Python interview questions and answers for 2022

This basic Python interview question warms up the candidate for the interview and is important even for senior Python positions. How you tackle this question displays your experience and expertise with the programming language. Python is a high-level, object-oriented programming language that enhances user interaction through objects, modules, and automatic memory. Due to Python being a cross-platform programming language, it can run on a myriad of different Operating Systems such as Windows, Linux, Macintosh, and UNIX. The language finds widespread use in data science, artificial intelligence, and machine learning because of its in-built data structures. Despite being a high-level language, the simplicity of its syntax makes Python a very easy language to grasp. Moreover, because Python supports various modules and packages, making applications using Python becomes extremely easy as less code is required.

Another basic Python interview question that tries to gauge the depth of your understanding of the language. Python is considered to be a multi-paradigm language, which means it supports multiple programming techniques including object-oriented and functional programming. Since most Python tools have bundled up data and functions, it is considered to be object-oriented. The functions of Python are important for data scientists and programmers alike because Python supports both object-oriented and functional programming.

In Python, variables are used for labeling and storing data. There are mainly two types of variables in Python - local and global. When a variable is not defined within a function, therefore is referenced within that function, its scope is global and it is called a global variable. When a variable is defined within a function, its scope is local and it is called a local variable. Additionally, using the keyword, ‘global’, you can explicitly declare a variable, declared within a function, as a global variable. Since the local variable is defined within a function, when accessed outside that function, it will return an error. Global variables, on the other hand, can be accessed throughout the program.

Slicing in Python is about dividing a given string to obtain sub-strings. If you wish to access sequences such as lists, tuples, and strings, slicing is the feature that will help you do so. You can select a specific range or part of these sequences using slicing. You can change or delete parts of sequences like lists that can be changed. Slicing in Python helps you write clean, precise, and readable code. You can perform slicing in Python by either extending indexing or using the slice() Constructor.

This Python interview question delves somewhat deeper into the programming language. In order to give a distinct and unique name to every single object, Python has a system called, namespace. The value of the object, which can be a variable or a method, is connected to the unique name assigned to that object. While searching for the object, the key, which corresponds to the unique name, is mapped with the value assigned to the related object.. Python has its namespace maintained like a Python dictionary.

Pass is a placeholder for the future code in Python. When the pass statement is executed, no operation takes place. It basically depicts a blank space, however, in places, like loops, class definitions, conditional statements such as: if statements, or even in function definitions, where empty code is not permitted, a pass can be used to prevent an error. The pass statement is not ignored by the Python interpreter, as it returns a null value, therefore it is different from a comment, which is ignored by the Python interpreter. This Python interview question can display your alertness and future orientation to the interviewer.

Unittest or unit testing is a way to test various codes in Python to ascertain whether they can be used safely or not. This framework is in-built in Python and helps to ensure the quality of code in Python. All the criteria, that are found to be useful and practical during the development process, are coded into the test script by the Python developer. This is done to ensure unit preciseness and accuracy. If any criterion fails, it is reported in the summary. This Python interview question can help the interviewer assess whether you are careful and stringent where the safety of code is concerned.

All programming languages use positive indexing in the arrays to locate and access elements. Python is the only language that allows both positive and negative indexing in arrays. A positive index would start from the first element of an array and go forward i.e. the first element would be 0, the second element would be 1, and so on. In negative indexing, the last element of the array would have the index -1, the penultimate element would be -2, and so on.

For example, arr = [a, b, c, d, e] print(arr[-1]) print(arr[-2]) Output e d

Python docstrings are strings that help note the module, classes, functions, and methods such that the python developer can understand their function without the need to go through their implementation. In online programming, it is common to see online documentation generated automatically through the help of docstrings. This Python interview question is a favorite among interviewers as it helps them assess the learning orientation of developers.

PYTHONPATH can be defined as an environment variable that guides the user to find the modules or directories that the user can add to the sys.path directory list. Normally, a user would set PYTHONPATH before running the interpreter because it has the initialization file with the Python source code. This Python interview question helps the interviewer know whether you have in-depth knowledge of Python or not.

NumPy Array is created using C, therefore it is presented in an easy-to-understand-and-use module. Lists have to be dynamically typed which means that every data element type must be checked by Python, every time it is typed. As compared to lists, data structures in NumPy occupy less space, are faster, and have built-in optimized structures like linear algebra.

In Python, memory is allocated by apportioning a block of space or private heap in the computer memory. This private heap contains all the data structures and objects. The interpreter, and not the programmer, has access to this private heap. The collection of objects and data structures to this private heap is automatic. The Python memory manager manages this private heap.

The Microsoft Open Database Connectivity is an interface for the C programming language. It is the standard for all APIs using database C. If you use a Python ODBC interface with the standard ODBC drivers that ship with most databases, you can likely connect your Python application with most databases in the market. The different Python ODBC modules are pyodbc, PythonWin ODBC, and MxODBC.

The pickle module is used for serializing or de-serializing an object structure in Python. Pickling is also known as serialization or marshaling and is used for converting Python object hierarchy into a byte stream. Unpickling is the reverse process in which the byte-like object is converted back into the object hierarchy.

You can use a secure connection with the extensions SMTP_SSL() and .starttls(). Following this step, use the built-in smtplib library module to define the SMTP client session object. This object can then be used to send the email message using Python Script. To send the emails you can use HTML content, as well as, the attachments with the email package. If you use a CSV file that contains contact data, you can even send a number of personalized emails. If you add a few lines of code to your Gmail account, you can configure the Yagmail package to send emails. Through this Python interview question, interviewers can understand your knack for applying Python for different uses.