Do you have a scheduled programming interview, or are you an IT professional actively looking for a coding-related job? Well, our article will come in handy. We will discuss some of the questions you should expect about Python, one of the most-used programming languages.
You must prepare adequately for your upcoming interview. We have reviewed some of the questions asked in Python-related interviews and picked the most common. Take a look at the following, rehearse well, and increase your chances of success:
1. Define Python
Python is one of the most common programming languages. It is a general-purpose and high-level language used for different software development and programming projects. This language supports threads, objects, automatic memory management, and modules. It allows developers to easily model real-life problems and develop solutions using Python, which explains why it is popular.
2. Why Would You Advise One To Use Python In Their Programming Projects?
Python comes with several advantages worth experiencing. As I mentioned, it is a high-level, general-purpose, and interpreted language that can build any application provided that the right tools are used. Thanks to high-level data structures that support dynamic building and typing, it comes in handy in rapid deployment and application development. Python is also easy to use. Its syntax can be easily grasped. Lastly, this language has better readability and lower maintenance cost, making it one of the best programming languages.
3. Your Resume Shows That You Are Highly Experienced In Python. Can You Define Scope?
The scope is a common term in Python. It is found in all the objects in Python, existing as a block of code that support relevance. These objects are found inside programs and uniquely identified by namespaces. The namespaces further define these scopes, allowing object use without requiring a prefix. Some of the scopes created when executing code in Python include the local scope, which ate the local objects found in various functions; global scopes, which are objects that exist during the entire execution stage and module-level scopes. It is worth noting that out of the available scopes, it is easy to synchronize local and global scopes objects via keywords.
4. Python Has Unit Tests. Define Them
Programming languages have test frameworks. Unit Tests are, therefore, Python’s test frameworks. They support a process known as unit testing, where different software components are separately tested, making it easier to identify any component in the software that leads to failure.
5. Define What Namespaces Are In Python And Why They Are Used
Namespaces are important in Python. They ensure the uniqueness of project names in different python programs, making them easy to use. Several namespaces can use the same name and map into different objects, given that they exist as dictionaries. Like the scopes, there exist different namespaces. The local namespace is temporarily created for function calls. Their lifecycle ends with the return of the function.
On the other hand, global namespaces are names from different imported packages. They are created on importation. Lastly, the built-in namespaces consist of built-in functions and built-in names for the different execution types.
6. Walk Us Through How One Copies An Object In Python
Copying an object in Python is not as hard. However, unlike other programming languages, one needs more than the assignment operator as it doesn’t do the job independently. Copying is thus one by the copy module as the former only binds the existing object and target variable name. The copy module supports both shallow and deep copy. For the shallow copy, the copied object resembles the original object regarding values. On the other hand, deep copying gives rise to recursive values.
7. Define Want Pickling And Unpickling Are In Python
The pickle module supports serialization, which can be defined as transforming an object into a format that can be easily stored as it awaits deserialization. Pickling refers to the serialization process where objects are serialized into a Bute stream and dumped as files. Such objects can also be compressed further. Unpickling, on the other hand, refers to reversing the former process. The byte system is deserialized in this case. Instead of the function pickle.dump() used in pickling, we use pickle.load() when Unpickling.
8. Tell Us About The Key Features Of Python
Python has several features that explain why it is one of the most used languages for programming and application development. First, it is an interpreted language, meaning it doesn’t have to be compiled to run. Secondly, it is applied in several spheres such as scientific modeling, augmentation, big data applications, and automation. Other features include dynamically typing, having an object-oriented language, and first-class objects as functions. Lastly, writing Python core is quick.
9. Mention The Common Built-In Data Types In Python
There are seven common built-in data types in Python. They include numbers such as complex and floating-point numbers, tuple, which is an order sequence of elements; a list which is an ordered sequence of items; set, which is a collection of unique items not arranged in a particular way; Boolean, which has two values- true and false. Other data types are string and dictionary.
10. Python Has Literals. What Are They?
The python source code has literals which are fixed values for primitive data types. Python has five types of literals: string, Boolean, numeric, and character Literals. The fifth literal collections consist of list collections, type literals, dictionary literals, special literals, and set literals. The string literals are constructed by assigning code texts in single or double quotes to variables, which result in multiline literals. For character literals, a single character enclosed in double quotes is assigned. Numeric literals have numeric values such as integers, and lastly, Boolean literals consist of either true or false.
11. Walk Us Through How One Can Combine Data Frames In Pandas
Python has data frames that can be combined in three main ways. The first two methods are concatenating data where data frames are stacked vertically or horizontally. The last means is combining the data frames of common columns, also known as joining. To concatenate data, the Concat function is used. It is also worth noting that for data frames to be combined, they have to be joined on a key, which is a common column. The join is used when all the rows in data frames are joined are referred to as the outer join, while for the common rows, the join is called the inner join.
12. Have You Ever Used The Python 3.9.0.0 Version? Mention The Key Features Added?
There are nine key additional features found in the latest Python version. It contains new dictionary functions Update(|=) and Merger(|), improved modules, new modules such as graphlib, erroneous methods and functions removal, depreciates commands and functions, new string methods that aid in prefixes and suffixes removal, type hinting generics in standard collections, new parser based on PEG and not LL1, optimizations such as signal handling etc. These make Python 3.9.0.0 more powerful than the previous versions.
13. Mention How Memory Is Managed In Python
There are three ways of managing memory in Python. The main way is through the Python private heap space, which contains all the python objects and data structures. However, a programmer does not always have access to the private heap and often relies on the python interpreter. This programming language also has an in-built garbage collector,making unused memory available to the heap space after recycling. Lastly, the core API of Python lets programmers access tools that can be used to code. The Python memory manager is often responsible for the allocation of heap space.
14. Python Has Break, Pass And Continue Functions. How Do They Work?
The break, continue and work functions are some of the most common functions in Python. Programmers often use the pass to retrieve a block of code without necessary executing it syntactically. It, therefore, supports a null operation. Continue is used to skip a part of a loop after meeting a given condition. In this case, control is automatically transferred to the loop’s beginning. Lastly, the brake function lets a programmer terminate the loop after a condition has been met. It transfers control to the next statement.
15. Do You Know How To Generate Random Numbers In Python?
Yes. To generate random numbers in Python, I often use the random module defined as import random and random.random. When random.random is used, the floating-point number in the range of [0,1] is returned, thus generating random float numbers. The random class uses the hidden instances and bound methods. Other random generators that can be applied to this effect are the randrange(a, b), the random class, uniform(a,b) and normalvariate(mean, sdev). The uniform(a,b) generator picks a floating-point number defined in the range of (a,b) while the normalvariate(mean,sdev) performs normal distribution. In this instance, the mu refers to the mean, while the sdev is the sigma used for standard variation.
16. Can You Differentiate Range And Xrange?
Xrange and range are quite similar in that they have the same functionality. They can be used to generate a list of integers used in different scenarios and as a developer wish. Their difference comes in the product returned. The Xrange function returns an Xrange object while the former is a Python list object. One cannot develop a static list at run time with the Xrange function instead of the range. On the other hand, it uses a technique known as yielding, supported by generators. Xrange works for huge ranges.
17. Mention The Advantages Of Numpy Arrays Over Nested Python Lists
NumPy arrays haveseveral advantages over nested python lists. Even though Python’s lists are considered amazing general-purpose containers since they support efficient insertion, appending, concatenation and deletion features, they come with several limitations. One cannot access vectorized operations such as eliminative multiplication and addition. However, NumPy is way more efficient and convenient. It allows matrix and vector operations without any added cost, making work easier. They can also be efficiently implemented. Lastly, the NumPy array is faster and has several built-in features such as basic statistics, linear algebra and histograms. It, therefore, comes with more advantages than the former.
18. Can You Multithread With Python?
Yes. Python comes with a multi-threading package that allows developers to speed up their code, even though it is not advisable to use. This is the Global Interpreter Lock (GIL), which ensures that only one of the threads is executed at one time. Once the thread acquires the Global Interpreter Lock, it undergoes a few operations andpasses to the GIL and the next thread. This feature uses the same CPU core, making it hard for the human eye to supervise the multi-threading process.
19. Define Inheritance In Python
Inheritance is when one class gains another class’s attributes and methods. It provides room for code reusability, allowing developers to create and maintain applications without breaking a sweat. The primary and former inheritance class is called a superclass, and the inherited class refers to as the child class. Python supports several inheritance types such as single, multi-level, multiple and hierarchical inheritance. In single inheritance, the members of a single superclass are acquired by the derived class. For multiple inheritances,inheritance happens frommore than one base class. Hierarchical inheritance lowers the inheritance of any number of child classes from the base class.
20. What Is A Flask?
Python has a web microframework known as a flask,based on Werkzeug, Jinja2 and good intentions BSD license, the first two acting as dependencies. The flask, therefore, rarely depends on any external libraries, making its framework light with reduced security bugs. The flask has sessions allowing developers to remember information from one session to the next. Flask sessions use signed cookies, allowing visibility and modifications of sessions’ contents
21. Now That You Have Defined What A Flask Is, Can You Compare It To Django?
Django and flask have a similar functionality given that they both map URLs and addresses typed in web browsers to functions. Even though the flask has a simpler framework than Django, it is limited in its automatic functionalities, meaning that the developer hasto do lots of work. Django comes with a prewritten code to be used for analysis, while flask dictates that users build their codes. All in all, even though both of them are good, they come with their advantages and disadvantages.
22. Tell Us About The Pros Of Using Python In Projects
Python has several pros that explain its popularity. First, it is beginner-friendly, making it the best programming language for newbies who want to be coders. It is not as technical; therefore, getting the hang of it wouldn’t be as hard. Python is also widely used owing to its beginner friendliness, guaranteeing you a large community of Python coders, professionals and developers. Furthermore, this programming language is flexible and extensible to other languages. You can easily write code in C and C++ languages.
23. Why Is Python Considered Beginner Friendly?
Almost every newbie is told to try Python first, owing to its beginner friendliness. It is one of the best languages for those starting to code from scratch simply because it is less technical. It is not as demanding as other languages. Furthermore, it is easy to learn and understand.
It is common knowledge that you don’t need to go extra to define the coding block when advancing. Thanks to Python being a verbose language, beginners can read it as they do in English. Python also has a large community behind it, meaning that finding help as a beginner isn’t as hard. Lastly, indentation is a must in Python, making it readable.
24. Python Has Its Disadvantages. Mention Them
Even though Python is a great programming language, it is not recommended for projects with complicated designs unless the developer is highly experienced and qualified. This is due to some of the issues developers face when handling such projects. It is also common knowledge that this language is slower than other non-compiled languages as one needs higher computational power. Lastly, Python needs the right work environment before one begins working ona project,only favoring experienced coders. Poor setupof the coding environment automatically leads to a rough coding experience.
25. From Experience, What Should One Consider When Picking The Right Programming Language For A Project?
The first consideration a coder or developer should make when picking the right programming language is the type of application. We have web, mobile and embedded software applications that require different programming languages. They will determine whether you use general or specific programming languages. The complexity of the application and its size also matters a lot. Lastly, one should consider factors such as the company culture, ease of maintainability, available community support, and security.
Conclusion
These are some common interview questions about Python, one of the most common general programming languages. It is a beginner-friendly language, so you shouldn’t have a problem answering questions about its technical aspects. We wish you all the best in your upcoming interview and hope you will get the job.
