Dynamically generate class objects by digesting key-value / pairwise data structures as object specifications.
objgen has no external dependencies, can be used immediately, and is more fun (and less limiting) than calling type('NewClassName', (*inheritances), {'attr': 'value'}).
>>> from objgen.generators.generic import Base
>>> base = Base()
>>> vars(base)
{}Pass a dictionary to a generator instance to construct its object, then use the object.
>>> hydrated = Base({'attr1': 'val1', 'attr2': 'val2'}, attr3='val3')
>>> vars(hydrated)
{'attr1': 'val1', 'attr2': 'val2', 'attr3': 'val3'}
>>> hydrated.attr1, hydrated.attr2, hydrated.attr3
('val1', 'val2', 'val3')Any input that can be cast into a dictionary will be digested; any data that cannot will be discarded.
>>> from objgen.generators.generic import Base
>>> b = Base(
... {'this': 'is', 'valid': 'input'},
... 'this_is_not_pairwise_data',
... [('this', 'however'), ('will', 'work'), ('just', 'fine')]
... )
Element cannot be cast into dict, and is being discarded: <class 'str'> this_is_not_pairwise_dataIf multiples of a field exists in a given collection of input arguments, the most recent passed value for that field will be preserved.
>>> b = Base({'this': 'is'}, [('this', 'however'), ])
>>> b
Base ['this']
>>> b.this
'however'- nesting is possible, intentional, and half the point of all this!
- nesting can be recursive, if we let it
- recursive nesting can be inclusively/exclusively filtered
Say we want to create a dog, but also be able to access/call a dog.actions.{action}.
>>> dog_info = {
... 'name': 'monty',
... 'breed': 'donkey child',
... 'is_good_boy': True,
... 'actions': {'run_to': 'car', 'bark_at': 'squirrel', 'pee_on': 'hydrant'},
... }Instantiate and hydrate a generator as dog, then do the same to the resulting dog.actions.
>>> from objgen.generators.generic import Base
>>>
>>> dog = Base(dog_info)
>>> dog.actions
{'run_to': 'car', 'bark_at': 'squirrel', 'pee_on': 'hydrant'}
>>> dog.actions = Base(dog.actions)
>>> dog.actions.run_to
'car'Let's make a Recursive generator to digest the full depth of the data structure -- having to call cls.attr = Base(cls.attr) for every single nested attributes at each given 'depth' is ridiculous.
Whereas a Base generator will simply create cls.key = value relationships,
setattr(self, field, spec[field])a Recursive generator will continue to digest any dictionary objects it encounters along any nesting path.
if isinstance(spec[field], dict):
setattr(self, field, Recursive(spec[field]))Let's try making our dog again, but with a Recursive generator:
>>> from objgen.generators.generic import Recursive
>>>
>>> dog = Recursive(dog_info)
>>> dog.actions
<objgen.generators.generic.Recursive object at 0x7f2bb4ef2c18>
>>> dog.actions.run_to
'car'So far so good - except, what if we want certain things to stay as dictionaries, rather than be indiscriminately digested?
For example, we want to add our dog's friends, and be able to access dog.friends - however, it would be silly for each {friend} to become a dog.friends.{friend} attribute instead of staying preserved as elements in a data structure.
... dog_info.update(
... {
... 'friends': {
... 'lassie': {'breed': 'collie', 'met_at': 'dog park'},
... 'marnie': {'breed': 'shih tzu', 'met_at': 'dms'},
... 'air_bud': {'breed': 'golden retriever', 'met_at': 'basketball courts'},
... 'laika': {'breed': 'mongrel', 'met_at': 'outer space'}
... }
... }
...)Let's make a RecursiveFiltered that deals with this for us.
Optionally, supply either _exclude or _include_only keyword arguments when creating the RecursiveFilter to determine which fields are (dis)allowed to be digested.
>>> from objgen.generators.generic import RecursiveFiltered
>>>
>>> dog = RecursiveFiltered(dog_info, _exclude='friends')
>>>
>>> type(dog.actions)
<class 'objgen.generators.generic.RecursiveFiltered'>
>>> type(dog.friends)
<class 'dict'>Note that excluding a field means that digestion along that path in the data tree will terminate at that field, rather than skip that field and continue down that path's depth.
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