In these following paragraphs, I will discuss top 10 commonly asked interview questions related to Python. This will help you crack any interview as a fresher.
1. What is an interpreted language?#
When a programming language is directly executed line-by-line by an interpreter, it is called interpreted language. Developers prefer these languages because of their dynamic nature. This type of language makes debugging and development of a project easy as it provides immediate feedback.
2. What are the key features of Python?#
Python is a powerful cross-platform programming language that supports various operating systems such as Windows, macOS, and Linux. It is an interpreted language that makes debugging easy and provides immediate feedback. The programming language has various standard libraries for data analysis and web development. These are Numpy, Panda, Django, and many more. Python is also used for OOP functions like encapsulation and polymorphism.
3. What are lists, tuples, and dictionaries in Python?#
A list is a collection of items like integers, floats, and strings. These data types are orderly distributed in the list. The nature of a list is dynamic, so, you can modify them whenever you want.
Like lists, tuples are also collections of data types. But, it is immutable in nature. You can not modify it once you created it.
A dictionary is an unordered collection of key pairs. These key pairs can be lists, tuples, or strings. It is mutable and used to retrieve essential data quickly.
4. How does garbage collection play an important role in handling memory management?#
In Python, the Garbage collection is used to reclaim those memories which are no longer used. This memory management is crucial to prevent memory leaks, leading to the safety of the memory. This also helps coders optimize available memory. The garbage collection mechanism works in two ways: reference counting and cycle detection.
5. What are the advantages of NumPy?#
NumPy is a Python library used for numerical computation and data analysis. If you implement Numpy in C, it will concertedly optimize performance and speed. You can store the same data types in Numpy arrays which makes memory storage efficient. Whereas Python lists store mixed data types, leading to slow performance. Moreover, you can integrate other libraries like SciPy and Pandas with NumPy. This integration enhances productivity and data manipulation and analysis.
6. What is the scope in Python?#
Scope is a crucial aspect of Python. It prevents conflicts in codes. There are four types of scope in Python. They are local, global, enclosing, and built-in. When a variable is defined in a function, it is called the local scope of that function. Global scope is when it is defined outside a function. When a variable is defined in a function and called from its inner functions, it is called enclosing scope.
7. What is the importance of PEP8?
Python enhancement proposal 8 or PEP8 is a guide to making the Python code clean and easy to read. This style guide is mainly used to make codes organized when multiple developers work on a single project.
8. Why is Python popular among developers?#
If you want to start your journey as a coder, Python will be the best option for you due to its simple syntax. The readability of the language is so simple that you can easily grasp any concepts. Even with basic Python coding knowledge, you can build this tool to calculate the petrol cost for your journey. Moreover, this language is a one-stop solution for data analysis and mapping, artificial intelligence, and machine learning. It has many powerful libraries that are helpful for the automation of repetitive tasks.
9. Which Python libraries are used for visualization?#
Matplotib: This is a foundational Python library that is used for interactive visualization. This library supports various types of graphs such as lines, bars, and histograms. You can easily integrate NumPy into this library.
Seaborn: With the Seaborn library, you can create complex visualizations with less code. It also supports various aspects of the plots.
Plotly: Plotly is used to create interactive web applications. Beginners use this library more often due to its user-friendly syntax. You can also create 3D plots and charts using this library.
Altair: Altair is a comprehensive library of Python. It is used for creating complex visualizations on web browsers. It is also used for data mapping and analysis.
10. What are common searching and graph traversal algorithms in Python?#
Linear search is also known as sequential search. It is a simple algorithm used to iterate each element in a list until the largest element is found.
A binary search algorithm can find elements from a sorted list. This algorithm divides the list in half and fixes a middle value. Then, it compares the middle value with the target value.
Breadth-First Search or BFS is a popular algorithm for traversing or searching tree data structures. First, you select a node to begin this algorithm. Then, it traverses all the neighbouring nodes before moving to the next depth level. This algorithm is used to find the shortest path in a graph.
Depth-first search is an algorithm that is used to explore all the nodes going to the depth level before backtracking to its previous position.
You can also check my earlier article on Top 12 JavaScript questions for interview.
The above is the detailed content of Common Python Interview Questions for Fresher. For more information, please follow other related articles on the PHP Chinese website!

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


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