Check if object attributes are non-empty python

If your class defines (on Py2) __nonzero__, (on Py3) __bool__ or (on either) __len__, then that will be used to evaluate the “truthiness” of objects of that class (if only __len__ is defined, an instance is truthy when it returns non-zero, and falsy when it returns zero). So, for example, to make your class simply report if it’s attributes are non-empty in either Py2 or Py3, you’d add:

 def __bool__(self):
     return bool(self.lis1 or self.dict1)
 __nonzero__ = __bool__ # To make it work on Py2 too

Alternatively, if your class instances have meaningful lengths, you define:

 def __len__(self):
     return len(self.lis1) + len(self.dict1)  # For example; I doubt the length is meaningful in terms of both

and get boolean behavior by side-effect of supporting len(myobject).

It is given in the documentation of Truth value testing for Python 2.x –

instances of user-defined classes, if the class defines a __nonzero__() or __len__() method, when that method returns the integer zero or bool value False.

For Python 3.x –

instances of user-defined classes, if the class defines a __bool__() or __len__() method, when that method returns the integer zero or bool value False.

According to the definition of your class, if maybe meaningful to define __len__() method, which returns the sum of length of the list as well as the dict.Then this method would be called to determine whether to interpret the object as True or False in boolean context. Example –

class my_class(object):
    def __init__(self):
        self.lis1 = []
        self.dict1 = {}
    def __len__(self):
        print("In len")
        return len(self.lis1) + len(self.dict1)

Demo –

>>> class my_class(object):
...     def __init__(self):
...         self.lis1 = []
...         self.dict1 = {}
...     def __len__(self):
...         print("In len")
...         return len(self.lis1) + len(self.dict1)
...
>>> obj = my_class()
>>> if obj:
...     print("yes")
...
In len
>>> obj.lis1.append(1)
>>>
>>> if obj:
...     print("yes")
...
In len
yes

Combining the answers for using any() and __bool__(self), the following code will allow you to check for all of the attributes using list comprehension.

class my_class(object):
    def __init__(self):
        self.list1 = []
        self.dict1 = {}

    def __bool__(self):
        check = any([self.__dict__[attr] for attr in self.__dict__.keys()])

        return check

obj1 = my_class()

if obj1:
    print('yes')

This code snippet will print nothing as expected.

As many answers and duplicate votes suggest, you need to override the __nonzero__ method. However, from your comment, you also want to avoid enumerating the attributes explicitly. This can be done with a trick like this:

class Example(object):
    def __init__(self):
        self._values = {}
        self.attr1 = []
        self.attr2 = {}

    def __setattr__(self, name, value):
        self.__dict__[name] = value
        if not name.startswith('_'):
            self._values[name] = value  # keep track of the assigned attributes

    def __nonzero__(self):
        return any(self._values.itervalues())

This handles all public attributes that are assigned or modified later on:

>>> ex = Example()
>>> bool(ex)
False
>>> ex.attr1.append('data')
>>> bool(ex)
True
>>> ex.attr1.pop()
>>> ex.attr3 = 42
bool(ex)
>>> False

Attribute deletion is not handled properly, for that you need to override __delattr__.

The build in vars() function makes a useful one-liner for checking if an object has any non-empty attributes. Combine it with __nonzero__ and you get the following:

def __nonzero__(self):
    return any(vars(self).values())

In python you wouldn’t know which attributes to expect if you do not declare them. A standard way to declare attributes is supplied in the dataclass

see https://docs.python.org/3/library/dataclasses.html

from dataclasses import dataclass

@dataclass
class my_class:
   lis1:list = []
   dict1:dict = {}

   def isEmtpy(self)->bool:
      return len(self.lis1)+len(self.dict1)==0

To implement a more generic solution you might want to inspect the dataclass source code at https://github.com/python/cpython/blob/3.11/Lib/dataclasses.py especially the fields accessor