CodeAlpha Python Programming Internship

A collection of four Python projects completed during the CodeAlpha Python Programming Internship. Each project targets a different domain—game development, finance, natural language processing, and automation—demonstrating practical Python skills from fundamentals through real-world integrations.

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Overview

Project	File	Purpose	Dependencies
Hangman Game	hangman.py	Interactive console word-guessing game	None (stdlib)
Stock Portfolio Tracker	copy_of_stock_portfolio_tracker.py	Real-time stock tracking with API & visualization	See requirements.txt
Conversational Chatbot	conversational_chatbot.py	Rule-based chatbot powered by NLP	See requirements.txt
Task Automation	task_automation_with_python_scripts.py	Automated file organization by type	None (stdlib)

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Skills Demonstrated

Core Python

• Functions, loops, conditionals, and dictionaries
• User input handling and input validation
• Modular code structure with reusable functions
• Interactive CLI menus and game loops

APIs & Data

• REST API integration (Alpha Vantage for stock data)
• JSON parsing and error handling
• Data manipulation with pandas
• Financial calculations (portfolio value, profit/loss)

Data Visualization

• Plotting with matplotlib and seaborn
• Time-series visualization of stock prices
• Custom charts with labels, grids, and formatting

Natural Language Processing (NLP)

• Text preprocessing and tokenization with NLTK
• Named entity and linguistic analysis with spaCy
• Stop-word removal and intent-based response generation
• Dual preprocessing pipelines (NLTK vs spaCy)

Automation & File Systems

• Directory creation and file traversal with os
• File moving and organization with shutil
• Extension-based classification and batch processing

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Projects in Detail

1. Hangman Game

A classic Hangman game played entirely in the terminal. The player guesses letters to reveal a hidden programming-related word before running out of attempts.

Features

• Random word selection from a curated word list
• ASCII art hangman stages (7 stages)
• Letter validation and duplicate-guess detection
• Win/loss detection with clear feedback

Dependencies: None — uses Python standard library only (random).

Run

python hangman.py

Skills: Game logic, string manipulation, set operations, user interaction, control flow.

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2. Stock Portfolio Tracker

A portfolio management tool that fetches live stock prices and tracks investment performance. Originally built in Google Colab with progressive enhancements—from a basic tracker to a version with pre-loaded holdings and price visualization.

Features

• Add, remove, and view stocks in a portfolio
• Real-time price lookup via Alpha Vantage API
• Profit/loss calculation per holding and total portfolio value
• Stock price visualization over time (matplotlib + seaborn)
• Interactive menu-driven interface

Setup

1. Install dependencies from the repo root: pip install -r requirements.txt
2. Get a free API key from Alpha Vantage.
3. Set your key in the script (replace the empty API_KEY or use an environment variable).

Packages used: requests, pandas, matplotlib, seaborn (listed in requirements.txt).

Run

python copy_of_stock_portfolio_tracker.py

Skills: API integration, financial data handling, data visualization, error handling, interactive CLI design.

Note: The script contains Colab-specific cells (!pip install). For local use, install dependencies via pip and run the final menu-driven section. Avoid committing API keys to version control.

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3. Conversational Chatbot

A rule-based chatbot that understands user intent through natural language preprocessing. Supports both NLTK and spaCy pipelines for text tokenization and stop-word filtering.

Features

• Greeting, farewell, help, joke, and small-talk responses
• Intent detection via keyword matching on preprocessed tokens
• Configurable preprocessing: nltk or spacy
• Continuous conversation loop until the user exits

Setup

1. Install dependencies from the repo root: pip install -r requirements.txt
2. Download the spaCy English model:

   python -m spacy download en_core_web_sm

3. NLTK data (punkt, stopwords) is downloaded automatically when you run the script.

Packages used: nltk, spacy (listed in requirements.txt).

Run

python conversational_chatbot.py

Skills: NLP fundamentals, text preprocessing, tokenization, stop-word removal, intent matching, conversational UI.

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4. Task Automation — File Organizer

Automates sorting of files in a folder into categorized subfolders based on file extension (Images, Documents, Videos, Audio, Others).

Features

• Auto-creates category folders if missing
• Moves files by extension (.jpg, .pdf, .mp4, etc.)
• Fallback Others folder for unrecognized types
• Progress logging for each moved file

Dependencies: None — uses Python standard library only (os, shutil).

Run

python task_automation_with_python_scripts.py

Skills: Scripting, filesystem operations, batch automation, path handling.

Note: The original script was written for Google Colab with Drive mounting. Update downloads_folder to a local path (e.g. C:/Users/You/Downloads) before running locally.

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Tech Stack

Category	Tools & Libraries
Language	Python 3
NLP	NLTK, spaCy
Data	pandas
Visualization	matplotlib, seaborn
HTTP / APIs	requests, Alpha Vantage
Automation	os, shutil
Dependency management	requirements.txt
Environment	Google Colab (development), local Python (execution)

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Dependencies

All third-party packages are listed in requirements.txt:

Package	Used by
requests	Stock Portfolio Tracker
pandas	Stock Portfolio Tracker
matplotlib	Stock Portfolio Tracker
seaborn	Stock Portfolio Tracker
nltk	Conversational Chatbot
spacy	Conversational Chatbot

Hangman and Task Automation need no external packages — only the Python standard library.

One-time setup after pip install:

python -m spacy download en_core_web_sm

NLTK corpora (punkt, stopwords) download automatically when you run the chatbot.

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Getting Started

Prerequisites

• Python 3.8+
• pip

1. Clone the repository

git clone https://github.com/<your-username>/CodeAlpha_tasks.git
cd CodeAlpha_tasks

2. Install dependencies

pip install -r requirements.txt
python -m spacy download en_core_web_sm

3. Run a project

python hangman.py
python copy_of_stock_portfolio_tracker.py
python conversational_chatbot.py
python task_automation_with_python_scripts.py

Only install what you need: Hangman and Task Automation run without step 2. Steps 2–3 apply to Stock Tracker and Chatbot.

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Repository Structure

CodeAlpha_tasks/
├── hangman.py                              # Console Hangman game
├── copy_of_stock_portfolio_tracker.py      # Stock portfolio tracker + charts
├── conversational_chatbot.py               # NLP chatbot (NLTK / spaCy)
├── task_automation_with_python_scripts.py  # File organization automation
├── requirements.txt                        # Python dependencies
└── README.md                               # Project documentation

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Internship Summary

Through the CodeAlpha Python Programming Internship, these projects covered:

1. Python fundamentals — logic, data structures, and interactive programs
2. External integrations — REST APIs and live data fetching
3. Data analysis & visualization — pandas and plotting libraries
4. NLP basics — preprocessing pipelines and conversational agents
5. Practical automation — filesystem scripts for real-world tasks

Each project was developed and tested in Google Colab, then exported as standalone Python scripts for this repository.

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Author

Roman Ahmad Khan
CodeAlpha Python Programming Internship

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License

This repository is for educational and portfolio purposes. Feel free to explore and learn from the code.