You must be aware of the fact that Python is the most popular language in the Data Science market at the present time. According to a survey done in 2018, 48% of the engagers voted for Python as the most essential language for a Data Scientist following the trend again the survey in 2019 says that 75% of the engagers believe Python to be the backbone for the Data Scientists.
After all, these reports there is no doubt that Python is the largest growing language in today's world and is in huge demand because of its skill set which it endorses.
Here are the top 10 very important questions which are commonly asked in every interview:-
1. What is Python? What are the benefits of using Python?
Python is a programming language with objects, modules, threads, exceptions & automatic memory management. The benefits of this language are that it is very simple and easy to use portable, extensible, built-in data structure & it is an open source.
2. What do you understand by Tuple? Differentiate between lists & tuples in Python?
Both lists and tuples are a series of data types that store a number of items. Each item in a program can be deposited in a list or a tuple & can be of any data sample.
But one of the major difference between the two of them is that lists are mutable whereas tuples are immutable. This simply means that in lists one has a chance of modifying the values but unlike lists, modification cannot be done in a tuple(in other words it means that they cannot be copied).
Another difference between them is tuples are extensively used to store heterogeneous elements, which are the components belonging to different data types whereas lists are used to store homogenous components which are components that belong to the same data type.
One very noticeable difference between both of them is lists are in square brackets and tuple are in the round brackets.
An immutable object can also be used as a key in a dictionary and in this way tuples can be used as dictionary keys if needed at any time.
3. Explain Pickling & Unpickling?
Pickling & Unpickling is practiced for serializing & deserializing the structure of an object in Python.
Any object in Python is free to be pickled so that it can be stored on disk. Before writing it to file Pickling basically serializes the object into binary streams first. It is a way to convert a Python object into a character stream. This is actually very useful for someone who wants to save the state if his objects and if needed can reuse them without losing any data.
Similar logic is used in the games domain. When one restores a saved game he will be loading data from its pickled state, therefore, unpickling it. Pickling & Unpickling enables you to efficiently send data from one server to different & eventually save it in a file or database.
4. How is memory managed in Python?
Memory management in Python involves a private volume containing all Python objects & data structures. Management of this private heap is secured inwardly by the Python memory manager.
There are different components of the Python memory manager which deals with the various dynamic storage management aspects like sharing, segmentation, prelocation or caching.
At the lowest level, a raw memory allocator assures that there is ample room in the private block for storing all the data by communicating with the memory manager of the operating system. On top of the raw memory allocator, various object-specific allocators operate on the same block & achieve distinct memory management strategies.
The memory manager thus assigns some of the work to the object-specific allocators, but at the same time assures that the letter operates within the bounds of the private stock.
5. What are Python modules? Name some of the commonly used built-in modules in Python?
Python has a separate design to put definitions in a file & use them accordingly in a script or in an interactive case of the interpreter. Such a file can be called as a module which is generally a file holding Python definitions & statements.
Definitions from a module can be imported into different modules or into the main module.
Some of the commonly used built-in modules in Python:-
6. What are the different built-in types that Python provides?
The principal built-in types that Python provides are:-
Some operations are supported by several object types. Practically all the objects can be compared, tested for truth value and can also be converted to a string.
The latter function is implicitly used when an object is written by the print() functions.
7. Explain! What is Flask & its benefits?
Flask is basically a Python framework, based on the framework libraries of Werkzeug, Jinja2 & inspired by Sinatra Ruby framework, available under the BSD license. It was designed to be simple and easy to use and extend.
The main idea behind was simply to build a solid and concrete foundation for web application of different complexity. From then on one is easy and free to plug in any extension he needs. They also have built-in development servers, support for secure cookies has blended support for unit testing & are Unicode based.
8. What is the lambda operator?
Lambda operator or lambda function is practiced for creating small, one-time & unknown function objects in Python. It actually can have a number of arguments but at the same time, it can only have one expression. It can not contain any statement & it reflects a function object which can be attached to any variable. Mostly lambda functions are transferred as parameters to a function that expects a function object as parameters like a map, reduce, filter functions.
9. What are some advantages of using Python over other programming languages?
Python comes with easy readability and a very simple syntax & it comes with the biggest advantage of being open sourced. It compromises of a huge standard library for most Internet platforms like Email, HTML & many others. It has a number of built-in data types, because of which it saves programming time & efforts from naming variables.
10. How can the ternary operators be used in Python?
Ternary operators are also known as conditional expressions, that evaluate something based on a position being true or false. It allows testing a condition in a single line replacing the multiline if else, thereby creating the code compact.