Python Interview Questions and Answers, Python Interview Questions and Answers Freshers, Python Interview Questions and Answers, Python Interview Questions

Before getting on to the Python interview questions, the student must know that the Hadoop is a continuously varying field which needs the students as well as professionals to upgrade their skills with the new features and knowledge, to get fit for the jobs associated. This post related to Python Interview Questions and Answers, Python Interview Questions and Answers Freshers, Python Interview Questions and Answers, Python Interview Questions will help you let out find all the solutions that are frequently asked in you upcoming Python interview.

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First of all, let us tell you about how the Python technology is evolving in today’s world and how demanding it is in the upcoming years. In fact, according to one study, most of the companies and businesses have moved to the Python. Now, you cannot predict how huge the future is going to be for the people experienced in the related technologies.

Hence, if you are looking for boosting up your profile and securing your future, Python will help you in reaching the zenith of your career. Apart from this, you would also have a lot of opportunities as a fresher.

These questions alone are omnipotent. Read and re-read the questions and their solutions to get accustomed to what you will be asked in the interview. These Python interview questions and answers will also help you on your way to mastering the skills and will take you to the giant world where worldwide and local businesses, huge or medium, are picking up the best and quality Python professionals.

This ultimate list of best Python interview questions will ride you through the quick knowledge of the subject and topics like Control Flow, Syntax, Decorators. This Python interview questions and answers can be your next gateway to your next job as a Python expert.

These are very Basic Python Interview Questions and Answers for freshers and experienced both.

Q1: What are the key features of Python?
A1: These are the few key features of Python:

  • Python is an interpreted language. That means that, unlike languages like C and its variants, Python does not need to be compiled before it is run. Other interpreted languages include PHP and Ruby.
  • Python is dynamically typed, this means that you don’t need to state the types of variables when you declare them or anything like that. You can do things like x=111 and then x=”I’m a string” without error
  • Python is well suited to object orientated programming in that it allows the definition of classes along with composition and inheritance. Python does not have access specifiers (like C++’s public, private), the justification for this point is given as “we are all adults here”
  • In Python, functions are first-class objects. This means that they can be assigned to variables, returned from other functions and passed into functions. Classes are also first class objects
  • Writing Python code is quick but running it is often slower than compiled languages. Fortunately,Python allows the inclusion of C based extensions so bottlenecks can be optimized away and often are. The numpy package is a good example of this, it’s really quite quick because a lot of the number crunching it does isn’t actually done by Python
  • Python finds use in many spheres – web applications, automation, scientific modelling, big data applications and many more. It’s also often used as “glue” code to get other languages and components to play nice.

Q2: What is the difference between deep and shallow copy?
A2: Shallow copy is used when a new instance type gets created and it keeps the values that are copied in the new instance. Shallow copy is used to copy the reference pointers just like it copies the values. These references point to the original objects and the changes made in any member of the class will also affect the original copy of it. Shallow copy allows faster execution of the program and it depends on the size of the data that is used.

Deep copy is used to store the values that are already copied. Deep copy doesn’t copy the reference pointers to the objects. It makes the reference to an object and the new object that is pointed by some other object gets stored. The changes made in the original copy won’t affect any other copy that uses the object. Deep copy makes execution of the program slower due to making certain copies for each object that is been called.

Q3: How is Multithreading achieved in Python?

  1. Python has a multi-threading package but if you want to multi-thread to speed your code up.
  2. Python has a construct called the Global Interpreter Lock (GIL). The GIL makes sure that only one of your ‘threads’ can execute at any one time. A thread acquires the GIL, does a little work, then passes the GIL onto the next thread.
  3. This happens very quickly so to the human eye it may seem like your threads are executing in parallel, but they are really just taking turns using the same CPU core.
  4. All this GIL passing adds overhead to execution. This means that if you want to make your code run faster then using the threading package often isn’t a good idea.

Q4: How is memory managed in Python?

  1. Python memory is managed by Python private heap space. All Python objects and data structures are located in a private heap. The programmer does not have an access to this private heap and interpreter takes care of this Python private heap.
  2. The allocation of Python heap space for Python objects is done by Python memory manager. The core API gives access to some tools for the programmer to code.
  3. Python also have an inbuilt garbage collector, which recycle all the unused memory and frees the memory and makes it available to the heap space.

Q5: Explain what Flask is and its benefits?
A5: Flask is a web micro framework for Python based on “Werkzeug, Jinja2 and good intentions” BSD license. Werkzeug and Jinja2 are two of its dependencies. This means it will have little to no dependencies on external libraries.  It makes the framework light while there is little dependency to update and less security bugs.

A session basically allows you to remember information from one request to another. In a flask, a session uses a signed cookie so the user can look at the session contents and modify. The user can modify the session if only it has the secret key Flask.secret_key.

Q6: What is the usage of help() and dir() function in Python?
A6: Help() and dir() both functions are accessible from the Python interpreter and used for viewing a consolidated dump of built-in functions.

  1. Help() function: The help() function is used to display the documentation string and also facilitates you to see the help related to modules, keywords, attributes, etc.
  2. Dir() function: The dir() function is used to display the defined symbols.

Q7: Explain split(), sub(), subn() methods of “re” module in Python.
A7: To modify the strings, Python’s “re” module is providing 3 methods. They are:

  • split() – uses a regex pattern to “split” a given string into a list.
  • sub() – finds all substrings where the regex pattern matches and then replace them with a different string
  • subn() – it is similar to sub() and also returns the new string along with the no. of replacements.

Q8: What is pickling and unpickling?
A8: Pickle module accepts any Python object and converts it into a string representation and dumps it into a file by using dump function, this process is called pickling. While the process of retrieving original Python objects from the stored string representation is called unpickling.

Q9: Is python a case-sensitive language?
A9: Yes! Python is a case sensitive programming language.

Q10: What are the supported data types in Python?
A10: Python has five standard data types −

  • Numbers
  • String
  • List
  • Tuple
  • Dictionary

Q11: What are Python’s dictionaries?
A11: Python’s dictionaries are kind of hash table type. They work like associative arrays or hashes found in Perl and consist of key-value pairs. A dictionary key can be almost any Python type, but are usually numbers or strings. Values, on the other hand, can be any arbitrary Python object.

Q12: How will you get a titlecased version of string?
A12: title() − Returns “titlecased” version of string, that is, all words begin with uppercase and the rest are lowercase.

Q13: How will you compare two lists?
A13: cmp(list1, list2) − Compares elements of both lists.

Q14: What is PEP 8?
A14: PEP 8 is a coding convention, a set of recommendation, about how to write your Python code more readable.

Q15: How Python is interpreted?
A15: Python language is an interpreted language. Python program runs directly from the source code. It converts the source code that is written by the programmer into an intermediate language, which is again translated into machine language that has to be executed.

Q16: What are the tools that help to find bugs or perform the static analysis?
A16: PyChecker is a static analysis tool that detects the bugs in Python source code and warns about the style and complexity of the bug. Pylint is another tool that verifies whether the module meets the coding standard.

Q17: What are Python decorators?
A17: A Python decorator is a specific change that we make in Python syntax to alter functions easily.

Q18: What is the difference between list and tuple?
A18: The difference between list and tuple is that list is mutable while tuple is not. Tuple can be hashed for e.g as a key for dictionaries.

Q19: What is Dict and List comprehensions are?
A19: They are syntax constructions to ease the creation of a Dictionary or List based on existing iterable.

Q20: What is namespace in Python?
A20: In Python, every name introduced has a place where it lives and can be hooked for. This is known as namespace. It is like a box where a variable name is mapped to the object placed.  Whenever the variable is searched out, this box will be searched, to get corresponding object.

Q21: Why lambda forms in python do not have statements?
A21: A lambda form in python does not have statements as it is used to make new function object and then return them at runtime.

Q22: How will you get all the keys from the dictionary?
A22: Using dictionary.keys() function, we can get all the keys from the dictionary object.
print dict.keys()   # Prints all the keys

Q23: What is the purpose of a // operator?
A23: // Floor Division − The division of operands where the result is the quotient in which the digits after the decimal point are removed.

Q24: What is the purpose of not in operator?
 not in − Evaluates to true if it does not finds a variable in the specified sequence and false otherwise. x not in y, here not in results in a 1 if x is not a member of sequence y.

Q25: How will you set the starting value in generating random numbers?
A25: seed([x]) − Sets the integer starting value used in generating random numbers. Call this function before calling any other random module function. Returns None.

Q26: What is used for?
A26:It declares that the given directory is a  package. #Python Docs (From Endophage‘s comment)

Q27: Given the list below remove the repetition of an element.
Q27: All the elements should be unique
words = [‘one’, ‘one’, ‘two’, ‘three’, ‘three’, ‘two’]

Q28: How do you invoke the Python interpreter for interactive use?
A28: python or pythonx.y where x.y are the version of the Python interpreter desired.

Q29: How are Phon blocks defined?
A29: By indents or tabs. This is different from most other languages which use symbols to define blocks. Indents in Python are significant.

Q30: Explain the difference between local and global namespaces.
A30: Local namespaces are created within a function. when that function is called. Global name spaces are created when the program starts.

Q31: What is the Encapsulation?
A31: The concept of binding or grouping related data members along with its related functionalities is known as a Encapsulation.

Q32: What is Garbage Collection?
A32: The concept of removing unused or unreferenced objects from the memory location is known as a Garbage Collection.
While executing the program, if garbage collection takes place then more memory space is available for the program and rest of the program execution becomes faster.
Garbage collector is a predefined program, which removes the unused or unreferenced objects from the memory location
Any object reference count becomes zero then we call that object as a unused or unreferenced object
Then no.of reference variables which are pointing the object is known as a reference count of the object.
While executing the python program if any object reference count becomes zero, then internally python interpreter calls the garbage collector and garbage collector will remove that object from memory location.

Q33: What is scheduling?
A33: Among multiple threads which thread as to start the execution first, how much time the thread as to execute after allocated time is over, which thread as to continue the execution next this comes under scheduling

Scheduling is highly dynamic

Q34: What is Threads Life Cycle?

Creating the object of a class which is overwriting run method of thread class is known as a creating thread
Whenever thread is created then we call thread is in new state or birth state thread.
Whenever we call the start method on the new state threads then those threads will be forwarded for scheduling
The threads which are forwarded for scheduling are known as ready state threads
Whenever scheduling time occurs, ready state thread starts execution
The threads which are executing are known as running state threads
Whenever sleep fun or join methods are called on the running state threads then immediately those threads will wait.
The threads which are waiting are known as waiting state threads
Whenever waiting time is over or specified thread execution is over then immediately waiting state threads are forwarded for scheduling.
If running state threads execution is over then immediately those threads execution will be terminated
The threads which execution is terminated are known as dead state threads.

Q35: What Does The <Self> Keyword Do?
A35: The <self> keyword is a variable that holds the instance of an object. In almost, all the object-oriented languages, it is passed to the methods as hidden parameter. 

Q36: What Are Different Methods To Copy An Object In Python?
A36: There are two ways to copy objects in Python.

  • copy() function
    • It makes a copy of the file from source to destination.
    • It’ll return a shallow copy of the parameter.
  • deepcopy() function
    • It also produces the copy of an object from the source to destination.
    • It’ll return a deep copy of the parameter that you can pass to the function.

Q37: What Are The Optional Statements That Can Be Used Inside A <Try-Except> Block In Python?
A37: There are two optional clauses you can use in the <try-except> block.

  • The <else>clause
    • It is useful if you want to run a piece of code when the try block doesn’t create any exception.
  • The <finally>clause
    • It is useful when you want to execute some steps which run, irrespective of whether there occurs an exception or not.

Q38: Python and multi-threading. Is it a good idea? List some ways to get some Python code to run in a parallel way.
A38: Python doesn’t allow multi-threading in the truest sense of the word. It has a multi-threading package but if you want to multi-thread to speed your code up, then it’s usually not a good idea to use it. Python has a construct called the Global Interpreter Lock (GIL). The GIL makes sure that only one of your ‘threads’ can execute at any one time. A thread acquires the GIL, does a little work, then passes the GIL onto the next thread. This happens very quickly so to the human eye it may seem like your threads are executing in parallel, but they are really just taking turns using the same CPU core. All this GIL passing adds overhead to execution. This means that if you want to make your code run faster then using the threading package often isn’t a good idea.

There are reasons to use Python’s threading package. If you want to run some things simultaneously, and efficiency is not a concern, then it’s totally fine and convenient. Or if you are running code that needs to wait for something (like some IO) then it could make a lot of sense. But the threading library won’t let you use extra CPU cores.

Multi-threading can be outsourced to the operating system (by doing multi-processing), some external application that calls your Python code (eg, Spark or Hadoop), or some code that your Python code calls (eg: you could have your Python code call a C function that does the expensive multi-threaded stuff).

Python Conclusion Interview FAQs

We know the list of Python Interview Questions and Answers, Python Interview Questions and Answers Freshers, Python Interview Questions and Answers, Python Interview Questions is overwhelming but the advantages of reading all the questions will maximize your potential and help you crack the interview. The surprising fact is that this Python interview questions and answers post covers all the basic of the Python technology and you have to check out the FAQs of different components of Python too.

However, you will be asked with the questions in the interview related to the above mentioned questions. Preparing and understanding all the concept of Python technology will help you strengthen the other little information around the topic.

After preparing these interview questions, we recommend you to go for a mock interview before facing the real one. You can take the help of your friend or a Python expert to find the loop holes in your skills and knowledge. Moreover, this will also allow you in practicing and improving the communication skill which plays a vital role in getting placed and grabbing high salaries.

Remember, in the interview, the company or the business or you can say the examiner often checks your basic knowledge of the subject. If your basics is covered and strengthened, you can have the job of your dream. The industry experts understand that if the foundation of the student is already made up, it is easy for the company to educate the employ towards advance skills. If there are no basics, there is no meaning of having learnt the subject.

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We hope that you enjoyed reading Python Interview Questions and Answers, Python Interview Questions and Answers Freshers, Python Interview Questions and Answers, Python Interview Questions and all the FAQs associated with the interview. Do not forget to revise all the Python interview questions and answers before going for the Python interview. In addition to this, if you’ve any doubt or query associated with Python, you can contact us anytime. We will be happy to help you out at our earliest convenience. At last, we wish you all the best for your upcoming interview on Python Technology.