Top 50 commonly asked Django Interview Questions and Answers

Top 50 commonly asked Django Interview Questions and Answers

Django along with Python is one of the most in-demand skills and surely amongst some of the trickiest ones. So if you want to prepare yourself to perform the best in the upcoming Django interview, here are the top 50 commonly asked Django Interview Questions and Answers.

Django along with Python is one of the most in-demand skills and surely amongst some of the trickiest ones. So if you want to prepare yourself to perform the best in the upcoming Django interview, here are the top 50 commonly asked Django Interview Questions and Answers.

Q1. What is the difference between Flask and Django?

Q2. What is Django?

Django is a web development framework that was developed in a fast-paced newsroom. It is a free and open-source framework that was named after Django Reinhardt who was a jazz guitarist from the 1930s. Django is maintained by a non-profit organization called the Django Software Foundation. The main goal of Django is to enable Web Development quickly and with ease.

Q3. Name some companies that make use of Django?

Some of the companies that make use of Django are Instagram, DISCUS, Mozilla Firefox, YouTube, Pinterest, Reddit, etc.

Q4. What are the features of Django?
  • SEO Optimized
  • Extremely fast
  • Fully loaded framework that comes along with authentications, content administrations, RSS feeds, etc
  • Very secure thereby helping developers avoid common security mistakes such as cross-site request forgery (csrf), clickjacking, cross-site scripting, etc
  • It is exceptionally scalable which in turn helps meet the heaviest traffic demands
  • Immensely versatile which allows you to develop any kind of websites
Q5. How do you check for the version of Django installed on your system?

To check for the version of Django installed on your system, you can open the command prompt and enter the following command:

  • python -m django –version

You can also try to import Django and use the get_version() method as follows:

import django 
print(django.get_version())
Q6. What are the advantages of using Django?
  • Django's stack is loosely coupled with tight cohesion
  • The Django apps make use of very less code
  • Allows quick development of websites
  • Follows the DRY or the Don't Repeat Yourself Principle which means, one concept or a piece of data should live in just one place
  • Consistent at low as well as high levels
  • Behaviors are not implicitly assumed, they are rather explicitly specified
  • SQL statements are not executed too many times and are optimized internally
  • Can easily drop into raw SQL whenever required
  • Flexibility while using URL's
Q7. Explain Django architecture.

Django follows the MVT or Model View Template architecture which is based on the MVC or Model View Controller architecture. The main difference between these two is that Django itself takes care of the controller part.

According to Django, the 'view' basically describes the data presented to the user. It does not deal with how the data looks but rather what the data actually is. Views are basically callback functions for the specified URL's and these callback functions describe which data is presented.

The 'templates' on the other hand deal with the presentation of data, thereby, separating the content from its presentation. In Django, views delegate to the templates to present the data.

The 'controller' here is Django itself which sends the request to the appropriate view in accordance with the specified URL. This is why Django is referred to as MTV rather than MVC architecture.

Q8. Give a brief about 'django-admin'.

django-admin is the command-line utility of Django for administrative tasks. Using the django-admin you can perform a number of tasks some of which are listed out in the following table:

Q9. How do you connect your Django project to the database?

Django comes with a default database which is SQLite. To connect your project to this database, use the following commands:

  1. python manage.py migrate (migrate command looks at the INSTALLED_APPS settings and creates database tables accordingly)
  2. python manage.py makemigrations (tells Django you have created/ changed your models)
  3. python manage.py sqlmigrate (sqlmigrate takes the migration names and returns their SQL)
Q10. What are the various files that are created when you create a Django Project? Explain briefly.

When you create a project using the startproject command, the following files will be created:

Q11. What are 'Models'?

Models are a single and definitive source for information about your data. It consists of all the essential fields and behaviors of the data you have stored. Often, each model will map to a single specific database table.

In Django, models serve as the abstraction layer that is used for structuring and manipulating your data. Django models are a subclass of the django.db.models.Model class and the attributes in the models represent database fields.

Q12. What are 'views'?

Django views serve the purpose of encapsulation. They encapsulate the logic liable for processing a user's request and for returning the response back to the user. Views in Django either return an HttpResponse or raise an exception such as Http404. HttpResponse contains the objects that consist of the content that is to be rendered to the user. Views can also be used to perform tasks such as read records from the database, delegate to the templates, generate a PDF file, etc.

Q13. What are 'templates'?

Django's template layer renders the information to be presented to the user in a designer-friendly format. Using templates, you can generate HTML dynamically. The HTML consists of both static as well as dynamic parts of the content. You can have any number of templates depending on the requirement of your project. It is also fine to have none of them.

Django has its own template system called the Django template language (DTL). Regardless of the backend, you can also load and render templates using Django's standard admin.

Q14. What is the difference between a Project and an App?

An app is basically a Web Application that is created to do something for example, a database of employee records. A project, on the other hand, is a collection of apps of some particular website. Therefore, a single project can consist of 'n' number of apps and a single app can be in multiple projects.

Q15. What are the different inheritance styles in Django?

Django has three possible inheritance styles:

Abstract base classes Used when you want to use the parent class to hold information that you don’t want to type for each child model. Here, the parent class is never used in solitude

Multi-table inheritance Used when you have to subclass an existing model and want each model to have its own database table

Proxy models Used if you only want to modify the Python-level behavior of a model, without changing the ‘models’ fields in any way

Q16. What are static files?

Static files in Django are those files that serve the purpose of additional files such as the CSS, images or JavaScript files. These files are managed by django.contrib.staticfiles. These files are created within the project app directory by creating a subdirectory named as static.

Q17. What are 'signals'?

Django consists of a signal dispatcher that helps allow decoupled applications to get notified when actions occur elsewhere in the framework. Django provides a set of built-in signals that basically allow senders to notify a set of receivers when some action is executed. Some of the signals are as follows:

Q18. Briefly explain Django Field Class.

'Field' is basically an abstract class that actually represents a column in the database table. The Field class, is in turn, a subclass of RegisterLookupMixin. In Django, these fields are used to create database tables (db_type()) which are used to map Python types to the database using get_prep_value() and vice versa using from_db_value() method_._ Therefore, fields are fundamental pieces in different Django APIs such as models and querysets.

Q19. How to do you create a Django project?

To create a Django project, cd into the directory where you would like to create your project and type the following command:

  • django-admin startproject xyz

NOTE: Here, xyz is the name of the project. You can give any name that you desire.

Q20. What is mixin?

Mixin is a type of multiple inheritance wherein you can combine behaviors and attributes of more than one parent class. Mixins provide an excellent way to reuse code from multiple classes. For example, generic class-based views consist of a mixin called TemplateResponseMixin whose purpose is to define render_to_response() method. When this is combined with a class present in the View, the result will be a TemplateView class.

One drawback of using these mixins is that it becomes difficult to analyze what a child class is doing and which methods to override in case of its code being too scattered between multiple classes.

Q21. What are 'sessions'?

Sessions are fully supported in Django. Using the session framework, you can easily store and retrieve arbitrary data based on the per-site-visitors. This framework basically stores data on the server-side and takes care of sending and receiving cookies. These cookies consist of a session ID but not the actual data itself unless you explicitly use a cookie-based backend.

Q22. What do you mean by context?

Context in Django is a dictionary mapping template variable name given to Python objects. This is the conventional name, but you can give any other name of your choice if you wish to do it.

Q23. When can you use iterators in Django ORM?

Iterators in Python are basically containers that consist of a countable number of elements. Any object that is an iterator implements two methods which are, the init() and the next() methods. When you are making use of iterators in Django, the best situation to do it is when you have to process results that will require a large amount of memory space. To do this, you can make use of the iterator() method which basically evaluates a QuerySet and returns the corresponding iterator over the results.

Q24. Explain the caching strategies of Django?

Caching basically means to save the output of an expensive calculation in order to avoid performing the same calculation again. Django provides a robust cache system which in turn helps you save dynamic web pages so that they don't have to be evaluated over and over again for each request. Some of the caching strategies of Django are listed down in the following table:

Q25. Explain the use of Middlewares in Django.

Middleware is a framework that is light and low-level plugin system for altering Django's input and output globally. It is basically a framework of hooks into the request/ response processing of Django. Each component in middleware has some particular task.

For example, the AuthenticationMiddleware is used to associate users with requests using sessions. Django provides many other middlewares such as cache middleware to enable site-wide cache, common middleware that performs many tasks such as forbidding access to user agents, URL rewriting, etc, GZip middleware which is used to compress the content for browsers, etc.

Q26. What is the significance of manage.py file in Django?

The manage.py file is automatically generated whenever you create a project. This is basically a command-line utility that helps you to interact with your Django project in various ways. It does the same things as django-admin but along with that, it also sets the DJANGO_SETTINGS_MODULE environment variable in order to point to your project's settings. Usually, it is better to make use of manage.py rather than the django-admin in case you are working on a single project.

Q27. Explain the use of 'migrate' command in Django?

In Django, migrations are used to propagate changes made to the models. The migrate command is basically used to apply or unapply migrations changes made to the models. This command basically synchronizes the current set of models and migrations with the database state. You can use this command with or without parameters. In case you do not specify any parameter, all apps will have all their migrations running.

Q28. How to view and filter items from the database?

In order to view all the items from your database, you can make use of the 'all()' function in your interactive shell as follows:

  • XYZ.objects.all() where XYZ is some class that you have created in your models

To filter out some element from your database, you either use the get() method or the filter method as follows:

  • XYZ.objects.filter(pk=1)
  • XYZ.objects.get(id=1)
Q29. Explain how a request is processed in Django?

In case some user requests a page from some Django powered site, the system follows an algorithm that determines which Python code needs to be executed. Here are the steps that sum up the algorithm:

  1. Django first determines which root URLconf or URL configuration module is to be used
  2. Then, that particular Python module is loaded and then Django looks for the variable urlpatterns
  3. These URL patterns are then run by Django, and it stops at the first match of the requested URL
  4. Once that is done, the Django then imports and calls the given view
  5. In case none of the URLs match the requested URL, Django invokes an error-handling view
Q30. How did Django come into existence?

Django basically grew from a very practical need. World Online developers namely Adrian Holovaty and Simon Willison started using Python to develop its websites. As they went on building intensive, richly interactive sites, they began to pull out a generic Web development framework that allowed them to build Web applications more and more quickly. In summer 2005, World Online decided to open-source the resulting software, which is, Django.

Q31. How to use file-based sessions?

In order to make use of file-based sessions, you will need to set the SESSION_ENGINE setting to "django.contrib.sessions.backends.
file".

Q32. Explain the Django URLs in brief?

Django allows you to design your own URLs however you like. The aim is to maintain a clean URL scheme without any framework limitations. In order to create URLs for your app, you will need to create a Python module informally called the URLconf or URL configuration which is pure Python code and is also a mapping between the URL path expressions to the Python methods.

The length of this mapping can be as long or short as required and can also reference other mappings. When processing a request, the requested URL is matched with the URLs present in the urls.py file and the corresponding view is retrieved. For more details about this, you can refer to the answer to Q29.

Q33. Give the exception classes present in Django.

Django uses its own exceptions as well as those present in Python. Django core exceptions are present in django.core.exceptions class some of which are mentioned in the table below:

Q34. Is Django stable?

Yes, Django is quite stable. Many companies like Instagram, Discus, Pinterest, and Mozilla have been using Django for a duration of many years now. Not just this, Websites that are built using Django have weathered traffic spikes of over 50 thousand hits per second.

Q35. Does the Django framework scale?

Yes. Hardware is much cheaper when compared to the development time and this is why Django is designed to make full use of any amount of hardware that you can provide it. Django makes use of a “shared-nothing” architecture meaning you can add hardware at any level i.e database servers, caching servers or Web/ application servers.

Q36. Is Django a CMS?

Django is not a CMS (content-management-system) . It is just a Web framework, a tool that allows you to build websites.

Q37. What Python version should be used with Django?

The following table gives you the details of the versions of Python that you can use for Django:

Python 3 is actually the most recommended because it is fast, has more features and is better supported. In the case of Python 2.7, Django 1.1 can be used along with it but only till the year 2020.

Q38. Does Django support NoSQL?

NoSQL basically stands for “not only SQL”. This is considered as an alternative to the traditional RDBMS or the relational Databases. Officially, Django does not support NoSQL databases. However, there are third-party projects, such as Django non-rel, that allow NoSQL functionality in Django. Currently, you can use MongoDB and Google App Engine.

Q39. How can you customize the functionality of the Django admin interface?

There are a number of ways to do this. You can piggyback on top of an add/ change form that is automatically generated by Django, you can add JavaScript modules using the js parameter. This parameter is basically a list of URLs that point to the JavaScript modules that are to be included in your project within a

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Top 100 Python Interview Questions and Answers

Top 100 Python Interview Questions and Answers

In this article, we brought 100 essential Python interview questions to acquaint you with the skills and knowledge required to succeed in a job interview.

In this article, we brought 100 essential Python interview questions to acquaint you with the skills and knowledge required to succeed in a job interview.

Our team which includes experienced Python programmers have made a careful selection of the questions to keep a balance between theory and practical knowledge. So, you can get the full advantage.

Not only the job aspirants but also the recruiters can refer this post to know the right set of questions to evaluate a candidate. Let’s now step-in to explore the Python Q&A section.

100 Essential Python Interview Questions

Let’s begin answering the fundamental-level Python interview questions.

Q-1: What is Python, what are the benefits of using it, and what do you understand of PEP 8?

Python is one of the most successful interpreted languages. When you write a Python script, it doesn’t need to get compiled before execution. Few other interpreted languages are PHP and Javascript.

Benefits of Python Programming

  • Python is a dynamic-typed language. It means that you don’t need to mention the data type of variables during their declaration. It allows to set variables like var1=101 and var2 =” You are an engineer.” without any error.
  • Python supports object orientated programming as you can define classes along with the composition and inheritance. It doesn’t use access specifiers like public or private).
  • Functions in Python are like first-class objects. It suggests you can assign them to variables, return from other methods and pass as arguments.
  • Developing using Python is quick but running it is often slower than compiled languages. Luckily, Python enables to include the “C” language extensions so you can optimize your scripts.
  • Python has several usages like web-based applications, test automation, data modeling, big data analytics and much more. Alternatively, you can utilize it as a “glue” layer to work with other languages.

PEP 8.

PEP 8 is the latest Python coding standard, a set of coding recommendations. It guides to deliver more readable Python code.

Q-2: What is the output of the following Python code fragment? Justify your answer.

def extendList(val, list=[]):
    list.append(val)
    return list

list1 = extendList(10)
list2 = extendList(123,[])
list3 = extendList('a')

print "list1 = %s" % list1
print "list2 = %s" % list2
print "list3 = %s" % list3

The result of the above Python code snippet is:

list1 = [10, 'a']
list2 = [123]
list3 = [10, 'a']

You may erroneously expect list1 to be equal to [10] and list3 to match with [‘a’], thinking that the list argument will initialize to its default value of [] every time there is a call to the extendList.

However, the flow is like that a new list gets created once after the function is defined. And the same get used whenever someone calls the extendList method without a list argument. It works like this because the calculation of expressions (in default arguments) occurs at the time of function definition, not during its invocation.

The list1 and list3 are hence operating on the same default list, whereas list2 is running on a separate object that it has created on its own (by passing an empty list as the value of the list parameter).

The definition of the extendList function can get changed in the following manner.

def extendList(val, list=None):
  if list is None:
    list = []
  list.append(val)
  return list

With this revised implementation, the output would be:

list1 = [10]
list2 = [123]
list3 = ['a']

Q-3: What is the statement that can be used in Python if the program requires no action but requires it syntactically?

The pass statement is a null operation. Nothing happens when it executes. You should use “pass” keyword in lowercase. If you write “Pass,” you’ll face an error like “NameError: name Pass is not defined.” Python statements are case sensitive.

letter = "hai sethuraman"
for i in letter:
    if i == "a":
        pass
        print("pass statement is execute ..............")
    else:
        print(i)

Q-4: What’s the process to get the home directory using ‘~’ in Python?

You need to import the os module, and then just a single line would do the rest.

import os
print (os.path.expanduser('~'))

Output:

/home/runner

Q-5: What are the built-in types available in Python?

Here is the list of most commonly used built-in types that Python supports:

  • Python is a dynamic-typed language. It means that you don’t need to mention the data type of variables during their declaration. It allows to set variables like var1=101 and var2 =” You are an engineer.” without any error.
  • Python supports object orientated programming as you can define classes along with the composition and inheritance. It doesn’t use access specifiers like public or private).
  • Functions in Python are like first-class objects. It suggests you can assign them to variables, return from other methods and pass as arguments.
  • Developing using Python is quick but running it is often slower than compiled languages. Luckily, Python enables to include the “C” language extensions so you can optimize your scripts.
  • Python has several usages like web-based applications, test automation, data modeling, big data analytics and much more. Alternatively, you can utilize it as a “glue” layer to work with other languages.

Q-6: How to find bugs or perform static analysis in a Python application?

  • Python is a dynamic-typed language. It means that you don’t need to mention the data type of variables during their declaration. It allows to set variables like var1=101 and var2 =” You are an engineer.” without any error.
  • Python supports object orientated programming as you can define classes along with the composition and inheritance. It doesn’t use access specifiers like public or private).
  • Functions in Python are like first-class objects. It suggests you can assign them to variables, return from other methods and pass as arguments.
  • Developing using Python is quick but running it is often slower than compiled languages. Luckily, Python enables to include the “C” language extensions so you can optimize your scripts.
  • Python has several usages like web-based applications, test automation, data modeling, big data analytics and much more. Alternatively, you can utilize it as a “glue” layer to work with other languages.

Q-7: When is the Python decorator used?

Python decorator is a relative change that you do in Python syntax to adjust the functions quickly.

Q-8: What is the principal difference between a list and the tuple?

List vs. Tuple.

The principal difference between a list and the tuple is that the former is mutable while the tuple is not.

A tuple is allowed to be hashed, for example, using it as a key for dictionaries.

Q-9: How does Python handle memory management?

  • Python is a dynamic-typed language. It means that you don’t need to mention the data type of variables during their declaration. It allows to set variables like var1=101 and var2 =” You are an engineer.” without any error.
  • Python supports object orientated programming as you can define classes along with the composition and inheritance. It doesn’t use access specifiers like public or private).
  • Functions in Python are like first-class objects. It suggests you can assign them to variables, return from other methods and pass as arguments.
  • Developing using Python is quick but running it is often slower than compiled languages. Luckily, Python enables to include the “C” language extensions so you can optimize your scripts.
  • Python has several usages like web-based applications, test automation, data modeling, big data analytics and much more. Alternatively, you can utilize it as a “glue” layer to work with other languages.

Q-10: What are the principal differences between the lambda and def?

Lambda vs. def.

  • Python is a dynamic-typed language. It means that you don’t need to mention the data type of variables during their declaration. It allows to set variables like var1=101 and var2 =” You are an engineer.” without any error.
  • Python supports object orientated programming as you can define classes along with the composition and inheritance. It doesn’t use access specifiers like public or private).
  • Functions in Python are like first-class objects. It suggests you can assign them to variables, return from other methods and pass as arguments.
  • Developing using Python is quick but running it is often slower than compiled languages. Luckily, Python enables to include the “C” language extensions so you can optimize your scripts.
  • Python has several usages like web-based applications, test automation, data modeling, big data analytics and much more. Alternatively, you can utilize it as a “glue” layer to work with other languages.

Q-11: Write a reg expression that confirms an email id using the python reg expression module “re”?

Python has a regular expression module “re.”

Check out the “re” expression that can check the email id for .com and .co.in subdomain.

import re
print(re.search(r"[0-9a-zA-Z.][email protected][a-zA-Z]+\.(com|co\.in)$","[email protected]"))

Q-12: What do you think is the output of the following code fragment? Is there any error in the code?

list = ['a', 'b', 'c', 'd', 'e']
print (list[10:])

The result of the above lines of code is []. There won’t be any error like an IndexError.

You should know that trying to fetch a member from the list using an index that exceeds the member count (for example, attempting to access list[10] as given in the question) would yield an IndexError. By the way, retrieving only a slice at the starting index that surpasses the no. of items in the list won’t result in an IndexError. It will just return an empty list.

Q-13: Is there a switch or case statement in Python? If not then what is the reason for the same?

No, Python does not have a Switch statement, but you can write a Switch function and then use it.

Q-14: What is a built-in function that Python uses to iterate over a number sequence?

Range() generates a list of numbers, which is used to iterate over for loops.

for i in range(5):
    print(i)

The range() function accompanies two sets of parameters.

  • Python is a dynamic-typed language. It means that you don’t need to mention the data type of variables during their declaration. It allows to set variables like var1=101 and var2 =” You are an engineer.” without any error.
  • Python supports object orientated programming as you can define classes along with the composition and inheritance. It doesn’t use access specifiers like public or private).
  • Functions in Python are like first-class objects. It suggests you can assign them to variables, return from other methods and pass as arguments.
  • Developing using Python is quick but running it is often slower than compiled languages. Luckily, Python enables to include the “C” language extensions so you can optimize your scripts.
  • Python has several usages like web-based applications, test automation, data modeling, big data analytics and much more. Alternatively, you can utilize it as a “glue” layer to work with other languages.

Q-15: What are the optional statements possible inside a try-except block in Python?

There are two optional clauses you can use in the try-except block.

  • Python is a dynamic-typed language. It means that you don’t need to mention the data type of variables during their declaration. It allows to set variables like var1=101 and var2 =” You are an engineer.” without any error.
  • Python supports object orientated programming as you can define classes along with the composition and inheritance. It doesn’t use access specifiers like public or private).
  • Functions in Python are like first-class objects. It suggests you can assign them to variables, return from other methods and pass as arguments.
  • Developing using Python is quick but running it is often slower than compiled languages. Luckily, Python enables to include the “C” language extensions so you can optimize your scripts.
  • Python has several usages like web-based applications, test automation, data modeling, big data analytics and much more. Alternatively, you can utilize it as a “glue” layer to work with other languages.

Q-16: What is a string in Python?

A string in Python is a sequence of alpha-numeric characters. They are immutable objects. It means that they don’t allow modification once they get assigned a value. Python provides several methods, such as join(), replace(), or split() to alter strings. But none of these change the original object.

Q-17: What is slicing in Python?

Slicing is a string operation for extracting a part of the string, or some part of a list. In Python, a string (say text) begins at index 0, and the nth character stores at position text[n-1]. Python can also perform reverse indexing, i.e., in the backward direction, with the help of negative numbers. In Python, the slice() is also a constructor function which generates a slice object. The result is a set of indices mentioned by range(start, stop, step). The slice() method allows three parameters. 1. start – starting number for the slicing to begin. 2. stop – the number which indicates the end of slicing. 3. step – the value to increment after each index (default = 1).

Q-18: What is %s in Python?

Python has support for formatting any value into a string. It may contain quite complex expressions.

One of the common usages is to push values into a string with the %s format specifier. The formatting operation in Python has the comparable syntax as the C function printf() has.

Q-19: Is a string immutable or mutable in Python?

Python strings are indeed immutable.

Let’s take an example. We have an “str” variable holding a string value. We can’t mutate the container, i.e., the string, but can modify what it contains that means the value of the variable.

Q-20: What is the index in Python?

An index is an integer data type which denotes a position within an ordered list or a string.

In Python, strings are also lists of characters. We can access them using the index which begins from zero and goes to the length minus one.

For example, in the string “Program,” the indexing happens like this:

Program 0 1 2 3 4 5

Q-21: What is Docstring in Python?

A docstring is a unique text that happens to be the first statement in the following Python constructs:

Module, Function, Class, or Method definition.

A docstring gets added to the doc attribute of the string object.

Now, read some of the Python interview questions on functions.

Q-22: What is a function in Python programming?

A function is an object which represents a block of code and is a reusable entity. It brings modularity to a program and a higher degree of code reusability.

Python has given us many built-in functions such as print() and provides the ability to create user-defined functions.

Q-23: How many basic types of functions are available in Python?

Python gives us two basic types of functions.

  1. Built-in, and

  2. User-defined.

The built-in functions happen to be part of the Python language. Some of these are print(), dir(), len(), and abs() etc.

Q-24: How do we write a function in Python?

We can create a Python function in the following manner.

Step-1: to begin the function, start writing with the keyword def and then mention the function name.

Step-2: We can now pass the arguments and enclose them using the parentheses. A colon, in the end, marks the end of the function header.

Step-3: After pressing an enter, we can add the desired Python statements for execution.

Q-25: What is a function call or a callable object in Python?

A function in Python gets treated as a callable object. It can allow some arguments and also return a value or multiple values in the form of a tuple. Apart from the function, Python has other constructs, such as classes or the class instances which fits in the same category.

Q-26: What is the return keyword used for in Python?

The purpose of a function is to receive the inputs and return some output.

The return is a Python statement which we can use in a function for sending a value back to its caller.

Q-27: What is “Call by Value” in Python?

In call-by-value, the argument whether an expression or a value gets bound to the respective variable in the function.

Python will treat that variable as local in the function-level scope. Any changes made to that variable will remain local and will not reflect outside the function.

Q-28: What is “Call by Reference” in Python?

We use both “call-by-reference” and “pass-by-reference” interchangeably. When we pass an argument by reference, then it is available as an implicit reference to the function, rather than a simple copy. In such a case, any modification to the argument will also be visible to the caller.

This scheme also has the advantage of bringing more time and space efficiency because it leaves the need for creating local copies.

On the contrary, the disadvantage could be that a variable can get changed accidentally during a function call. Hence, the programmers need to handle in the code to avoid such uncertainty.

Q-29: What is the return value of the trunc() function?

The Python trunc() function performs a mathematical operation to remove the decimal values from a particular expression and provides an integer value as its output.

Q-30: Is it mandatory for a Python function to return a value?

It is not at all necessary for a function to return any value. However, if needed, we can use None as a return value.

Q-31: What does the continue do in Python?

The continue is a jump statement in Python which moves the control to execute the next iteration in a loop leaving all the remaining instructions in the block unexecuted.

The continue statement is applicable for both the “while” and “for” loops.

Q-32: What is the purpose of id() function in Python?

The id() is one of the built-in functions in Python.

Signature: id(object)

It accepts one parameter and returns a unique identifier associated with the input object.

Q-33: What does the *args do in Python?

We use *args as a parameter in the function header. It gives us the ability to pass N (variable) number of arguments.

Please note that this type of argument syntax doesn’t allow passing a named argument to the function.

Example of using the *args:

# Python code to demonstrate 
# *args for dynamic arguments 
def fn(*argList):  
    for argx in argList:  
        print (argx) 
    
fn('I', 'am', 'Learning', 'Python')

The output:

I
am
Learning
Python

Q-34: What does the **kwargs do in Python?

We can also use the **kwargs syntax in a Python function declaration. It let us pass N (variable) number of arguments which can be named or keyworded.

Example of using the **kwargs:

# Python code to demonstrate 
# **kwargs for dynamic + named arguments 
def fn(**kwargs):  
    for emp, age in kwargs.items(): 
        print ("%s's age is %s." %(emp, age)) 
    
fn(John=25, Kalley=22, Tom=32)

The output:

John's age is 25.
Kalley's age is 22.
Tom's age is 32.

Q-35: Does Python have a Main() method?

The main() is the entry point function which happens to be called first in most programming languages.

Since Python is interpreter-based, so it sequentially executes the lines of the code one-by-one.

Python also does have a Main() method. But it gets executed whenever we run our Python script either by directly clicking it or starts it from the command line.

We can also override the Python default main() function using the Python if statement. Please see the below code.

print("Welcome")
print("__name__ contains: ", __name__)
def main():
    print("Testing the main function")
if __name__ == '__main__':
    main()

The output:

Welcome
__name__ contains:  __main__
Testing the main function

Q-36: What does the __ Name __ do in Python?

The name is a unique variable. Since Python doesn’t expose the main() function, so when its interpreter gets to run the script, it first executes the code which is at level 0 indentation.

To see whether the main() gets called, we can use the name variable in an if clause compares with the value “main.”

Q-37: What is the purpose of “end” in Python?

Python’s print() function always prints a newline in the end. The print() function accepts an optional parameter known as the ‘end.’ Its value is ‘\n’ by default. We can change the end character in a print statement with the value of our choice using this parameter.

# Example: Print a  instead of the new line in the end.
print("Let's learn" , end = ' ')  
print("Python") 

# Printing a dot in the end.
print("Learn to code from techbeamers" , end = '.')  
print("com", end = ' ')

The output is:

Let's learn Python
Learn to code from techbeamers.com

Q-38: When should you use the “break” in Python?

Python provides a break statement to exit from a loop. Whenever the break hits in the code, the control of the program immediately exits from the body of the loop.

The break statement in a nested loop causes the control to exit from the inner iterative block.

Q-39: What is the difference between pass and continue in Python?

The continue statement makes the loop to resume from the next iteration.

On the contrary, the pass statement instructs to do nothing, and the remainder of the code executes as usual.

Q-40: What does the len() function do in Python?

In Python, the len() is a primary string function. It determines the length of an input string.

>>> some_string = 'techbeamers'
>>> len(some_string)
11

Q-41: What does the chr() function do in Python?

The chr() function got re-added in Python 3.2. In version 3.0, it got removed.

It returns the string denoting a character whose Unicode code point is an integer.

For example, the chr(122) returns the string ‘z’ whereas the chr(1212) returns the string ‘Ҽ’.

Q-42: What does the ord() function do in Python?

The ord(char) in Python takes a string of size one and returns an integer denoting the Unicode code format of the character in case of a Unicode type object, or the value of the byte if the argument is of 8-bit string type.

>>> ord("z")
122

Q-43: What is Rstrip() in Python?

Python provides the rstrip() method which duplicates the string but leaves out the whitespace characters from the end.

The rstrip() escapes the characters from the right end based on the argument value, i.e., a string mentioning the group of characters to get excluded.

The signature of the rstrip() is:

str.rstrip([char sequence/pre>
#Example
test_str = 'Programming    '
# The trailing whitespaces are excluded
print(test_str.rstrip())

Q-44: What is whitespace in Python?

Whitespace represents the characters that we use for spacing and separation.

They possess an “empty” representation. In Python, it could be a tab or space.

Q-45: What is isalpha() in Python?

Python provides this built-in isalpha() function for the string handling purpose.

It returns True if all characters in the string are of alphabet type, else it returns False.

Q-46: How do you use the split() function in Python?

Python’s split() function works on strings to cut a large piece into smaller chunks, or sub-strings. We can specify a separator to start splitting, or it uses the space as one by default.

#Example
str = 'pdf csv json'
print(str.split(" "))
print(str.split())

The output:

['pdf', 'csv', 'json']
['pdf', 'csv', 'json']

Q-47: What does the join method do in Python?

Python provides the join() method which works on strings, lists, and tuples. It combines them and returns a united value.

Q-48: What does the Title() method do in Python?

Python provides the title() method to convert the first letter in each word to capital format while the rest turns to Lowercase.

#Example
str = 'lEaRn pYtHoN'
print(str.title())

The output:

Learn Python

Now, check out some general purpose Python interview questions.

Q-49: What makes the CPython different from Python?

CPython has its core developed in C. The prefix ‘C’ represents this fact. It runs an interpreter loop used for translating the Python-ish code to C language.

Q-50: Which package is the fastest form of Python?

PyPy provides maximum compatibility while utilizing CPython implementation for improving its performance.

The tests confirmed that PyPy is nearly five times faster than the CPython. It currently supports Python 2.7.

Q-51: What is GIL in Python language?

Python supports GIL (the global interpreter lock) which is a mutex used to secure access to Python objects, synchronizing multiple threads from running the Python bytecodes at the same time.

Q-52: How is Python thread safe?

Python ensures safe access to threads. It uses the GIL mutex to set synchronization. If a thread loses the GIL lock at any time, then you have to make the code thread-safe.

For example, many of the Python operations execute as atomic such as calling the sort() method on a list.

Q-53: How does Python manage the memory?

Python implements a heap manager internally which holds all of its objects and data structures.

This heap manager does the allocation/de-allocation of heap space for objects.

Q-54: What is a tuple in Python?

A tuple is a collection type data structure in Python which is immutable.

They are similar to sequences, just like the lists. However, There are some differences between a tuple and list; the former doesn’t allow modifications whereas the list does.

Also, the tuples use parentheses for enclosing, but the lists have square brackets in their syntax.

Q-55: What is a dictionary in Python programming?

A dictionary is a data structure known as an associative array in Python which stores a collection of objects.

The collection is a set of keys having a single associated value. We can call it a hash, a map, or a hashmap as it gets called in other programming languages.

Q-56: What is the set object in Python?

Sets are unordered collection objects in Python. They store unique and immutable objects. Python has its implementation derived from mathematics.

Q-57: What is the use of the dictionary in Python?

A dictionary has a group of objects (the keys) map to another group of objects (the values). A Python dictionary represents a mapping of unique Keys to Values.

They are mutable and hence will not change. The values associated with the keys can be of any Python types.

Q-58: Is Python list a linked list?

A Python list is a variable-length array which is different from C-style linked lists.

Internally, it has a contiguous array for referencing to other objects and stores a pointer to the array variable and its length in the list head structure.

Here are some Python interview questions on classes and objects.

Q-59: What is Class in Python?

Python supports object-oriented programming and provides almost all OOP features to use in programs.

A Python class is a blueprint for creating the objects. It defines member variables and gets their behavior associated with them.

We can make it by using the keyword “class.” An object gets created from the constructor. This object represents the instance of the class.

In Python, we generate classes and instances in the following way.

>>>class Human:  # Create the class
...     pass
>>>man = Human()  # Create the instance
>>>print(man)


Q-60: What are Attributes and Methods in a Python class?

A class is useless if it has not defined any functionality. We can do so by adding attributes. They work as containers for data and functions. We can add an attribute directly specifying inside the class body.

>>> class Human:
...     profession = "programmer" # specify the attribute 'profession' of the class
>>> man = Human()
>>> print(man.profession)
programmer

After we added the attributes, we can go on to define the functions. Generally, we call them methods. In the method signature, we always have to provide the first argument with a self-keyword.

>>> class Human:
    profession = "programmer"
    def set_profession(self, new_profession):
        self.profession = new_profession      
>>> man = Human()
>>> man.set_profession("Manager")
>>> print(man.profession)
Manager

Q-61: How to assign values for the Class attributes at runtime?

We can specify the values for the attributes at runtime. We need to add an init method and pass input to object constructor. See the following example demonstrating this.

>>> class Human:
    def __init__(self, profession):
        self.profession = profession
    def set_profession(self, new_profession):
        self.profession = new_profession

>>> man = Human("Manager")
>>> print(man.profession)
Manager

Q-62: What is Inheritance in Python programming?

Inheritance is an OOP mechanism which allows an object to access its parent class features. It carries forward the base class functionality to the child.

We do it intentionally to abstract away the similar code in different classes.

The common code rests with the base class, and the child class objects can access it via inheritance. Check out the below example.

class PC: # Base class
    processor = "Xeon" # Common attribute
    def set_processor(self, new_processor):
        processor = new_processor

class Desktop(PC): # Derived class
    os = "Mac OS High Sierra" # Personalized attribute
    ram = "32 GB"

class Laptop(PC): # Derived class
    os = "Windows 10 Pro 64" # Personalized attribute
    ram = "16 GB"

desk = Desktop()
print(desk.processor, desk.os, desk.ram)

lap = Laptop()
print(lap.processor, lap.os, lap.ram)

The output:

Xeon Mac OS High Sierra 32 GB
Xeon Windows 10 Pro 64 16 GB

Q-63: What is Composition in Python?

The composition is also a type of inheritance in Python. It intends to inherit from the base class but a little differently, i.e., by using an instance variable of the base class acting as a member of the derived class.

See the below diagram.

To demonstrate composition, we need to instantiate other objects in the class and then make use of those instances.

class PC: # Base class
    processor = "Xeon" # Common attribute
    def __init__(self, processor, ram):
        self.processor = processor
        self.ram = ram

    def set_processor(self, new_processor):
        processor = new_processor

    def get_PC(self):
        return "%s cpu & %s ram" % (self.processor, self.ram)

class Tablet():
    make = "Intel"
    def __init__(self, processor, ram, make):
        self.PC = PC(processor, ram) # Composition
        self.make = make

    def get_Tablet(self):
        return "Tablet with %s CPU & %s ram by %s" % (self.PC.processor, self.PC.ram, self.make)

if __name__ == "__main__":
    tab = Tablet("i7", "16 GB", "Intel")
    print(tab.get_Tablet())

The output is:

Tablet with i7 CPU & 16 GB ram by Intel

Q-64: What are Errors and Exceptions in Python programs?

Errors are coding issues in a program which may cause it to exit abnormally.

On the contrary, exceptions happen due to the occurrence of an external event which interrupts the normal flow of the program.

Q-65: How do you handle exceptions with Try/Except/Finally in Python?

Python lay down Try, Except, Finally constructs to handle errors as well as Exceptions. We enclose the unsafe code indented under the try block. And we can keep our fall-back code inside the except block. Any instructions intended for execution last should come under the finally block.

try:
    print("Executing code in the try block")
    print(exception)
except:
    print("Entering in the except block")
finally:
    print("Reached to the final block")

The output is:

Executing code in the try block
Entering in the except block
Reached to the final block

Q-66: How do you raise exceptions for a predefined condition in Python?

We can raise an exception based on some condition.

For example, if we want the user to enter only odd numbers, else will raise an exception.

# Example - Raise an exception
while True:
    try:
        value = int(input("Enter an odd number- "))
        if value%2 == 0:
            raise ValueError("Exited due to invalid input!!!")
        else:
            print("Value entered is : %s" % value)
    except ValueError as ex:
        print(ex)
        break

The output is:

Enter an odd number- 2
Exited due to invalid input!!!
Enter an odd number- 1
Value entered is : 1
Enter an odd number-

Q-67: What are Python Iterators?

Iterators in Python are array-like objects which allow moving on the next element. We use them in traversing a loop, for example, in a “for” loop.

Python library has a no. of iterators. For example, a list is also an iterator and we can start a for loop over it.

Q-68: What is the difference between an Iterator and Iterable?

The collection type like a list, tuple, dictionary, and set are all iterable objects whereas they are also iterable containers which return an iterator while traversing.

Here are some advanced-level Python interview questions.

Q-69: What are Python Generators?

A Generator is a kind of function which lets us specify a function that acts like an iterator and hence can get used in a “for” loop.

In a generator function, the yield keyword substitutes the return statement.

# Simple Python function
def fn():
    return "Simple Python function."

# Python Generator function
def generate():
    yield "Python Generator function."

print(next(generate()))

The output is:

Python Generator function.

Q-70: What are Closures in Python?

Python closures are function objects returned by another function. We use them to eliminate code redundancy.

In the example below, we’ve written a simple closure for multiplying numbers.

def multiply_number(num):
    def product(number):
        'product() here is a closure'
        return num * number
    return product

num_2 = multiply_number(2)
print(num_2(11))
print(num_2(24))

num_6 = multiply_number(6)
print(num_6(1))

The output is:

22
48
6

Q-71: What are Decorators in Python?

Python decorator gives us the ability to add new behavior to the given objects dynamically. In the example below, we’ve written a simple example to display a message pre and post the execution of a function.

def decorator_sample(func):
    def decorator_hook(*args, **kwargs):
        print("Before the function call")
        result = func(*args, **kwargs)
        print("After the function call")
        return result
    return decorator_hook

@decorator_sample
def product(x, y):
    "Function to multiply two numbers."
    return x * y

print(product(3, 3))

The output is:

Before the function call
After the function call
9

Q-72: How do you create a dictionary in Python?

Let’s take the example of building site statistics. For this, we first need to break up the key-value pairs using a colon(“:”). The keys should be of an immutable type, i.e., so we’ll use the data-types which don’t allow changes at runtime. We’ll choose from an int, string, or tuple.

However, we can take values of any kind. For distinguishing the data pairs, we can use a comma(“,”) and keep the whole stuff inside curly braces({…}).

>>> site_stats = {'site': 'tecbeamers.com', 'traffic': 10000, "type": "organic"}
>>> type(site_stats)

>>> print(site_stats)
{'type': 'organic', 'site': 'tecbeamers.com', 'traffic': 10000}

Q-73: How do you read from a dictionary in Python?

To fetch data from a dictionary, we can directly access using the keys. We can enclose a “key” using brackets […] after mentioning the variable name corresponding to the dictionary.

>>> site_stats = {'site': 'tecbeamers.com', 'traffic': 10000, "type": "organic"}
>>> print(site_stats["traffic"])

We can even call the get method to fetch the values from a dict. It also let us set a default value. If the key is missing, then the KeyError would occur.

>>> site_stats = {'site': 'tecbeamers.com', 'traffic': 10000, "type": "organic"}
>>> print(site_stats.get('site'))
tecbeamers.com

Q-74: How do you traverse through a dictionary object in Python?

We can use the “for” and “in” loop for traversing the dictionary object.

>>> site_stats = {'site': 'tecbeamers.com', 'traffic': 10000, "type": "organic"}
>>> for k, v in site_stats.items():
    print("The key is: %s" % k)
    print("The value is: %s" % v)
    print("++++++++++++++++++++++++")

The output is:

The key is: type
The value is: organic
++++++++++++++++++++++++
The key is: site
The value is: tecbeamers.com
++++++++++++++++++++++++
The key is: traffic
The value is: 10000
++++++++++++++++++++++++

Q-75: How do you add elements to a dictionary in Python?

We can add elements by modifying the dictionary with a fresh key and then set the value to it.

>>> # Setup a blank dictionary
>>> site_stats = {}
>>> site_stats['site'] = 'google.com'
>>> site_stats['traffic'] = 10000000000
>>> site_stats['type'] = 'Referral'
>>> print(site_stats)
{'type': 'Referral', 'site': 'google.com', 'traffic': 10000000000}

We can even join two dictionaries to get a bigger dictionary with the help of the update() method.

>>> site_stats['site'] = 'google.co.in'
>>> print(site_stats)
{'site': 'google.co.in'}
>>> site_stats_new = {'traffic': 1000000, "type": "social media"}
>>> site_stats.update(site_stats_new)
>>> print(site_stats)
{'type': 'social media', 'site': 'google.co.in', 'traffic': 1000000}

Q-76: How do you delete elements of a dictionary in Python?

We can delete a key in a dictionary by using the del() method.

>>> site_stats = {'site': 'tecbeamers.com', 'traffic': 10000, "type": "organic"}
>>> del site_stats["type"]
>>> print(site_stats)
{'site': 'google.co.in', 'traffic': 1000000}

Another method, we can use is the pop() function. It accepts the key as the parameter. Also, a second parameter, we can pass a default value if the key doesn’t exist.

>>> site_stats = {'site': 'tecbeamers.com', 'traffic': 10000, "type": "organic"}
>>> print(site_stats.pop("type", None))
organic
>>> print(site_stats)
{'site': 'tecbeamers.com', 'traffic': 10000}

Q-77: How do you check the presence of a key in a dictionary?

We can use Python’s “in” operator to test the presence of a key inside a dict object.

>>> site_stats = {'site': 'tecbeamers.com', 'traffic': 10000, "type": "organic"}
>>> 'site' in site_stats
True
>>> 'traffic' in site_stats
True
>>> "type" in site_stats
True

Earlier, Python also provided the has_key() method which got deprecated.

Q-78: What is the syntax for List comprehension in Python?

The signature for the list comprehension is as follows:

[ expression(var) for var in iterable ]

For example, the below code will return all the numbers from 10 to 20 and store them in a list.

>>> alist = [var for var in range(10, 20)]
>>> print(alist)

Q-79: What is the syntax for Dictionary comprehension in Python?

A dictionary has the same syntax as was for the list comprehension but the difference is that it uses curly braces:

{ aKey, itsValue for aKey in iterable }

For example, the below code will return all the numbers 10 to 20 as the keys and will store the respective squares of those numbers as the values.

>>> adict = {var:var**2 for var in range(10, 20)}
>>> print(adict)

Q-80: What is the syntax for Generator expression in Python?

The syntax for generator expression matches with the list comprehension, but the difference is that it uses parenthesis:

( expression(var) for var in iterable )

For example, the below code will create a generator object that generates the values from 10 to 20 upon using it.

>>> (var for var in range(10, 20))
 at 0x0000000003668728>
>>> list((var for var in range(10, 20)))

Now, see more Python interview questions for practice.

Q-81: How do you write a conditional expression in Python?

We can utilize the following single statement as a conditional expression. default_statment if Condition else another_statement

>>> no_of_days = 366
>>> is_leap_year = "Yes" if no_of_days == 366 else "No"
>>> print(is_leap_year)
Yes

Q-82: What do you know about the Python enumerate?

While using the iterators, sometimes we might have a use case to store the count of iterations. Python gets this task quite easy for us by giving a built-in method known as the enumerate().

The enumerate() function attaches a counter variable to an iterable and returns it as the “enumerated” object.

We can use this object directly in the “for” loops or transform it into a list of tuples by calling the list() method. It has the following signature:

enumerate(iterable, to_begin=0)
Arguments:
iterable: array type object which enables iteration
to_begin: the base index for the counter is to get started, its default value is 0
# Example - enumerate function 
alist = ["apple","mango", "orange"] 
astr = "banana"
  
# Let's set the enumerate objects 
list_obj = enumerate(alist) 
str_obj = enumerate(astr) 
  
print("list_obj type:", type(list_obj))
print("str_obj type:", type(str_obj))

print(list(enumerate(alist)) )  
# Move the starting index to two from zero
print(list(enumerate(astr, 2)))

The output is:

list_obj type: 
str_obj type: 
[(0, 'apple'), (1, 'mango'), (2, 'orange')]
[(2, 'b'), (3, 'a'), (4, 'n'), (5, 'a'), (6, 'n'), (7, 'a')]

Q-83: What is the use of globals() function in Python?

The globals() function in Python returns the current global symbol table as a dictionary object.

Python maintains a symbol table to keep all necessary information about a program. This info includes the names of variables, methods, and classes used by the program.

All the information in this table remains in the global scope of the program and Python allows us to retrieve it using the globals() method.

Signature: globals()

Arguments: None
# Example: globals() function 
x = 9
def fn(): 
    y = 3
    z = y + x
    # Calling the globals() method
    z = globals()['x'] = z
    return z
       
# Test Code     
ret = fn() 
print(ret)

The output is:

12

Q-84: Why do you use the zip() method in Python?

The zip method lets us map the corresponding index of multiple containers so that we can use them using as a single unit.

Signature: 
 zip(*iterators)
Arguments: 
 Python iterables or collections (e.g., list, string, etc.)
Returns: 
 A single iterator object with combined mapped values
# Example: zip() function
  
emp = [ "tom", "john", "jerry", "jake" ] 
age = [ 32, 28, 33, 44 ] 
dept = [ 'HR', 'Accounts', 'R&D', 'IT' ] 
  
# call zip() to map values 
out = zip(emp, age, dept)
  
# convert all values for printing them as set 
out = set(out) 
  
# Displaying the final values  
print ("The output of zip() is : ",end="") 
print (out)

The output is:

The output of zip() is : {('jerry', 33, 'R&D'), ('jake', 44, 'IT'), ('john', 28, 'Accounts'), ('tom', 32, 'HR')}

Q-85: What are Class or Static Variables in Python programming?

In Python, all the objects share common class or static variables.

But the instance or non-static variables are altogether different for different objects.

The programming languages like C++ and Java need to use the static keyword to make a variable as the class variable. However, Python has a unique way to declare a static variable.

All names initialized with a value in the class declaration becomes the class variables. And those which get assigned values in the class methods becomes the instance variables.

# Example 
class Test: 
    aclass = 'programming' # A class variable 
    def __init__(self, ainst): 
        self.ainst = ainst # An instance variable 
  
# Objects of CSStudent class 
test1 = Test(1) 
test2 = Test(2) 
  
print(test1.aclass)
print(test2.aclass)
print(test1.ainst)
print(test2.ainst)

# A class variable is also accessible using the class name
print(Test.aclass)

The output is:

programming
programming
1
2
programming

Let’s now answer some advanced-level Python interview questions.

Q-86: How does the ternary operator work in Python?

The ternary operator is an alternative for the conditional statements. It combines true or false values with a statement that you need to test.

The syntax would look like the one given below.

[onTrue] if [Condition] else [onFalse]

x, y = 35, 75
smaller = x if x < y else y
print(smaller)

Q-87: What does the “self” keyword do?

The self is a Python keyword which represents a variable that holds the instance of an object.

In almost, all the object-oriented languages, it is passed to the methods as a hidden parameter.

Q-88: What are the different methods to copy an object in Python?

There are two ways to copy objects in Python.

  • Python is a dynamic-typed language. It means that you don’t need to mention the data type of variables during their declaration. It allows to set variables like var1=101 and var2 =” You are an engineer.” without any error.
  • Python supports object orientated programming as you can define classes along with the composition and inheritance. It doesn’t use access specifiers like public or private).
  • Functions in Python are like first-class objects. It suggests you can assign them to variables, return from other methods and pass as arguments.
  • Developing using Python is quick but running it is often slower than compiled languages. Luckily, Python enables to include the “C” language extensions so you can optimize your scripts.
  • Python has several usages like web-based applications, test automation, data modeling, big data analytics and much more. Alternatively, you can utilize it as a “glue” layer to work with other languages.

Q-89: What is the purpose of docstrings in Python?

In Python, the docstring is what we call as the docstrings. It sets a process of recording Python functions, modules, and classes.

Q-90: Which Python function will you use to convert a number to a string?

For converting a number into a string, you can use the built-in function str(). If you want an octal or hexadecimal representation, use the inbuilt function oct() or hex().

Q-91: How do you debug a program in Python? Is it possible to step through the Python code?

Yes, we can use the Python debugger (pdb) to debug any Python program. And if we start a program using pdb, then it let us even step through the code.

Q-92: List down some of the PDB commands for debugging Python programs?

Here are a few PDB commands to start debugging Python code.

  • Python is a dynamic-typed language. It means that you don’t need to mention the data type of variables during their declaration. It allows to set variables like var1=101 and var2 =” You are an engineer.” without any error.
  • Python supports object orientated programming as you can define classes along with the composition and inheritance. It doesn’t use access specifiers like public or private).
  • Functions in Python are like first-class objects. It suggests you can assign them to variables, return from other methods and pass as arguments.
  • Developing using Python is quick but running it is often slower than compiled languages. Luckily, Python enables to include the “C” language extensions so you can optimize your scripts.
  • Python has several usages like web-based applications, test automation, data modeling, big data analytics and much more. Alternatively, you can utilize it as a “glue” layer to work with other languages.

Q-93: What is the command to debug a Python program?

The following command helps run a Python program in debug mode.

$ python -m pdb python-script.py

Q-94: How do you monitor the code flow of a program in Python?

In Python, we can use the sys module’s settrace() method to setup trace hooks and monitor the functions inside a program.

You need to define a trace callback method and pass it to the settrace() function. The callback should specify three arguments as shown below.

import sys

def trace_calls(frame, event, arg):
    # The 'call' event occurs before a function gets executed.
    if event != 'call':
        return
    # Next, inspect the frame data and print information.
    print 'Function name=%s, line num=%s' % (frame.f_code.co_name, frame.f_lineno)
    return

def demo2():
    print 'in demo2()'

def demo1():
    print 'in demo1()'
    demo2()

sys.settrace(trace_calls)
demo1()

Q-95: Why and when do you use generators in Python?

A generator in Python is a function which returns an iterable object. We can iterate on the generator object using the yield keyword. But we can only do that once because their values don’t persist in memory, they get the values on the fly.

Generators give us the ability to hold the execution of a function or a step as long as we want to keep it. However, here are a few examples where it is beneficial to use generators.

  • Python is a dynamic-typed language. It means that you don’t need to mention the data type of variables during their declaration. It allows to set variables like var1=101 and var2 =” You are an engineer.” without any error.
  • Python supports object orientated programming as you can define classes along with the composition and inheritance. It doesn’t use access specifiers like public or private).
  • Functions in Python are like first-class objects. It suggests you can assign them to variables, return from other methods and pass as arguments.
  • Developing using Python is quick but running it is often slower than compiled languages. Luckily, Python enables to include the “C” language extensions so you can optimize your scripts.
  • Python has several usages like web-based applications, test automation, data modeling, big data analytics and much more. Alternatively, you can utilize it as a “glue” layer to work with other languages.

Q-96: What does the yield keyword do in Python?

The yield keyword can turn any function into a generator. It works like a standard return keyword. But it’ll always return a generator object. Also, a method can have multiple calls to the yield keyword.

See the example below.

def testgen(index):
  weekdays = ['sun','mon','tue','wed','thu','fri','sat']
  yield weekdays[index]
  yield weekdays[index+1]

day = testgen(0)
print next(day), next(day)

#output: sun mon

Q-97: How to convert a list into other data types?

Sometimes, we don’t use lists as is. Instead, we have to convert them to other types.

Turn a list into a string.

We can use the ”.join() method which combines all elements into one and returns as a string.

weekdays = ['sun','mon','tue','wed','thu','fri','sat']
listAsString = ' '.join(weekdays)
print(listAsString)

#output: sun mon tue wed thu fri sat

Turn a list into a tuple.

Call Python’s tuple() function for converting a list into a tuple.

This function takes the list as its argument.

But remember, we can’t change the list after turning it into a tuple because it becomes immutable.

weekdays = ['sun','mon','tue','wed','thu','fri','sat']
listAsTuple = tuple(weekdays)
print(listAsTuple)

#output: ('sun', 'mon', 'tue', 'wed', 'thu', 'fri', 'sat')

Turn a list into a set.

Converting a list to a set poses two side-effects.

  • Python is a dynamic-typed language. It means that you don’t need to mention the data type of variables during their declaration. It allows to set variables like var1=101 and var2 =” You are an engineer.” without any error.
  • Python supports object orientated programming as you can define classes along with the composition and inheritance. It doesn’t use access specifiers like public or private).
  • Functions in Python are like first-class objects. It suggests you can assign them to variables, return from other methods and pass as arguments.
  • Developing using Python is quick but running it is often slower than compiled languages. Luckily, Python enables to include the “C” language extensions so you can optimize your scripts.
  • Python has several usages like web-based applications, test automation, data modeling, big data analytics and much more. Alternatively, you can utilize it as a “glue” layer to work with other languages.

However, we can use the set() function to convert a list into a Set.

weekdays = ['sun','mon','tue','wed','thu','fri','sat','sun','tue']
listAsSet = set(weekdays)
print(listAsSet)

#output: set(['wed', 'sun', 'thu', 'tue', 'mon', 'fri', 'sat'])

Turn a list into a dictionary.

In a dictionary, each item represents a key-value pair. So converting a list isn’t as straightforward as it were for other data types.

However, we can achieve the conversion by breaking the list into a set of pairs and then call the zip() function to return them as tuples.

Passing the tuples into the dict() function would finally turn them into a dictionary.

weekdays = ['sun','mon','tue','wed','thu','fri']
listAsDict = dict(zip(weekdays[0::2], weekdays[1::2]))
print(listAsDict)

#output: {'sun': 'mon', 'thu': 'fri', 'tue': 'wed'}

Q-98: How do you count the occurrences of each item present in the list without explicitly mentioning them?

Unlike sets, lists can have items with the same values.

In Python, the list has a count() function which returns the occurrences of a particular item.

Count the occurrences of an individual item.

weekdays = ['sun','mon','tue','wed','thu','fri','sun','mon','mon']
print(weekdays.count('mon'))

#output: 3

Count the occurrences of each item in the list.

We’ll use the list comprehension along with the count() method. It’ll print the frequency of each of the items.

weekdays = ['sun','mon','tue','wed','thu','fri','sun','mon','mon']
print([[x,weekdays.count(x)] for x in set(weekdays)])

#output: [['wed', 1], ['sun', 2], ['thu', 1], ['tue', 1], ['mon', 3], ['fri', 1]]

Q-99: What is NumPy and how is it better than a list in Python?

NumPy is a Python package for scientific computing which can deal with large data sizes. It includes a powerful N-dimensional array object and a set of advanced functions.

Also, the NumPy arrays are superior to the built-in lists. There are a no. of reasons for this.

  • Python is a dynamic-typed language. It means that you don’t need to mention the data type of variables during their declaration. It allows to set variables like var1=101 and var2 =” You are an engineer.” without any error.
  • Python supports object orientated programming as you can define classes along with the composition and inheritance. It doesn’t use access specifiers like public or private).
  • Functions in Python are like first-class objects. It suggests you can assign them to variables, return from other methods and pass as arguments.
  • Developing using Python is quick but running it is often slower than compiled languages. Luckily, Python enables to include the “C” language extensions so you can optimize your scripts.
  • Python has several usages like web-based applications, test automation, data modeling, big data analytics and much more. Alternatively, you can utilize it as a “glue” layer to work with other languages.

Q-100: What are different ways to create an empty NumPy array in Python?

There are two methods which we can apply to create empty NumPy arrays.

The first method to create an empty array.

import numpy
numpy.array([])

The second method to create an empty array.

# Make an empty NumPy array
numpy.empty(shape=(0,0))

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Django Interview Questions | Python Interview Questions | Intellipaat

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