🐍 Python Core Laboratory 1 — Operators, String Processing & List Operations

Documented Academic Laboratory Submission: Computational Jupyter Notebooks and Graded Technical Reports on Arithmetic Operations and Sequences.

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📌 Table of Contents

• 📖 Executive Summary & Overview
• 🎯 Key Features & Capabilities
• 🏗️ System Architecture & Pipeline
• 🛠️ Tech Stack Breakdown
• ⚙️ Reproducible Quickstart & Setup
• 📁 Project Directory Layout
• 🧪 Testing & Validation
• 🔮 Future Improvements & Roadmap
• 🤝 Contributing Guidelines
• 👨‍💻 Author & Contributions

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📖 Executive Summary & Overview

Foundational computer science pedagogy requires hands-on experimentation with operator precedence, string immutability, and dynamic array reallocation. Without practical verification of arithmetic operators, bitwise logic, and slice indexing, programming errors frequently compound in higher-level numerical modules.

The Python Core Laboratory 1 (Python-Assignment-1) provides a documented laboratory submission for BCA Python Programming coursework by Amaraiah C. The repository contains the computational notebook ASS-1.ipynb and its formal academic report Assignment 1(LAB).pdf, demonstrating hands-on mastery of arithmetic operations, string transformations, and list manipulations.

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🎯 Key Features & Capabilities

🧮 1. Arithmetic & Precedence Logic

• Complete evaluation of addition, subtraction, multiplication, floor division (//), modulo (%), and exponentiation (**).

🔤 2. String Slicing & Methods

• Slice notation with positive/negative step values, token splitting, stripping, and formatting.

📋 3. Dynamic List Processing

• Appending, popping, nested slicing, and in-place list sorting.

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🏗️ System Architecture & Pipeline

flowchart LR
    A["Lab Exercise Prompts<br/>(Assignment 1 LAB.pdf)"] --> B["Interactive Code Cells<br/>(ASS-1.ipynb)"]
    B --> C["Operator Evaluation & Arithmetic Logic"]
    B --> D["String Parsing & Slice Sequences"]
    B --> E["List Mutation & Element Transformations"]
    C --> F["Verified Execution Output"]
    D --> F
    E --> F

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🛠️ Tech Stack Breakdown

Technology	Category	Detail
Language	Python 3.x	Core programming language
Notebook Runtime	Jupyter / Google Colab	Interactive cell-by-cell execution
Documentation	Academic Lab Report (.pdf)	Formal problem statements, code, and output logs

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⚙️ Reproducible Quickstart & Setup

Prerequisites

• Python 3.8+ and Jupyter Notebook installed

# 1. Clone repository
git clone https://github.com/Amaraiah11/Python-Assignment-1.git
cd Python-Assignment-1

# 2. Launch notebook
jupyter notebook ASS-1.ipynb

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📁 Project Directory Layout

Python-Assignment-1/
├── ASS-1.ipynb                # Interactive Jupyter notebook with laboratory solutions
├── Assignment 1(LAB).pdf      # Formal graded academic laboratory report
└── README.md                  # Comprehensive laboratory documentation

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🧪 Testing & Validation

• All notebook cells execute sequentially from top to bottom with zero exceptions.

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🔮 Future Improvements & Roadmap

• Add performance benchmarks comparing Python lists with NumPy array slices.

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👨‍💻 Author & Contributions

This project is developed and maintained with rigorous engineering standards by Amaraiah C, Software Developer and Applied Data Analytics Practitioner studying Bachelor of Computer Applications (BCA) at Alliance University, Bangalore.

• 🌐 GitHub Profile: @Amaraiah11
• 💼 LinkedIn Profile: Connect on LinkedIn
• 📧 Institutional Email: camaraiahBCA24@ced.alliance.edu.in

🤝 Contributing Guidelines

Contributions, bug reports, and architectural discussions are welcome!

1. Fork the repository: https://github.com/Amaraiah11/Python-Assignment-1
2. Create a Feature Branch:

   git checkout -b feature/your-feature-name

3. Commit Your Enhancements:

   git commit -m "feat: enhance feature logic"

4. Push to Your Branch:

   git push origin feature/your-feature-name

5. Open a Pull Request against the main branch.

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