README.md

Project 3: Docker Container for Data Processing Script

Project Overview

This project involves building and deploying a Docker container that automates text file processing through a Python script. The container will count words, handle contractions, find frequent words, and display results along with the machine’s IP address. Screenshots of Docker Desktop and a tar file of the final container image are required for submission.

Requirements

Part 1: Docker Installation

1. Install Docker Desktop on your personal computer (Windows, macOS, or Linux).
2. Submit a screenshot of Docker Desktop showing your containers running.

Part 2: Dockerfile Setup

1. Create a Dockerfile using a lightweight base image (e.g., ubuntu, alpine, or python:3.9-slim).
2. Submit the Dockerfile as a text file or share it on GitHub.

Part 3: Script Development

1. Write a Python script (scripts.py) to read and process two text files, IF.txt and AlwaysRememberUsThisWay.txt, from /home/data inside the container.
2. Submit the script as a text file or on GitHub.

Part 4: Script Objectives

The Python script should accomplish the following:

• Word Count in Each File: Count the total number of words in each file.
• Grand Total Word Count: Sum the word counts from both files.
• Top 3 Frequent Words in IF.txt: Find and display the three most frequent words in IF.txt with counts.
• Top 3 Frequent Words in AlwaysRememberUsThisWay.txt: Handle contractions (e.g., "I'm") by splitting, then display the three most frequent words with counts.
• IP Address Retrieval: Display the IP address of the machine running the container.
• Output Results: Write all results to /home/data/output/result.txt and print the contents to the console upon container execution.

Part 5: Optimize Docker Image

• Minimize the Docker image size (target size: less than 200MB).

Part 6: Submit Final Image

1. Create a tar file of your final Docker image, named with your email username (e.g., yourusername.tar).
2. Submit the tar file for evaluation.

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Extra Credit

• Container Orchestration with Kubernetes or Docker Swarm:
  • Deploy and manage at least two replicas of your container using Kubernetes or Docker Swarm.
  • Submit your Kubernetes manifest (YAML file) or Docker Swarm configuration.
  • Provide the output of kubectl get pods > kube_output.txt; cat kube_output.txt or an equivalent command for Docker Swarm.

Key Points to Remember

• Use a lightweight base image in the Dockerfile to minimize the final image size.
• Ensure the script can handle contractions and edge cases.
• The container should be fully automated, executing, generating output, and exiting without manual interaction.
• Test the container to ensure it runs correctly on any machine.
• Confirm that all outputs (word counts, IP address, etc.) are written to result.txt and printed to the console when the container runs.

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Application Setup Screenshots

Below are the key screenshots documenting each step of the application setup on AWS EC2.