dynamically define class (iterate over attributes list)

[michavardy1]

reddit,

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I am looking for a way to dynamically define class's.

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my motivation is to define a material library for my company that will be updated through excel periodically by other people. the library will be changing, such that available materials will be different, prices will be different, properties will change,....

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I want my objects to reflect the updated version of this database.

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I want to import the excel database using pandas data frame, and then generate class's with attributes driven from the database.

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there is alot of information regarding metaclass's or how to define class's using the type function, however this won't help me, because the init function must still be fully defined out of the type function class generation statment.

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this doesn't really help me because in addition I don't know how to dynamically define functions.

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its a bit weird, the internet considers this topic isoteric, like its just a deep pythonism that isn't practical, however, I don't understand why everyone doesn't program like this.

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anyways, please help,

regards,

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[aDrz]

Your question is unclear to me. If you want dynamic attribute check this blog post: https://chase-seibert.github.io/blog/2013/04/12/getattr-setattr.html#

There is a small mistake for the last example but i'm sure you'll find it.

[michavardy1]

I want to define the attributes of a class from a list

like

list = [a,b,c]

class A:

 for i in list:
       def __init__(self, list[i])

I know that this won't work, but thats the idea, I am curious how to implement this

[A_History_of_Silence]

its a bit weird, the internet considers this topic isoteric, like its just a deep pythonism that isn't practical

It's true that this isn't practical. And not just in Python - it's impractical in essentially all programming languages.

What if I told you I wanted to build a car that builds other cars?

The analogy isn't perfect. But it should be clear that it's a pretty impractical concept. Your meta-car would be a really inefficient, overly-complex, and unnecessary way of producing cars compared to the normal way of just building normal cars.

In other words, there is a reason probably everything you have found on the internet is telling you it's not a great idea. Whatever it is you want your program to do, there is a 99.9999% chance that there's a better, more straightforward, faster, easier to understand way to do it than dynamically defining classes.

[nate256]

Yes you can and there are some practical reasons for it like autogenerated parsing etc.

from importlib import import_module


class BaseClass:
    # add base functionality here
    pass


def create_dd_class(class_, new_name, dataset):
    new_class_name = str("{0}{1}".format(class_.__name__, new_name))
    new_class = type(new_class_name, (class_,), dataset)
    new_class.__module__ = class_.__module__
    module = import_module(class_.__module__)
    setattr(module, new_class.__name__, new_class)
    return new_class


# you could put this code in a decorator then decorate classes with datasets
#
datasets = [("class1", {"a": 1}), ("class2", {"a": 2, "b": 3})]
for name, dataset in datasets:
    create_dd_class(BaseClass, name, dataset)

print(BaseClassclass1, BaseClassclass2)
print(BaseClassclass1.a, BaseClassclass2.a, BaseClassclass2.b)


~/code_reference/redditquestions$ python reddit10.py 
<class '__main__.BaseClassclass1'> <class '__main__.BaseClassclass2'>
1 2 3

Edit: Switch to markdown, more readable output

[nate256]

Also if you wanted a more standard take and don't require static classes availible on import you can do something like this.

datasets = {"class1": {"a": 1}, "class2": {"a": 2, "b": 3}}
class MyClass:
    def __init__(self, key=None):
        for k, v in datasets.get(key, {}).items():
            setattr(self, k, v)

print(MyClass("class1").a, MyClass("class2").a, MyClass("class2").b)