Featured Post

Claude Code for Beginners: Step-by-Step AI Coding Tutorial

-
Image
 Artificial Intelligence is changing how developers write software. From generating code to fixing bugs and explaining complex logic, AI tools are becoming everyday companions for programmers. One such powerful tool is Claude Code , powered by Anthropic’s Claude AI model. If you’re a beginner or  an experienced developer looking to improve productivity, this guide will help you understand  what Claude Code is, how it works, and how to use it step-by-step . Let’s get started. What is Claude Code? Claude Code is an AI-powered coding assistant built on top of Anthropic’s Claude models. It helps developers by: Writing code from natural language prompts Explaining existing code Debugging errors Refactoring code for better readability Generating tests and documentation In simple words, you describe what you want in plain English, and Claude Code helps turn that into working code. It supports multiple programming languages, such as: Python JavaScri...
Post a Comment

5 Tricky Python Interpreter Interview Questions

-

Python is an interpreter, which converts to byte-code when it first encounters the .py module. It is portable. And, it is a one-time job.



IN THIS PAGE


  1. Python Interpreter Interview Questions

Python Interpreter


1 - What's an Interpreter?


Python interpreter converts source-code to byte-code when you first execute it is non-runnable code. The only software can process that code. During Python installation, a virtual environment will create. This environment can parse the byte code.



2 - What're the differences Between Bytecode and Machine Code?


  • Machine code is binary that you can see in the form of 0,1s.
  • Byte code is non-readable, only a designated software can parse it.

3 - How does Python Interpreter Work?

Self-read flow chart. The smiley is byte-code. It uses other libraries and create byte-code.


Python interpreter is not a compiler. It is tricky, interviews, they may confuse you. This answer is perfect for how the interpreter works in Python.
Execution flow of Interpreter


4 - When you Install Python, the list of components do you think to install?


Interpreter and Libraries.


Interpreter.


The process of the interpreter is BlackBox to the programmer. The interpreter will create a .pyc module. It will then be input to PVM (Python Virtual Machine). So you don't need to interpret it when you invoke next time.



The PVM (Python Virtual Machine) is just like JVM in Java, a run-time environment, which executes Byte-code and gives you output. Here are 4 Python Oops Concepts.



Libraries.


During the Python installation, you can see a lot of other libraries do install. These libraries help the interpreter work smoothly.


A Flowchart that shows how Python interpreter uses the Libraries to create byte code.



Python Byte-code


5. What is the name of the Module That creates PVM?

It is called Venu. The source code present at Lib/venv/.


Keep Reading

Comments

Post a Comment

Thanks for your message. We will get back you.

Popular posts from this blog

SQL Query: 3 Methods for Calculating Cumulative SUM

-
Image
SQL provides various constructs for calculating cumulative sums, offering flexibility and efficiency in data analysis. In this article, we explore three distinct SQL queries that facilitate the computation of cumulative sums. Each query leverages different SQL constructs to achieve the desired outcome, catering to diverse analytical needs and preferences. Using Window Functions (e.g., PostgreSQL, SQL Server, Oracle) SELECT id, value, SUM(value) OVER (ORDER BY id) AS cumulative_sum  FROM your_table; This query uses the SUM() window function with the OVER clause to calculate the cumulative sum of the value column ordered by the id column. Using Subqueries (e.g., MySQL, SQLite): SELECT t1.id, t1.value, SUM(t2.value) AS cumulative_sum FROM your_table t1 JOIN your_table t2 ON t1.id >= t2.id GROUP BY t1.id, t1.value ORDER BY t1.id; This query uses a self-join to calculate the cumulative sum. It joins the table with itself, matching rows where the id in the first table is greater than...
Read more

Step-by-Step Guide to Reading Different Files in Python

-
Image
 In the world of data science, automation, and general programming, working with files is unavoidable. Whether you’re dealing with CSV reports, JSON APIs, Excel sheets, or text logs, Python provides rich and easy-to-use libraries for reading different file formats. In this guide, we’ll explore how to read different files in Python , with code examples and best practices. 1. Reading Text Files ( .txt ) Text files are the simplest form of files. Python’s built-in open() function handles them effortlessly. Example: # Open and read a text file with open ( "sample.txt" , "r" ) as file: content = file.read() print (content) Explanation: "r" mode means read . with open() automatically closes the file when done. Best Practice: Always use with to handle files to avoid memory leaks. 2. Reading CSV Files ( .csv ) CSV files are widely used for storing tabular data. Python has a built-in csv module and a powerful pandas library. Using cs...
Read more

5 SQL Queries That Popularly Used in Data Analysis

-
Image
 Here are five popular SQL queries frequently used in data analysis. 1. SELECT with Aggregations Summarize data by calculating aggregates like counts, sums, averages, etc. SELECT department, COUNT(*) as employee_count, AVG(salary) as average_salary FROM employees GROUP BY department; 2. JOIN Operations  Combine data from multiple tables based on a related column. SELECT e.employee_id, e.name, d.department_name FROM employees e JOIN departments d ON e.department_id = d.department_id; 3. WHERE Clause for Filtering Filter records based on specified conditions. SELECT * FROM sales WHERE sale_date BETWEEN '2024-01-01' AND '2024-12-31'   AND amount > 1000; 4. ORDER BY Clause for Sorting Sort results in ascending or descending order based on one or more columns. SELECT product_name, price FROM products ORDER BY price DESC; 5. GROUP BY with HAVING Clause Group records and apply conditions to the aggregated results. SELECT department, SUM(salary) as total_salaries FROM employ...
Read more