Python Interview Questions
Outline
This comprehensive guide has three sets of important Python questions and answers: Beginners, Intermediate and Advanced.
Read, learn, practice and prepare yourself with these sure-shot python interview questions to crack your next interview for a python developer job.
Read, learn, practice and prepare yourself with these sure-shot python interview questions to crack your next interview for a python developer job.
Read, learn, practice and prepare yourself with these sure-shot python interview questions to crack your next interview for a python developer job.
We have compiled the top python interview questions and answers for you to prepare for your next interview. We have divided the questions into three categories based on experience.
✔️ Python Interview Questions for Beginners
✔️ Intermediate Python Interview Questions
✔️ Advanced Python Interview Questions
We have selected the most asked python questions in any interview. Each of these questions represents some core insights on the Python programming language.
But first let’s discuss – Why python is one of the top programming languages? Why is there high demand for Python developers? What makes python development a competitive job?
Python development has become pretty competitive. In a 2021 survey, 41% of microservice developers said they would be using Java in 2021. It also states that JavaScript and Python are two popular programming languages used by microservice developers. We can see that python is instantly competitive in the microservices sector.
The popular cloud platform among python developers is AWS. Among the beginners and intermediate python developers, Heroko and PythonAnywhere are more popular.
In 2022, SQL and Java were the other two languages with more popularity than Python. Learn these two languages along python and increase your chances of getting hired.
Amazon Web Services (AWS) topped the list of cloud computing platforms used by Python developers in 2020 with a share of 53%. In fact, Python programmers with more experience tend to favour AWS and DigitalOcean, while programmers with less experience—up to two years of professional experience—tend to favour Heroku and PythonAnywhere.
SQL and Java were a couple of the highly sought-after skills for the information technology sector in 2022. With almost 10% of respondents considering Python to be one of the most in-demand IT skills in 2022, it came in fourth place.
According to a statista report of April 2019, there were more data science job postings and 76% of those job postings on linkedin required Python programming knowledge.
The above statistics prove that python is indeed one of the most sought-after programming languages.
Now, let’s learn top interview questions on Python. Let’s start.
Let us look the chart to get an idea of salaries according to location:
Python Interview Questions for Beginners
1. What is a class in Python?
Because they containerize data (variables) and behaviour (methods) that act on that data and should logically be grouped together, classes are great if you need to keep state. This results in more logically organised (cleaner) code and reusability.
A class is a particular object type. It is created by executing a class statement. Many Developers uses class objects as templates. They use it to create class instance objects that can embody both the data structure and program routines specific to a data type.
A class is a particular object type. It is created by executing a class statement. Many Developers uses class objects as templates. They use it to create class instance objects that can embody both the data structure and program routines specific to a data type.
2. How to create a string containing a single quote?
We can create a string with double quotes to include single quotes inside the string:
>>> str1 = “that is jerry’s ball”
>>> str1 = “that is jerry’s ball”
3. Is Python case sensitive?
Yes. Python is a case sensitive language
4. What is pickling and unpickling?
Pickling is the process of taking any Python object and turning it into a string representation and dumping it into a file using the dump function.
Unpickling is the process of obtaining the original Python objects from the stored string representation.
Unpickling is the process of obtaining the original Python objects from the stored string representation.
5. What are modules in Python? Which Python built-in modules are most frequently used?
Python code is stored in files called modules. Variables, classes, or functions may be used in this code. A .py file containing executable code is referred to as a Python module.
Developers like to use the following built-in modules:
Developers like to use the following built-in modules:
- -os
- -sys
-random
-data time
-JSON
6. How can we manage memory in Python?
The Python Memory Manager is responsible for managing memory in Python. The memory that the manager allots to Python is in the form of a private heap space. This private heap is where all Python objects are kept and is inaccessible to programmers. Python does, however, offer some fundamental API functions to work with the private heap space.
Python also includes a built-in garbage collector to reuse any unused memory for the private heap space.
Python also includes a built-in garbage collector to reuse any unused memory for the private heap space.
7. What are tuples and lists? What distinguishes the two in particular?
Both lists and tuples are sequence data types in Python that can hold a collection of objects. Different data types may be present in the objects stored in the two sequences. In Python, we can distinguish Tuples with parenthesis (‘ansh’, 5, 0.97) and the Lists as square brackets [‘sara’, 6, 0.19].
But what actually distinguishes the two? The main distinction between the two is that while tuples are immutable objects, lists are mutable objects. This means that while tuples remain constant and cannot be changed in any way, lists can be changed, added to, or sliced as needed.
But what actually distinguishes the two? The main distinction between the two is that while tuples are immutable objects, lists are mutable objects. This means that while tuples remain constant and cannot be changed in any way, lists can be changed, added to, or sliced as needed.
8. How is Python used in different cloud platforms like Azure, AWS & Google Cloud?
You can develop web applications, machine learning models that are trained using Python code, and models that are deployed using SDK or DevOps in Microsoft Azure. All of these platforms support Python. In Azure, you have the Azure Machine Learning studio where you can create, train, test, and deploy models. Similarly, in AWS, we have SageMaker for machine learning models.
Additionally, Python is now widely used in Google Cloud to build Cloud Run, AI notebooks, and deployment templates, among other things.
Additionally, Python is now widely used in Google Cloud to build Cloud Run, AI notebooks, and deployment templates, among other things.
9. How do local and global variables operate?
Variables that are referred to within a function are implicitly global in Python. If a variable receives a value while it is being used in the function, it is local unless you specifically declare it to be global.
10. What is an IDE? Name some of the best Python IDEs?
A software development programme is known as an IDE (Integrated Development Environment).
Some key features of a good IDE for a Python environment include the ability to save and reload your code files, run code directly from the environment, support for debugging, syntax highlighting, and automatic code formatting.
Developers like the following General IDEs that supports Python:
– Sublime Text
– Atom
– Eclipse + PyDev
Special editors and IDEs for Python:
– Spyder
– PyCharm
– Thonny
Some key features of a good IDE for a Python environment include the ability to save and reload your code files, run code directly from the environment, support for debugging, syntax highlighting, and automatic code formatting.
Developers like the following General IDEs that supports Python:
– Sublime Text
– Atom
– Eclipse + PyDev
Special editors and IDEs for Python:
– Spyder
– PyCharm
– Thonny
Intermediate Python Interview Questions
As a python developer, with experience you will be able to answer python interview questions for freshers with much ease. In this section we have collected some Python tricky interview questions for you. This section will help you with the exact kind of Intermediate Python Interview Questions that you may face in your job hunt.
11. How Can You Copy Objects in Python?
The function used to copy objects in Python are
copy.copy() for shallow copy
copy.deepcopy() for shallow copy
copy.copy() for shallow copy
copy.deepcopy() for shallow copy
12. What is a map function in Python?
Python’s
map() function takes two arguments: iterable and function. A function is passed to the map() function as an argument,
and that function is then applied to all of the iterable’s elements. An object list of results is returned.
Look at the following example:
Look at the following example:
13. How can we delete files in Python?
We have to import the OS Module. Then use the function os.remove() to delete a file in python.
consider the code below:
consider the code below:
14. Name some Python tools that help in finding bugs or performing static analysis?
There’s no developer who can write bug-free code. Every developer has used tools to find bugs. For this basic Python interview question, you must have the answer on the tip of your tongue as follows:
The extraordinary library of Python packages has many tools to find bugs and perform static analysis.
Pylint and Pyflakes perform fundamental checks that will enable us to find bugs sooner than later.
Python source code can be examined by static type checkers like Mypy, Pyre, and Pytype.
The extraordinary library of Python packages has many tools to find bugs and perform static analysis.
Pylint and Pyflakes perform fundamental checks that will enable us to find bugs sooner than later.
Python source code can be examined by static type checkers like Mypy, Pyre, and Pytype.
15. If your Python program is slow then list some ways to optimize and improve its performance?
Every Python developer faces such a situation. There are numerous methods for making Python code faster. The following general guidelines will help you get to acceptable performance levels:
- – Instead of trying to sprinkle micro-optimization techniques throughout your code, you can achieve much greater benefits by making your algorithms faster (or switching to a faster algorithm).
- – Pick the appropriate data structures.
– Abstractions frequently lead to indirections and add extra work for the interpreter. Your programme will run more slowly if the levels of indirection outweigh the amount of useful work completed. Excessive abstraction should be avoided, especially when it takes the form of tiny functions or methods.
16. What is type conversion in Python?
The transformation of one data type into another is referred to as type conversion.
int() converts the data type into float type
float() converts the data type into float type
ord() character to integer conversion
hex() converts integers data type into hexadecimal data type
oct() converts integer data type into octal
tuple() This is a function. It is used to convert to a tuple.
set() This function returns the type after converting to set.
list() This function is used to convert any data type to a list type.
dict() This function is used to convert a tuple of order (key, value) into a dictionary.
str() Used to convert integer into a string
complex(real,imag) This function is used for conversion of real numbers to complex(real,imag) numbers.
int() converts the data type into float type
float() converts the data type into float type
ord() character to integer conversion
hex() converts integers data type into hexadecimal data type
oct() converts integer data type into octal
tuple() This is a function. It is used to convert to a tuple.
set() This function returns the type after converting to set.
list() This function is used to convert any data type to a list type.
dict() This function is used to convert a tuple of order (key, value) into a dictionary.
str() Used to convert integer into a string
complex(real,imag) This function is used for conversion of real numbers to complex(real,imag) numbers.
17. What rules does the local and global variable follow in Python?
Variables in Python that are only used within a function are implicitly global. Anywhere in the body of the function where a variable is given a value, unless explicitly declared as global, it is assumed to be a local variable
Though initially a little surprising, a moment’s thought clarifies this. One benefit of making assigned variables global is that it prevents unintended side effects. On the other hand, you would use global constantly if it were a requirement for all global references. Every reference to a built-in function or to a part of an imported module would need to be declared as global. The value of the global declaration for identifying side effects would be negated by this clutter.
Though initially a little surprising, a moment’s thought clarifies this. One benefit of making assigned variables global is that it prevents unintended side effects. On the other hand, you would use global constantly if it were a requirement for all global references. Every reference to a built-in function or to a part of an imported module would need to be declared as global. The value of the global declaration for identifying side effects would be negated by this clutter.
18. Why are Iterator Objects important?
There are numerous uses of iterator objects. After we implement a general function and call it then it returns an iterator. Similarly, if an iterator class containing a generator method is called then returns an iterator. Some benefits are –
– It is a straightforward, practical, and effective programming pattern once mastered.
– It has numerous, wide-ranging uses.
– Lexically separating the producer code from the consumer code is helpful. This makes it simpler to identify issues and to localise and fix code without causing unintended side effects.
– We can define our own abstract sequences—sequences whose composition is determined by our computations rather than by their presence in a container—by implementing our own iterators (and generators). In fact, as each value is requested, our iterator can calculate or retrieve the requested value.
– It is a straightforward, practical, and effective programming pattern once mastered.
– It has numerous, wide-ranging uses.
– Lexically separating the producer code from the consumer code is helpful. This makes it simpler to identify issues and to localise and fix code without causing unintended side effects.
– We can define our own abstract sequences—sequences whose composition is determined by our computations rather than by their presence in a container—by implementing our own iterators (and generators). In fact, as each value is requested, our iterator can calculate or retrieve the requested value.
19. How do I generate random numbers in Python?
A random number generator is implemented by the standard module random. It’s simple to use:
This returns a random floating point number in the range [0, 1).
There are numerous additional specialised generators included in this module, including:
int() – – It is used to choose an integer between the range [a, b).
uniform(a, b) – – – It is used to choose a floating point number between the range [a, b)
normalvariate(mean, sdev)
Several higher-level operations directly affect sequences, including:
choice(S) – – It is used to select a random element from a sequence.
shuffle(L) – – shuffles a list while it is still in use, or permutes it.
You can also instantiate the Random class to create multiple independent random number generators.
There are numerous additional specialised generators included in this module, including:
int() – – It is used to choose an integer between the range [a, b).
uniform(a, b) – – – It is used to choose a floating point number between the range [a, b)
normalvariate(mean, sdev)
Several higher-level operations directly affect sequences, including:
choice(S) – – It is used to select a random element from a sequence.
shuffle(L) – – shuffles a list while it is still in use, or permutes it.
You can also instantiate the Random class to create multiple independent random number generators.
20. What is slicing in Python?
Slicing is a method for choosing a range of elements from sequence data types, such as list, string, and tuple. Slices make it simple and advantageous to separate the elements. It needs a : (colon) to demarcate the field’s start index and end index. Each type of data sequence We are able to use slicing to obtain the required elements from a list or tuple. Even though we can obtain elements by supplying an index, doing so yields only a single element; however, by using slicing, we can obtain a collection or suitable range of the required elements.
Syntax:
Syntax:
Python Interview Questions
This section contains some advanced interview questions on python. This section also explores a few Python coding Interview questions You may practice the common python programs which the interviewer often asks.
21. What is Polymorphism in Python?
The capacity of the code to take various forms is known as polymorphism. Consider the scenario where the parent class has a method called XYZ and the child class is able to have a method with the same name but different variables and parameters.
22. Define encapsulation in Python?
In Python, the term “encapsulation” refers to the act of combining various functions and variables into a single unit. The best illustration of encapsulation in Python is the class.
23. What is pandas?
Pandas is a free and open-source library for Python that supports data structures for operations on data that are related to data analysing and data manipulation. With its extensive feature set, Pandas can be used for any type of data operation, whether it’s for implementing various algorithms or resolving challenging business issues. Pandas assists in handling multiple files when carrying out specific operations on the data that files store.
24. Why use NumPy arrays instead of lists in Python?
Users benefit from three main advantages of NumPy arrays, as illustrated below:
– Because NumPy arrays use much less memory, the code is more effective.
– NumPy arrays run more quickly and don’t require a lot of runtime processing.
– Because of its highly readable syntax, NumPy is simple and practical for programmers.
– Because NumPy arrays use much less memory, the code is more effective.
– NumPy arrays run more quickly and don’t require a lot of runtime processing.
– Because of its highly readable syntax, NumPy is simple and practical for programmers.
25. State the differences between Django, Pyramid, and Flask.
- – Pyramid was made with larger apps in mind. It offers flexibility to developers and enables them to use the best tools for their projects. The developer has access to the database, URL architecture, templating style, and other options. Pyramid is easily adaptable.
- -A “microframework” called Flask is made for simple, compact applications. In a flask, external libraries are necessary.
-Pyramid and Django both lend themselves to more extensive applications. It contains an ORM.
26. What is the Lambda function? Why is it used?
An anonymous function is a lambda function. You can pass as many parameters as you like into this function, but only one statement.
An anonymous function is a lambda function. You can pass as many parameters as you like into this function, but only one statement.
– Lambda function assigning to a variable
– Lambda function wrapping in another function
An anonymous function is a lambda function. You can pass as many parameters as you like into this function, but only one statement.
– Lambda function assigning to a variable
– Lambda function wrapping in another function
27. Explain multithreading in Python.
Although Python has a multi-threading package built in, it is not generally recommended to use multi-threading to speed up code.
The construct known as the GIL, or Global Interpreter Lock, is included in the package. It makes sure that only one thread is ever active at once. A thread obtains the GIL, does its work with it, and then transfers it to the following thread.
Because of how quickly this occurs, users may believe that multiple threads are working simultaneously. This is obviously not the case since they are merely sharing the same CPU core. GIL passing increases the overall execution overhead.
As a result, using the threading package is not advised if your goal is to speed up the execution.
The construct known as the GIL, or Global Interpreter Lock, is included in the package. It makes sure that only one thread is ever active at once. A thread obtains the GIL, does its work with it, and then transfers it to the following thread.
Because of how quickly this occurs, users may believe that multiple threads are working simultaneously. This is obviously not the case since they are merely sharing the same CPU core. GIL passing increases the overall execution overhead.
As a result, using the threading package is not advised if your goal is to speed up the execution.
28. Write a sorting algorithm for a set of number in Python?
The following is the code to sort a list in Python:
The output of the above program is: 2,3,4,6,8
29. Write a program in Python to check if a number is prime?
The following is the Python program code to check a prime number and its output.
30. Write a Python program to find the factorial of a number.
The program and its output:
Conclusion
We hope these Python interview questions and answers will be of great assistance to you throughout the process, whether
you’re a developer getting ready for an interview or a hiring manager looking for the best applicant.
Remember that the hiring process involves more than just technical expertise. To ensure that you land a high paying Python developer job, both previous experience and soft skills are crucial.
A lot of the Python interview questions are open-ended, so keep that in mind. Interviewers are interested in your reasoning, not just the answer you memorised. Always be ready for follow-up questions regarding how you arrived at your answer. Describe your thought process.
Good luck with your upcoming Python interview! You can go through our python developers jobs here.
Remember that the hiring process involves more than just technical expertise. To ensure that you land a high paying Python developer job, both previous experience and soft skills are crucial.
A lot of the Python interview questions are open-ended, so keep that in mind. Interviewers are interested in your reasoning, not just the answer you memorised. Always be ready for follow-up questions regarding how you arrived at your answer. Describe your thought process.
Good luck with your upcoming Python interview! You can go through our python developers jobs here.
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