Python Reflection: Introspection and Dynamic Code Exploration

In object-oriented programming, reflection refers to the ability to extract information about any object in use. You can get to know the type of object, is it a subclass of any other class, what are its attributes and much more. Python's standard library has a number of functions that reflect on different properties of an object. Reflection is also sometimes called introspect.

Let us take a review of reflection functions.

The type() Function

We have used this function many times. It tells you which class does an object belong to.

Example

Following statements print the respective class of different built-in data type objects

Here, you will get the following output −

<class 'int'>
<class 'float'>
<class 'complex'>
<class 'str'>
<class 'list'>
<class 'dict'>

Let us verify the type of an object of a user-defined class −

It will produce the following output −

<class '__main__.test'>

The isinstance() Function

This is another built-in function in Python which ascertains if an object is an instance of the given class

Syntax

This function always returns a Boolean value, true if the object is indeed belongs to the given class and false if not.

Example

Following statements return True −

In contrast, these statements print False.

It will produce the following output −

True
True
True
True
False
False

You can also perform check with a user defined class

It will produce the following output −

True

In Python, even the classes are objects. All classes are objects of object class. It can be verified by following code −

All the above print statements print True.

The issubclass() Function

This function checks whether a class is a subclass of another class. Pertains to classes, not their instances.

As mentioned earlier, all Python classes are subclassed from object class. Hence, output of following print statements is True for all.

It will produce the following output −

True
True
True

The callable() Function

An object is callable if it invokes a certain process. A Python function, which performs a certain process, is a callable object. Hence callable(function) returns True. Any function, built-in, user defined or a method is callable. Objects of built-in data types such as int, str, etc., are not callable.

Example

A string object is not callable. But abs is a function which is callable. The pop method of list is callable, but clear() is actually call to the function and not a function object, hence not a callable

It will produce the following output −

False
True
True
False
True

A class instance is callable if it has a __call__() method. In the example below, the test class includes __call__() method. Hence, its object can be used as if we are calling function. Hence, object of a class with __call__() function is a callable.

It will produce the following output −

Hello
obj is callable? True

The getattr() Function

The getattr() built-in function retrieves the value of the named attribute of object.

Example

It will produce the following output −

Manav

The setattr() Function

The setattr() built-in function adds a new attribute to the object and assigns it a value. It can also change the value of an existing attribute.

In the example below, the object of test class has a single attribute − name. We use setattr to add age attribute and to modify the value of name attribute.

It will produce the following output −

Madhav 20

The hasattr() Function

This built-in function returns True if the given attribute is available to the object argument, and false if not. We use the same test class and check if it has a certain attribute or not.

It will produce the following output −

False
True

The dir() Function

If his built in function called without an argument, return the names in the current scope. Fpr any object as argument, it returns a list the attributes of the given object, and of attributes reachable from it.

• For a module object − the function returns the module's attributes.

• For a class object − the function returns its attributes, and recursively the attributes of its bases.

• For any other object − its attributes, its class's attributes, and recursively the attributes of its class's base classes.

Example

It will produce the following output −

dir(int): ['__abs__', '__add__', '__and__', '__bool__', '__ceil__', '__class__', '__delattr__', '__dir__', '__divmod__', '__doc__', '__eq__', '__float__', '__floor__', '__floordiv__', '__format__', '__ge__', '__getattribute__', '__getnewargs__', '__getstate__', '__gt__', '__hash__', '__index__', '__init__', '__init_subclass__', '__int__', '__invert__', '__le__', '__lshift__', '__lt__', '__mod__', '__mul__', '__ne__', '__neg__', '__new__', '__or__', '__pos__', '__pow__', '__radd__', '__rand__', '__rdivmod__', '__reduce__', '__reduce_ex__', '__repr__', '__rfloordiv__', '__rlshift__', '__rmod__', '__rmul__', '__ror__', '__round__', '__rpow__', '__rrshift__', '__rshift__', '__rsub__', '__rtruediv__', '__rxor__', '__setattr__', '__sizeof__', '__str__', '__sub__', '__subclasshook__', '__truediv__', '__trunc__', '__xor__', 'as_integer_ratio', 'bit_count', 'bit_length', 'conjugate', 'denominator', 'from_bytes', 'imag', 'numerator', 'real', 'to_bytes']

Example

It will produce the following output −

dir(dict): ['__class__', '__class_getitem__', '__contains__', '__delattr__', '__delitem__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__getitem__', '__getstate__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__ior__', '__iter__', '__le__', '__len__', '__lt__', '__ne__', '__new__', '__or__', '__reduce__', '__reduce_ex__', '__repr__', '__reversed__', '__ror__', '__setattr__', '__setitem__', '__sizeof__', '__str__', '__subclasshook__', 'clear', 'copy', 'fromkeys', 'get', 'items', 'keys', 'pop', 'popitem', 'setdefault', 'update', 'values']

Example

It will produce the following output −

dir(obj): ['__class__', '__delattr__', '__dict__', '__dir__', '__doc__',


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