Avatto>>DATA SCIENTIST>>SHORT QUESTIONS>>Python Interview Questions
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.
In Python, we use range(0,10) to create a list in memory for 10 numbers.

Python provides another function xrange() that is similar to range() but xrange() returns a sequence object instead of list object. In xrange() all the values are not stored simultaneously in memory. It is a lazy loading based function.

But as per Python documentation, the benefit of xrange() over range() is very minimal in regular scenarios.
As of version 3.1, xrange is deprecated.
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_
We can use Generator to create Iterators in Python. A Generator is written like a regular function. It can make use of yield statement to return data during the function call. In this way, we can write complex logic that works as an Iterator.

A Generator is more compact than an Iterator due to the fact that _iter_() and next() functions are automatically created in a Generator.

Also within a Generator code, local variables and execution state is saved between multiple calls. Therefore, there is no need to add extra variables like self.index, etc to keep track of iteration.

Generator also increases the readability of the code written in Python. It is a very simple implementation of an Iterator.
An Iterable is an object that can be iterated by an Iterator.

In Python, Iterator object provides _iter_() and next() methods.

In Python, an Iterable object has _iter_ function that returns an Iterator object.

When we work on a map or a for loop in Python, we can use next() method to get an Iterable item from the Iterator.


Description