Creating class instance properties from a dictionary?

user_35335 0
Viewed 87881

I'm importing from a CSV and getting data roughly in the format

{ 'Field1' : 3000, 'Field2' : 6000, 'RandomField' : 5000 }

The names of the fields are dynamic. (Well, they're dynamic in that there might be more than Field1 and Field2, but I know Field1 and Field2 are always going to be there.

I'd like to be able to pass in this dictionary into my class allMyFields so that I can access the above data as properties.

class allMyFields:
    # I think I need to include these to allow hinting in Komodo. I think.
    self.Field1 = None
    self.Field2 = None

    def __init__(self,dictionary):
        for k,v in dictionary.items():
            self.k = v
            #of course, this doesn't work. I've ended up doing this instead
            #self.data[k] = v
            #but it's not the way I want to access the data.

q = { 'Field1' : 3000, 'Field2' : 6000, 'RandomField' : 5000 }
instance = allMyFields(q)
# Ideally I could do this.
print q.Field1

Any suggestions? As far as why -- I'd like to be able to take advantage of code hinting, and importing the data into a dictionary called data as I've been doing doesn't afford me any of that.

(Since the variable names aren't resolved till runtime, I'm still going to have to throw a bone to Komodo - I think the self.Field1 = None should be enough.)

So - how do I do what I want? Or am I barking up a poorly designed, non-python tree?

komodo class python
11 Answers
class SomeClass:
    def __init__(self,
                 property1,
                 property2):
       self.property1 = property1
       self.property2 = property2


property_dict = {'property1': 'value1',
                 'property2': 'value2'}
sc = SomeClass(**property_dict)
print(sc.__dict__)
user_107060980

enhanced of sub class of dict

recurrence dict works!

class AttributeDict(dict):
    """https://stackoverflow.com/a/1639632/6494418"""

    def __getattr__(self, name):
        return self[name] if not isinstance(self[name], dict) \
            else AttributeDict(self[name])


if __name__ == '__main__':
    d = {"hello": 1, "world": 2, "cat": {"dog": 5}}
    d = AttributeDict(d)
    print(d.cat)
    print(d.cat.dog)
    print(d.cat.items())

    """
    {'dog': 5}
    5
    dict_items([('dog', 5)])
    """
user_64944180

Or you can try this

class AllMyFields:
    def __init__(self, field1, field2, random_field):
        self.field1 = field1
        self.field2 = field2
        self.random_field = random_field

    @classmethod
    def get_instance(cls, d: dict):
        return cls(**d)


a = AllMyFields.get_instance({'field1': 3000, 'field2': 6000, 'random_field': 5000})
print(a.field1)
user_62396350

If you are open for adding a new library, pydantic is a very efficient solution. It uses python annotation to construct object and validate type Consider the following code:

from pydantic import BaseModel

class Person(BaseModel):
    name: str
    age: str


data = {"name": "ahmed", "age": 36}

p = Person(**data)

pydantic: https://pydantic-docs.helpmanual.io/

user_39065710

A simple solution is

field_dict = { 'Field1' : 3000, 'Field2' : 6000, 'RandomField' : 5000 }

# Using dataclasses
from dataclasses import make_dataclass
field_obj = make_dataclass("FieldData", list(field_dict.keys()))(*field_dict.values())

# Using attrs
from attrs import make_class
field_obj = make_class("FieldData", list(field_dict.keys()))(*field_dict.values())
user_101836460
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