In python how can we create a new object without having a predefined Class and later dynamically add properties to it ?
example:
dynamic_object = Dynami
If you take metaclassing approach from @Martijn's answer, @Ned's answer can be rewritten shorter (though it's obviously less readable, but does the same thing).
obj = type('Expando', (object,), {})()
obj.foo = 71
obj.bar = 'World'
Or just, which does the same as above using dict
argument:
obj = type('Expando', (object,), {'foo': 71, 'bar': 'World'})()
For Python 3, passing object to bases
argument is not necessary (see type documentation).
But for simple cases instantiation doesn't have any benefit, so is okay to do:
ns = type('Expando', (object,), {'foo': 71, 'bar': 'World'})
At the same time, personally I prefer a plain class (i.e. without instantiation) for ad-hoc test configuration cases as simplest and readable:
class ns:
foo = 71
bar = 'World'
In Python 3.3+ there is exactly what OP asks for, types.SimpleNamespace. It's just:
A simple
object
subclass that provides attribute access to its namespace, as well as a meaningful repr.Unlike
object
, withSimpleNamespace
you can add and remove attributes. If aSimpleNamespace
object is initialized with keyword arguments, those are directly added to the underlying namespace.
import types
obj = types.SimpleNamespace()
obj.a = 123
print(obj.a) # 123
print(repr(obj)) # namespace(a=123)
However, in stdlib of both Python 2 and Python 3 there's argparse.Namespace, which has the same purpose:
Simple object for storing attributes.
Implements equality by attribute names and values, and provides a simple string representation.
import argparse
obj = argparse.Namespace()
obj.a = 123
print(obj.a) # 123
print(repr(obj)) # Namespace(a=123)
Note that both can be initialised with keyword arguments:
types.SimpleNamespace(a = 'foo',b = 123)
argparse.Namespace(a = 'foo',b = 123)
Just define your own class to do it:
class Expando(object):
pass
ex = Expando()
ex.foo = 17
ex.bar = "Hello"
One way that I found is also by creating a lambda. It can have sideeffects and comes with some properties that are not wanted. Just posting for the interest.
dynamic_object = lambda:expando
dynamic_object.dynamic_property_a = "abc"
dynamic_object.dynamic_property_b = "abcdefg"
Use the collections.namedtuple() class factory to create a custom class for your return value:
from collections import namedtuple
return namedtuple('Expando', ('dynamic_property_a', 'dynamic_property_b'))('abc', 'abcdefg')
The returned value can be used both as a tuple and by attribute access:
print retval[0] # prints 'abc'
print retval.dynamic_property_b # prints 'abcdefg'
Using an object just to hold values isn't the most Pythonic style of programming. It's common in programming languages that don't have good associative containers, but in Python, you can use use a dictionary:
my_dict = {} # empty dict instance
my_dict["foo"] = "bar"
my_dict["num"] = 42
You can also use a "dictionary literal" to define the dictionary's contents all at once:
my_dict = {"foo":"bar", "num":42}
Or, if your keys are all legal identifiers (and they will be, if you were planning on them being attribute names), you can use the dict
constructor with keyword arguments as key-value pairs:
my_dict = dict(foo="bar", num=42) # note, no quotation marks needed around keys
Filling out a dictionary is in fact what Python is doing behind the scenes when you do use an object, such as in Ned Batchelder's answer. The attributes of his ex
object get stored in a dictionary, ex.__dict__
, which should end up being equal to an equivalent dict
created directly.
Unless attribute syntax (e.g. ex.foo
) is absolutely necessary, you may as well skip the object entirely and use a dictionary directly.