neural(def_level):
perceptron, mlp = "perceptron", "mlp"
so that I can call classification.neural.available() from the code.
Keep in mind that no instantiation is performed.
Thanks.
python-3.x class constants
asked Nov 13 '18 at 13:14
npitnpit
4891414
add a comment |
I am using a class structure in python to keep and easily remember constants.
Here is an example of a constants hierarchy:
class classification:
class baseline:
nb, logreg = "nb", "logreg"
class neural:
perceptron, mlp = "perceptron", "mlp"
This way I can check parameters like if classifier == classification.neural.mlp: #...
I want a function to return all possible values from a given level.
If I have the class in a variable, this is achievable like this:
> [v for (k,v) in dict(vars(classification.neural)).items()
if not k.startswith("__")]
['perceptron', 'mlp']
Is there a way to do it via a common base class?
i.e. like
class def_level:
def available():
class_var = "somehow_get_this"
[v for (k,v) in dict(vars(class_var)).items() if not k.startswith("__")]
class classification:
class baseline(def_level):
nb, logreg = "nb", "logreg"
class neural(def_level):
perceptron, mlp = "perceptron", "mlp"
so that I can call classification.neural.available() from the code.
Keep in mind that no instantiation is performed.
Thanks.
python-3.x class constants
asked Nov 13 '18 at 13:14
npitnpit
4891414
I am using a class structure in python to keep and easily remember constants.
Here is an example of a constants hierarchy:
class classification:
class baseline:
nb, logreg = "nb", "logreg"
class neural:
perceptron, mlp = "perceptron", "mlp"
This way I can check parameters like if classifier == classification.neural.mlp: #...
I want a function to return all possible values from a given level.
If I have the class in a variable, this is achievable like this:
> [v for (k,v) in dict(vars(classification.neural)).items()
if not k.startswith("__")]
['perceptron', 'mlp']
Is there a way to do it via a common base class?
i.e. like
class def_level:
def available():
class_var = "somehow_get_this"
[v for (k,v) in dict(vars(class_var)).items() if not k.startswith("__")]
class classification:
class baseline(def_level):
nb, logreg = "nb", "logreg"
class neural(def_level):
perceptron, mlp = "perceptron", "mlp"
so that I can call classification.neural.available() from the code.
Keep in mind that no instantiation is performed.
Thanks.
python-3.x class constants
python-3.x class constants
asked Nov 13 '18 at 13:14
npitnpit
4891414
asked Nov 13 '18 at 13:14
npitnpit
4891414
asked Nov 13 '18 at 13:14
npitnpit
4891414
asked Nov 13 '18 at 13:14
npitnpit
4891414
asked Nov 13 '18 at 13:14
npitnpit
4891414
4891414
add a comment |
add a comment |
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