Creating class instance properties from a dictionary?
Question:
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?
Answers:
You can use setattr (be careful though: not every string is a valid attribute name!):
>>> class AllMyFields:
... def __init__(self, dictionary):
... for k, v in dictionary.items():
... setattr(self, k, v)
...
>>> o = AllMyFields({'a': 1, 'b': 2})
>>> o.a
1
Edit: let me explain the difference between the above code and SilentGhost’s answer. The above code snippet creates a class of which instance attributes are based on a given dictionary. SilentGhost’s code creates a class whose class attributes are based on a given dictionary.
Depending on your specific situation either of these solutions may be more suitable. Do you plain to create one or more class instances? If the answer is one, you may as well skip object creation entirely and only construct the type (and thus go with SilentGhost’s answer).
>>> q = { 'Field1' : 3000, 'Field2' : 6000, 'RandomField' : 5000 }
>>> q = type('allMyFields', (object,), q)
>>> q.Field1
3000
docs for type explain well what’s going here (see use as a constructor).
edit: in case you need instance variables, the following also works:
>>> a = q() # first instance
>>> a.Field1
3000
>>> a.Field1 = 1
>>> a.Field1
1
>>> q().Field1 # second instance
3000
You can also use dict.update instead of manually looping over items (and if you’re looping, iteritems is better).
class allMyFields(object):
# note: you cannot (and don't have to) use self here
Field1 = None
Field2 = None
def __init__(self, dictionary):
self.__dict__.update(dictionary)
q = { 'Field1' : 3000, 'Field2' : 6000, 'RandomField' : 5000 }
instance = allMyFields(q)
print instance.Field1 # => 3000
print instance.Field2 # => 6000
print instance.RandomField # => 5000
Use setattr for the pretty way. The quick-n-dirty way is to update the instance internal dictionary:
>>> class A(object):
... pass
...
>>> a = A()
>>> a.__dict__.update({"foo": 1, "bar": 2})
>>> a.foo
1
>>> a.bar
2
>>>
Using named tuples (Python 2.6):
>>> from collections import namedtuple
>>> the_dict = {'Field1': 3, 'Field2': 'b', 'foo': 4.9}
>>> fields = ' '.join(the_dict.keys())
>>> AllMyFields = namedtuple('AllMyFields', fields)
>>> instance = AllMyFields(**the_dict)
>>> print instance.Field1, instance.Field2, instance.foo
3 b 4.9
You could make a subclass of dict which allows attribute lookup for keys:
class AttributeDict(dict):
def __getattr__(self, name):
return self[name]
q = AttributeDict({ 'Field1' : 3000, 'Field2' : 6000, 'RandomField' : 5000 })
print q.Field1
print q.Field2
print q.RandomField
If you try to look up an attribute that dict already has (say keys or get), you’ll get that dict class attribute (a method). If the key you ask for doesn’t exist on the dict class, then the __getattr__ method will get called and will do your key lookup.
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__)
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)
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)])
"""
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/
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))(*field_dict.values())
# Using attrs
from attrs import make_class
field_obj = make_class("FieldData", list(field_dict))(*field_dict.values())
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?
You can use setattr (be careful though: not every string is a valid attribute name!):
>>> class AllMyFields:
... def __init__(self, dictionary):
... for k, v in dictionary.items():
... setattr(self, k, v)
...
>>> o = AllMyFields({'a': 1, 'b': 2})
>>> o.a
1
Edit: let me explain the difference between the above code and SilentGhost’s answer. The above code snippet creates a class of which instance attributes are based on a given dictionary. SilentGhost’s code creates a class whose class attributes are based on a given dictionary.
Depending on your specific situation either of these solutions may be more suitable. Do you plain to create one or more class instances? If the answer is one, you may as well skip object creation entirely and only construct the type (and thus go with SilentGhost’s answer).
>>> q = { 'Field1' : 3000, 'Field2' : 6000, 'RandomField' : 5000 }
>>> q = type('allMyFields', (object,), q)
>>> q.Field1
3000
docs for type explain well what’s going here (see use as a constructor).
edit: in case you need instance variables, the following also works:
>>> a = q() # first instance
>>> a.Field1
3000
>>> a.Field1 = 1
>>> a.Field1
1
>>> q().Field1 # second instance
3000
You can also use dict.update instead of manually looping over items (and if you’re looping, iteritems is better).
class allMyFields(object):
# note: you cannot (and don't have to) use self here
Field1 = None
Field2 = None
def __init__(self, dictionary):
self.__dict__.update(dictionary)
q = { 'Field1' : 3000, 'Field2' : 6000, 'RandomField' : 5000 }
instance = allMyFields(q)
print instance.Field1 # => 3000
print instance.Field2 # => 6000
print instance.RandomField # => 5000
Use setattr for the pretty way. The quick-n-dirty way is to update the instance internal dictionary:
>>> class A(object):
... pass
...
>>> a = A()
>>> a.__dict__.update({"foo": 1, "bar": 2})
>>> a.foo
1
>>> a.bar
2
>>>
Using named tuples (Python 2.6):
>>> from collections import namedtuple
>>> the_dict = {'Field1': 3, 'Field2': 'b', 'foo': 4.9}
>>> fields = ' '.join(the_dict.keys())
>>> AllMyFields = namedtuple('AllMyFields', fields)
>>> instance = AllMyFields(**the_dict)
>>> print instance.Field1, instance.Field2, instance.foo
3 b 4.9
You could make a subclass of dict which allows attribute lookup for keys:
class AttributeDict(dict):
def __getattr__(self, name):
return self[name]
q = AttributeDict({ 'Field1' : 3000, 'Field2' : 6000, 'RandomField' : 5000 })
print q.Field1
print q.Field2
print q.RandomField
If you try to look up an attribute that dict already has (say keys or get), you’ll get that dict class attribute (a method). If the key you ask for doesn’t exist on the dict class, then the __getattr__ method will get called and will do your key lookup.
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__)
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)
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)])
"""
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/
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))(*field_dict.values())
# Using attrs
from attrs import make_class
field_obj = make_class("FieldData", list(field_dict))(*field_dict.values())