Top 50 Python Interview Questions and Answers for Freshers and Experts

Top 50 Python Interview Questions and Answers for Freshers and Experts

Python Interview Questions and Answers: Below listed are some of the tops and most frequently asked questions as well as answers during the Python Technical Interviews. The Python Developer Interview questions and answers 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 questions on python and answer listed below.

 

Python Interview Questions and Answers for Freshers and Experts:

 

Q1. What is Python?

Python is nothing but an advanced and smart computer programming language that has exceptions, objects, modules, threads, and automatic memory management. The language is quite simple and easy to use, transferrable, extensible, open-source, and build-in data structure.

Q2. What is the shortest and the easiest way to read a file? 

2 memory- effective way which is ranked in order where the first one is the best.

It is exclusively supported from 2.5 Python and above it.

2. If you eventually would like to have control over how much is to be read, you can make use of yield.
3. Use of WITH

This can be the best as well as the most effective pythonic way to read huge files.

Advantages:

Let us check out a few of these advantages

• The object of the file is automatically closed once the exciting form is closed along with the execution block.
• Handling the exception inside the with block
• The memory of the loop iterates along, through the file f with an object line by line. It internally buffers the optimization on costly IO operations as well as with the memory management with an open (“x.txt”) as f for the line in f as something to do with data.
• The statement handles and takes care of the opening as well as the closing of the file, along with the exception which is raised with the inner block.

Q3. What is the reason behind using yield in Python?

There are situations where sometimes people wish to have more thorough and fine access control over how much is to be read over in each iteration. To get better control in these cases it’s always the best idea to use iter and yield.

Q4. What is the use of the <__init__.py> module in Python?

The use of the <__init__.py> module can help in several ways for fulfilling the following objectives.

• It allows Python to interpret the directories with the package containments by not including the things which contain names in common like a string.
• Apart from all this, it additionally allows all the programming experts to take control and decide whether which directory is a package and which one is not.
• Likewise, the <__init__.py> can be an empty file as well which can further help in code initialization and execution for setting the variable of <__all__> as well as for a package.

Q5. Which are the various methods that Python provides for copying an object?
Either we can use the Shallow Copy method or the Deep Copy method to approach copying an object.

Shallow Copy method.

In this method, the content of the object like a dictionary does not get copied by the values but it does by creating the new reference.

SHALLOW COPY METHOD.

>>> a = {1: [1,2,3]}

>>> b = a.copy()

>>> a, b

({1: [1, 2, 3]}, {1: [1, 2, 3]})

>>> a[1].append(4)

>>> a, b

({1: [1, 2, 3, 4]}, {1: [1, 2, 3, 4]})

1

2

3

4

5

6

7

>>> a = {1: [1,2,3]}

>>> b = a.copy()

>>> a, b

({1: [1, 2, 3]}, {1: [1, 2, 3]})

>>> a[1].append(4)

>>> a, b

({1: [1, 2, 3, 4]}, {1: [1, 2, 3, 4]})

DEEP COPY METHOD.

It copies all the contents by value.

>>> c = copy.deepcopy(a)

>>> a, c

({1: [1, 2, 3, 4]}, {1: [1, 2, 3, 4]})

>>> a[1].append(5)

>>> a, c

({1: [1, 2, 3, 4, 5]}, {1: [1, 2, 3, 4]})

1

2

3

4

5

6

>>> c = copy.deepcopy(a)

>>> a, c

({1: [1, 2, 3, 4]}, {1: [1, 2, 3, 4]})

>>> a[1].append(5)

>>> a, c

({1: [1, 2, 3, 4, 5]}, {1: [1, 2, 3, 4]})

Q6. How can one set a global variable inside a function?

One can easily use the global variable for various functions by presenting it as global in every function which gets assigned to it:

globvar = 0

def set_globvar_to_one():

global globvar # Needed to modify global

copy of globvar

globvar = 1

def print_globvar():

print globvar # No need for global

declaration to read the value of globvar

set_globvar_to_one()

print_globvar() # Prints 1

1

2

3

4

5

6

7

8

I can only imagine all the reasons behind it that, as the global variables happen to be so dangerous, Python tries and makes sure that you should know about what you actually playing with explicitly needs the global keyword.

Q7. For what is forelse used in Python language?
The language Python is very interesting which easily allows you to specify an else suite:

Here is a clear example of this type.

for I in foo:

if bar(i):

break

else:

baz()

the else suite is executed after the for, but only if the for terminates normally (not by a break).

Here’s some code is written without for…else:

def contains_even_number(l):

“Prints whether or not the list l contains an even number.”

has_even_number = False

for elt in l:

if elt % 2 == 0:

has_even_number = True

break

if has_even_number:

print “list contains an even number”

else:

print “list does not contain an even number”

The same code snippet listed below shows how to use of for…else. This allows you to remove the extraneous flag variable which is in the loop:

def contains_even_number(l):

“Prints whether or not the list l contains an even number.”

for elt in l:

if elt % 2 == 0:

print “list contains an even number”

break

else:

print “list does not contain an even number”

Decide wisely while judging whether to use for…else construct or not. It is not really unequivocally better but yes, when there is an asymmetry between any two possibilities, you can easily make your code more readable to use it for…else to follow the happy path logic at the top avoiding the errors at the bottom. Learn at 3RI Technologies.

Q8 How to make an Iterator in Python?

The objects in Python Iterator conform to the protocol of the iterator, which primarily offers 2 kinds of methods:

__iter__() and next().

The __iter__ returns the iterator object and is implicitly called at the start of loops.

The next() method returns the next value and is implicitly called at each loop increment.

next() raises a StopIteration exception when there is no more value to return, which is implicitly captured by looping constructs to stop iterating.

Here’s a simple example of a counter:

class Counter:

def __init__(self, low, high):

self.current = low

self.high = high

def __iter__(self):

return self

def next(self): # Python 3: def

__next__(self)

if self.current > self.high:

raise StopIteration

else:

self.current += 1

return self.current – 1

for c in Counter(3, 8):

print c

This will print:

3

4

5

6

7

8

Q 9: What is the difference between lists and tuples?

Lists are mutable, and it means these can be edited while tuples are immutable, it means these can be edited.

Lists are considered slower than tuples.

Syntax that is used in List is list_1 = [10, ‘Chelsea’], 20 while for tuples, syntax is tup_1 = (10, ‘Chelsea’, 20)

Q 10: What is meant by pep 8?

The term stands for Python Enhancement Proposal. Pep 8 is a set of rules that are used to specify the formatting of python code to get the maximum readability.

Q 11: How can it possible to manage memory in Python?

It is possible to manage memory management in Python with Python Private Heap Space. The fact, all the data structures, and python objects are located in a private heap. The programmer is not supposed to access this private heap.

The inbuilt garbage collector is also found in Python that recycles all the unused memory thereby, and it can be used for heap space. Moreover, in python objects, the allocation of heap space is done through Python’sPython’s memory manager. Learn more at Python Web Development Course

 

Q 12: What do you mean by namespace in Python?

It is a naming system used to be sure that names are unique to avoid naming conflicts.

 

Q 13: How can you explain the term Pythonpath?

Python path is an environmental variable that is used in the case of the importing of a module. A module is introduced; the python path is used to check out the presence of the imported in all directories. With an interpreter, it is possible to decide which module is needed to load.

 

Q 14: Differentiate the terms pickling and unpickling in Python?

With the pickling module, it is possible to accept any module of python object to convert it into a string representation. After that, that object dumps into a file with a dump function that is known as pickling.

Moreover, the process where retrieving original Python objects is possible from the stored string representation is known as unpickling.

 

Q 15: What do you mean by python modules? Which are built-in modules commonly used in Python?

Python modules mean those files where python codes are available. Moreover, this code may be like function classes or variables. Kindly note that a python module is considered as a .py file that has executable code.

Commonly used built-in modules in Python are:

• os
• random
• data time
• os
• sys
• math
• JSON

Q 16: In Python, what is the usage of local variables and global variables?

Global Variables: When variables are considered either outside a function or in global space, it is known as global variables. The fact, it is possible to access these variables from any function in the program.

Local Variables: When variables are considered inside a function, it is known as local variables. The fact, this variable is presented in the local space rather than in the global space.

Q 17: Names the tools used to perform static analysis or finding bugs?

To find out errors or bugs in python source code, PyChecker is used that is a static analysis tool. It is also used to warn about the complexity and style of the virus.

Even Pylint is another tool that is verified to check whether the module fulfils the coding standard or not.

 

Q 18: Explain about lambda in Python

Lambda in Python is a single expression anonymous function that is frequently used as an inline function.

 

Q 19: In Python, why lambda forms do not have statements?

Yes! Lambda forms do not have statements in Python as it is used in case of a new function object and also get returned at runtime.

 

 

Q 20: What do you mean by Python decorators?

These are specific amendments that need to make in python syntax to alter functions flawlessly.

 

Q 21: Explain the term self in Python?

A python is an object of a class, explicitly considered as the first parameter. But this is not possible in the case of Java. This command assists in differentiating between attributes and methods of a class along with local variables.

 

Q 22: What is the working of a break, pass, and continue?

• Breaks: It permits loop termination at the time some condition is fulfilled, and the control is sent to the next statement.

• Pass: It is used when the users require some block of code syntactically; however, the users seek to skip the execution. Generally, it is a null operation. During its performance, nothing happens.
• Continue: It permits skipping some phase of a loop after fulfilment of a particular condition and also when control is sent to the beginning of the loop.

Q 23: Name some type of conversion in Python

The term type of conversion used in Python means the conversion of one data type to another data type. For example:

• int()– It is used to convert any data type into integer type
• hex() – When there is a need to convert integers into hexadecimal, then this command is used.
• Complex (real, image) –It is used to convert real numbers into a complex number.
• ListList () – It is needed when there is a need for conversion of any data type to a list type.
• dict() – It is used for the conversion of a tuple of order into a dictionary.
• float()– It is used when there is a need to convert any data type into float typeset() – It is used to convert nature into the set.
• ord()– It easily converts characters into integer
• oct()– – It is used to convert an integer into octal
• str() – It means the task of converting an integer into a string.

Q 24: Tell about Dict and List comprehensions

These are syntax constructions used to make the creation of a dictionary or list process easier that is based on existing iterable.

 

Q 25: Does there any need for indentation in Python?

Yup! Indents the station is required in Python to specify a block of code. The codes, like functions, classes, loops, etc. are defined in an indented block. It is possible to perform with four space characters.

Kindly note that when a code is not indented correctly, then it will not execute accurately and will offer errors or bugs as well.

 

Q 26: In Python, what is the use of the split function?

It is used to break a string into shorter strings with the help of the defined separator. It also sends a list of all words that are presented in the string.

 

Q 27: What is meant to pass in Python?

The term pass means no no-operation Python statement. In simple words, it is a placeholder that is available in a compound statement, where there must be a new left, and also nothing has been mentioned there.

 

Q 28: What are iterators in Python?

These are used to iterate some groups of elements or containers, such as a list.

 

Q 29: How can you differentiate pyramid, Django, and flask?

Pyramids are built to use for more extensive applications as it offers flexibility along with letting the developers use accurate tools for completing their projects. It provides developers to choose from templates, URL structure, databases, and much more. Kindly note that the pyramid is a more massive configuration. Moreover, like the pyramid, Django is also successful or suggested in the case of heavy applications. It also comprises an ORM.

Flask is a “microframework” primarily build for a small application with more straightforward requirements. In a flask, you don’t have to use external libraries. Flask is ready to use.

However, the flask is a micro-framework that is suggested for small applications that have more straightforward requirements. Moreover, the flask doesn’t use any external libraries. It is always ready to use.

 

Q 30: What do you know about the unit test in Python?

United means a unit testing framework in Python. It supports the sharing of automation testing, aggregation of tests, setups, etc.

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Q 31: Explain the term__init__ in Python?

It is a constructor or method in Python. This method is come into consideration automatically to allocate memory when a new instance of a class is established. The fact, all classes have the _init_ method.

Q 32: Do you tell about docstring in Python?

Docstring means a python documentation string. It is a method of documenting Python functions, classes, and modules.

 

Q 33: What do you mean about the negative index in Python?

Python sequences are indexed in negative and positive numbers. For the negative index, -1 is used as the last index, and -2 is the second last index, and so on. While in the case of a positive index, 0 is the first index, and 1 is the second index, and so on.

 

Q 34: Define flask and its advantages?

It is a web microframework based on Jinga 2, Werkzeuo, and good intentions BSC licensed in the flask. The fact Jinga 2 and Werkzeuo are considered as the two dependencies.

The fact, the flask is a part of a micro-framework means it is not dependent upon external libraries. It also makes a framework light as there are no dependencies to update along with a very little chance of security bugs.

 

Q 35: Name the standard way used for the Flask script to work?

To work the flash script, the user should either import the path of their application or give the path to a python file.

 

Q 36: How does it feasible to capitalize on the first letter of a string in Python?

With the help of capitalizing (), it is feasible to obtain the first letter of a string in Python. In a case, a string already has a capital letter at the beginning, in that case, it returns the original string.

 

Q 37: How can you differentiate the terms range and xrange?

In the case of functionality, range and xrange are used in the same manner. Both ensure a list of a way to send a list of integers. The primary difference between both the terms is xrange returns an xrange object while range returns a python list object.

It means, in the case of xrange, it is not possible to generate a static list during the run time like range does. It can create a value that is needed with the help of a particular technique known as yielding. Furthermore, this technique is used with the help of an object called generators. It means that with an extensive range, users like to generate a list for, say two billion; in that case, xrange is used.

Q 38: How it possible to delete a file in Python with ease?

With a command known as os.unlink (filename) and os.remove (filename), it is easily possible to delete a file in Python.

 

 Q 39: Define the term flask-WTF and its features?

The fact, flask-WTF is a simple integration having WTF forms. It has features such as;

• Global csrf protection
• Internationalization integration
• Recaptcha supporting
• Integration with webforms
• Secure form with csrf token

 

Q 40: Explain the term generators in the Python programming language?

Those functions that are returned in an iterated set of items are known as generators.

Q 41: What is the function of database connection in a python flask?

It is used to support RDBS that is a database-powered application. This system needs to create a schema that is required to pipe the hema.sql file in a sqlite3 command. Thus, the users need to install the sqlite3 command to initiate or establish the database in the flask. Moreover, flask permits to request database in three methods;

• teardown_request(): This method is used in that case where the exception is raised along with no response is getting. It is used to modify the request and its values.
• before_request(): It is used in case of before an application along with passing no arguments
• after_request(): It is used in case of after an application along with moving the response that needs to send to the customers.

Q 42: Does Python a case-sensitive programming language?

Yup! Python is considered a case-sensitive programming language.

 

Q 43: Explain the use of dir() and help() function in Python?

Both these functions are Python interpreters, and these are used to view a consolidated dump in terms of built-in features.

 

• Help() function: It is used to exhibit the documentation string and permits the users to see the assistance related to keywords, attributes, and modules.
• Dir() function: It is used in the case of displaying the defined symbols.

Q 44: Tell us how Memcached should not be entertained in a python project?

The fundamental misuse of Memcached is to use it to store data rather than storing it as a cache. Kindly note that never entertains Memcached as the only source of information that is needed to execute your application. Data must also be available via another source.

Moreover, Memcached never offers any security, either in authentication and encryption. Also, Memcached is a key that can’t be performed query, and it also does not allow the contents to fetch out information.

Q 45: Do you know about a dictionary in Python?

Dictionary means built-in data types available in Python. It also specifies about one to one relationship between values and keys. Moreover, it comprises a pair of keys and even their corresponding values.

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Q 46: What is the use of *args, **kwargs?

The term *args is used when we are not sure about how many arguments are needed or going through via function. Even, it specifies the passing of tuple of arguments or passing of stored ListList to a task.

The term *kwargs is used when we are not sure about how many keyword arguments are needed or going through via function. Even, it explains the passing of values of a dictionary-like as keyword arguments.

Q 47: Explain the python package?

These are namespaces having different or multiple modules.

Q 48: In Python, do we use OOps concepts?

The fact, Python is an object-oriented programming language where programs can solve by establishing an object model. But, Python is treated as a structural and procedural language.

Q 49: What is meant by the Dogpile effect? Does it prevent using Python?

Dogpile effect means an event where cache expires and sites are interrupted by the different requests made by the various clients at the same time. With the help of a semaphore lock, this effect can prevent. The fact, in the dogpile effect, when a value gets expired, the initial process obtains the lock and starts producing a new value. 

Q 50: How can you convert a string to all lowercase in the Python programming language?

The lower () function is used when there is a need for converting a string to all lowercase in the python programming language.

Now your process of attempting and cracking Python interview becomes more comfortable with the above written 50 Python developer interview questions and answers. When you read these interview questions on python and answers, you will be able to crack your Python interview in the first attempt. Thus, we recommend you read these Python interview questions thoroughly before going for an interview. And if you need to learn this language comprehensively before the interview, again, 3ritechnologies are entirely helpful. Thus, before going for an interview, be sure to make a wise decision.

Some Python Developer Interview Questions Are :

Prepare yourself for these questions also.

1. What do you know about Python?

2. What do you like about Python?

3. What are some of the challenges you have faced with Python?

4. How have you used Python to solve specific problems?

5. Have you ever created a library or application in Python? If so, could you tell us about it?

6. Do you have any experience with databases (e.g., MySQL, MongoDB, etc.) and how has Python helped you interact with them?

7. Have you ever worked with Unix-like systems (e.g., Linux, FreeBSD)? If so, could you tell us how your experience has been using Python on those systems?

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