Ans : Python provides many built-in functions that are surrounded by _ symbol at the start and end of the function name. As per Python documentation, double _ symbol is used for reserved names of functions.

These are also known as System-defined names. Some of the important functions are : 

• Object._new_
• Object._init_
• Object._del_

As of version 3.1, xrange is deprecated.

23. What is lambda expression in Python?

Ans : A lambda expression in Python is used for creating an anonymous function. Wherever we need a function, we can also use a lambda expression.

We have to use lambda keyword for creating a lambda expression. Syntax of lambda function is as follows:

lambda argumentList: expression

E.g. lambda a,b: a+b

The above mentioned lambda expression takes two arguments and returns their sum.

We can use lambda expression to return a function.

A lambda expression can be used to pass a function as an argument in another function.

24. How will you copy an object in Python?

Ans : In Python we have two options to copy an object. It is similar to cloning an object in Java.

• Shallow Copy: To create a shallow copy we call copy.copy(x). In a shallow copy, Python creates a new compound object based on the original object. And it tries to put references from the original object into copy object.
• Deep Copy: To create a deep copy, we call copy.deepcopy(x). In a deep copy, Python creates a new object and recursively creates and inserts copies of the objects from original object into copy object. In a deep copy, we may face the issue of recursive loop due to infinite recursion.

Easy to learn: Python is simple language. It is easy to learn for a new programmer.

Large library: There is a large library for utilities in Python that can be used for different kinds of applications.

Readability: Python has a variety of statements and expressions that are quite readable and very explicit in their use. It increases the readability of overall code.

Memory management: In Python, memory management is built into the Interpreter. So a developer does not have to spend effort on managing memory among objects.

Complex built-in Data types: Python has built-in Complex data types like list, set, dict etc. These data types give very good performance as well as save time in coding new features.

26. What is a meta class in Python?

Ans : A metaclass in Python is also known as class of a class. A class defines the behavior of an instance. A metaclass defines the behavior of a class.

One of the most common metaclass in Python is type. We can subclass type to create our own metaclass.

We can use metaclass as a class-factory to create different types of classes.

27. What is the use of frozen set in Python?

Ans : A frozenset is a collection of unique values in Python. In addition to all the properties of set, a frozenset is immutable and hashable.

Once we have set the values in a frozenset, we cannot change. So we cannot use and update methods from set on frozenset.

Being hashable, we can use the objects in frozenset as keys in a Dictionary.

28. What is Python Flask?

Ans : Python Flask is a micro-framework based on Python to develop a web application.

It is a very simple application framework that has many extensions to build an enterprise level application.

Flask does not provide a data abstraction layer or form validation by default. We can use external libraries on top of Flask to perform such tasks.

29. What is None in Python?

Ans : None is a reserved keyword used in Python for null objects. It is neither a null value nor a null pointer. It is an actual object in Python. But there is only one instance of None in a Python environment.

We can use None as a default argument in a function.

During comparison we have to use “is” operator instead of “==” for None.

30. What is the use of zip() function in Python?

Ans : In Python, we have a built-in function zip() that can be used to aggregate all the Iterable objects of an Iterator.

We can use it to aggregate Iterable objects from two iterators as well. E.g.

list_1 = [‘a’, ‘b’, ‘c’]

list_2 = [‘1’, ‘2’, ‘3’]

for a, b in zip(list_1, list_2): print a, b

Output:

a1 

b2 

c3

By using zip() function we can divide our input data from different sources into fixed number of sets.