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Interview Questions - Python
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This Interview Questions- Python course is designed by Uplatz to get you acquainted with the nature of questions you may encounter during your interview for the subject of Python Programming Language. As per experience good interviewers hardly plan to ask any particular question during your interview, normally questions start with some basic concept of the subject and later they continue based on further discussion and what you answer. Uplatz is devoted to help Python learners become successful in their Python careers. That’s why Uplatz created an interesting and helpful course of Interview Questions- Python. In this course, you will get Interview Questions - Python and Answer which cover a wide basic level topics associated with Python such as pickling and unpickling, slicing, basic types of functions available in Python, ways to convert a string to a number in Python, whitespaces in Python and advanced level topics like iterators, generators, decorators, rstrip() function in Python. Go through these Interview Questions - Python sets and land your dream job as a Python Developer and other top profiles. Practice these interview questions on Python with answers provided by experts and be fully prepared for your next Python interview. Our team which includes experienced Python Programmer have made a careful selection of the questions to keep a balance between theory and practical knowledge. So, you can get the full advantages. The Interview Questions- Python can be helpful and suitable for Python freshers as well as for experienced Python professionals at any level of the career. Some of the question answers here can also be beneficial for networking related professionals. While even if you are a Python beginner or a Python expert, we are pretty much sure you would understand every Interview Questions- Python.
Course/Topic - Interview Questions - Python - all lectures
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In this Python - Interview Questions tutorial, you will get to know about the different questions being asked by the interviewers in an interview and their answers regarding Python learning like what are the key features of python, what is pep 8.
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In this Python - Interview Questions tutorial, you will get to know about the different questions being asked by the interviewers in an interview and their answers regarding Python learning like is indentation required in python, difference between python arrays and lists.
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In this Python - Interview Questions tutorial, you will get to know about the different questions being asked by the interviewers in an interview and their answers regarding Python learning like how does the break and continue keyword work.
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In this Python - Interview Questions tutorial, you will get to know about the different questions being asked by the interviewers in an interview and their answers regarding Python learning like linear search in python.
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In this Python - Interview Questions tutorial, you will get to know about the different questions being asked by the interviewers in an interview and their answers regarding Python learning like what is the purpose of is, not and in operators in python.
• Learn how to answer most frequently asked questions in Python interviews for the year 2021.
• If you are appearing for a technical round of interview for Python, here are the top interview questions with answers to help you prepare.
• These questions cover all the basic applications of Python and will showcase your expertise in the subject.
• Learn the skills to tackle any interview question.
• Our Python interview questions for experienced and freshers will help you in your interview preparation.
The Python Certification ensures you know planning, production and measurement techniques needed to stand out from the competition.
Python is a computer programming language often used to build websites and software, automate tasks, and conduct data analysis. Python is a general-purpose language, meaning it can be used to create a variety of different programs and isn't specialized for any specific problems.
Python is an interpreted, interactive, object-oriented programming language. It incorporates modules, exceptions, dynamic typing, very high level dynamic data types, and classes. It supports multiple programming paradigms beyond object-oriented programming, such as procedural and functional programming.
There are several levels of Python certification that one can attain, from entry-level Python programmer (PCEP), to Certified Associate in Python Programming (PCAP), to Certified Professional in Python Programming (PCPP). Learning Python and getting a Python certificate can open incredible opportunities.
PCAP – Certified Associate in Python Programming certification is a professional credential that measures your ability to accomplish coding tasks related to the basics of programming in the Python language and the fundamental notions and techniques used in object-oriented programming.
Uplatz online training guarantees the participants to successfully go through the Python Certification provided by Uplatz. Uplatz provides appropriate teaching and expertise training to equip the participants for implementing the learnt concepts in an organization.
Course Completion Certificate will be awarded by Uplatz upon successful completion of the Python online course.
The Python draws an average salary of $120,000 per year depending on their knowledge and hands-on experience.
Being a Python developer is a good career choice, mainly due to the increasing demand for Python developers in many industries. Many high profile companies such as Google and Facebook use Python, and it also has a high paying salary with an average of $120,000 USD per year.
The highest number of Python programming jobs is for software engineer roles. People with this job title very often specialize in another programming language aside from Python – Java and Javascript are among the popular options. The second type of role with the most Python coding jobs is data scientist.
Python Job Profiles
● Software Engineer.
● Python Developer.
● Research Analyst.
● Data Analyst.
● Data Scientist.
● Software Developer.
1. What is Python? What are the benefits of using Python
Python is a high-level, interpreted, general-purpose programming language. Being a general-purpose language, it can be used to build almost any type of application with the right tools/libraries. Additionally, python supports objects, modules, threads, exception-handling, and automatic memory management which help in modelling real-world problems and building applications to solve these problems.
Benefits of using Python:
· Python is a general-purpose programming language that has a simple, easy-to-learn syntax that emphasizes readability and therefore reduces the cost of program maintenance. Moreover, the language is capable of scripting, is completely open-source, and supports third-party packages encouraging modularity and code reuse.
· Its high-level data structures, combined with dynamic typing and dynamic binding, attract a huge community of developers for Rapid Application Development and deployment.
2. What is a dynamically typed language?
Before we understand a dynamically typed language, we should learn about what typing is. Typing refers to type-checking in programming languages. In a strongly-typed language, such as Python, "1" + 2 will result in a type error since these languages don't allow for "type-coercion" (implicit conversion of data types). On the other hand, a weakly-typed language, such as Javascript, will simply output "12" as result.
Type-checking can be done at two stages -
· Static - Data Types are checked before execution.
· Dynamic - Data Types are checked during execution.
Python is an interpreted language, executes each statement line by line and thus type-checking is done on the fly, during execution. Hence, Python is a Dynamically Typed Language.
3. What is an Interpreted language?
An Interpreted language executes its statements line by line. Languages such as Python, Javascript, R, PHP, and Ruby are prime examples of Interpreted languages. Programs written in an interpreted language runs directly from the source code, with no intermediary compilation step.
4. What is PEP 8 and why is it important?
PEP stands for Python Enhancement Proposal. A PEP is an official design document providing information to the Python community, or describing a new feature for Python or its processes. PEP 8 is especially important since it documents the style guidelines for Python Code. Apparently contributing to the Python open-source community requires you to follow these style guidelines sincerely and strictly.
5. What is Scope in Python?
Every object in Python functions within a scope. A scope is a block of code where an object in Python remains relevant. Namespaces uniquely identify all the objects inside a program. However, these namespaces also have a scope defined for them where you could use their objects without any prefix. A few examples of scope created during code execution in Python are as follows:
· A local scope refers to the local objects available in the current function.
· A global scope refers to the objects available throughout the code execution since their inception.
· A module-level scope refers to the global objects of the current module accessible in the program.
· An outermost scope refers to all the built-in names callable in the program. The objects in this scope are searched last to find the name referenced.
6. What are lists and tuples? What is the key difference between the two?
Lists and Tuples are both sequence data types that can store a collection of objects in Python. The objects stored in both sequences can have different data types. Lists are represented with square brackets ['sara', 6, 0.19], while tuples are represented with parantheses ('ansh', 5, 0.97).
But what is the real difference between the two? The key difference between the two is that while lists are mutable, tuples on the other hand are immutable objects. This means that lists can be modified, appended or sliced on the go but tuples remain constant and cannot be modified in any manner. You can run the following example on Python IDLE to confirm the difference:
my_tuple = ('sara', 6, 5, 0.97)
my_list = ['sara', 6, 5, 0.97]
print(my_tuple[0]) # output => 'sara'
print(my_list[0]) # output => 'sara'
my_tuple[0] = 'ansh' # modifying tuple => throws an error
my_list[0] = 'ansh' # modifying list => list modified
print(my_tuple[0]) # output => 'sara'
print(my_list[0]) # output => 'ansh'
7. What are the common built-in data types in Python?
There are several built-in data types in Python. Although, Python doesn't require data types to be defined explicitly during variable declarations type errors are likely to occur if the knowledge of data types and their compatibility with each other are neglected. Python provides type() and isinstance() functions to check the type of these variables. These data types can be grouped into the following categories-
· None Type:
None keyword represents the null values in Python. Boolean equality operation can be performed using these NoneType objects.
|
Class Name |
Description |
|
NoneType |
Represents the NULL values in Python. |
· Numeric Types:
There are three distinct numeric types - integers, floating-point numbers, and complex numbers. Additionally, booleans are a sub-type of integers.
|
Class Name |
Description |
|
int |
Stores integer literals including hex, octal and binary numbers as integers |
|
float |
Stores literals containing decimal values and/or exponent signs as floating-point numbers |
|
complex |
Stores complex numbers in the form (A + Bj) and has attributes: real and imag |
|
bool |
Stores boolean value (True or False). |
· Sequence Types:
According to Python Docs, there are three basic Sequence Types - lists, tuples, and range objects. Sequence types have the in and not in operators defined for their traversing their elements. These operators share the same priority as the comparison operations.
|
Class Name |
Description |
|
list |
Mutable sequence used to store collection of items. |
|
tuple |
Immutable sequence used to store collection of items. |
|
range |
Represents an immutable sequence of numbers generated during execution. |
|
str |
Immutable sequence of Unicode code points to store textual data. |
1. Binary data such as bytearray bytes memoryview , and
2. Text strings such as str.
· Mapping Types:
A mapping object can map hashable values to random objects in Python. Mappings objects are mutable and there is currently only one standard mapping type, the dictionary.
|
Class Name |
Description |
|
dict |
Stores comma-separated list of key: value pairs |
· Set Types:
Currently, Python has two built-in set types - set and frozenset. set type is mutable and supports methods like add() and remove(). frozenset type is immutable and can't be modified after creation.
|
Class Name |
Description |
|
set |
Mutable unordered collection of distinct hashable objects. |
|
frozenset |
Immutable collection of distinct hashable objects. |
· Modules:
Module is an additional built-in type supported by the Python Interpreter. It supports one special operation, i.e., attribute access: mymod.myobj, where mymod is a module and myobj references a name defined in m's symbol table. The module's symbol table resides in a very special attribute of the module __dict__, but direct assignment to this module is neither possible nor recommended.
· Callable Types:
Callable types are the types to which function call can be applied. They can be user-defined functions, instance methods, generator functions, and some other built-in functions, methods and classes.
8. What is pass in Python?
The pass keyword represents a null operation in Python. It is generally used for the purpose of filling up empty blocks of code which may execute during runtime but has yet to be written. Without the pass statement in the following code, we may run into some errors during code execution.
def myEmptyFunc():
# do nothing
pass
myEmptyFunc() # nothing happens
## Without the pass keyword
# File "", line 3
# IndentationError: expected an indented block
9. What are modules and packages in Python?
Python packages and Python modules are two mechanisms that allow for modular programming in Python. Modularizing has several advantages -
· Simplicity: Working on a single module helps you focus on a relatively small portion of the problem at hand. This makes development easier and less error-prone.
· Maintainability: Modules are designed to enforce logical boundaries between different problem domains. If they are written in a manner that reduces interdependency, it is less likely that modifications in a module might impact other parts of the program.
· Reusability: Functions defined in a module can be easily reused by other parts of the application.
· Scoping: Modules typically define a separate namespace, which helps avoid confusion between identifiers from other parts of the program.
Modules, in general, are simply Python files with a .py extension and can have a set of functions, classes, or variables defined and implemented. They can be imported and initialized once using the import statement. If partial functionality is needed, import the requisite classes or functions using from foo import bar.
Packages allow for hierarchial structuring of the module namespace using dot notation. As, modules help avoid clashes between global variable names, in a similar manner, packages help avoid clashes between module names.
Creating a package is easy since it makes use of the system's inherent file structure. So just stuff the modules into a folder and there you have it, the folder name as the package name. Importing a module or its contents from this package requires the package name as prefix to the module name joined by a dot.
10. What are global, protected and private attributes in Python?
· Global variables are public variables that are defined in the global scope. To use the variable in the global scope inside a function, we use the global keyword.
· Protected attributes are attributes defined with an underscore prefixed to their identifier eg. _sara. They can still be accessed and modified from outside the class they are defined in but a responsible developer should refrain from doing so.
· Private attributes are attributes with double underscore prefixed to their identifier eg. __ansh. They cannot be accessed or modified from the outside directly and will result in an AttributeError if such an attempt is made.