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README.md

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+# Module Lab: Automating Python Projects with Pip, PyPi & Scripting
+
+## Learning Goals
+
+- Automate Python tasks using command-line scripts.
+- Use pip to install and manage external packages.
+- Write modular Python scripts with clean entry points.
+- Track dependencies using a requirements.txt file.
+- Generate structured outputs using file I/O techniques.
+
+## Introduction
+
+In this lab, you will build a **Python automation tool** that uses pip-installed packages and scriptable logic to automate a real-world task. Your script will:
+
+- Use pip to install third-party packages (e.g., `requests`).
+- Fetch or process external data.
+- Write structured output to a local file.
+- Track all dependencies in `requirements.txt` for reproducibility.
+
+This lab emphasizes automation, scripting practices, and environment management using the standard Python ecosystem.
+
+## Setup Instructions
+
+### Fork and Clone the Repository
+
+1. Go to the provided GitHub repository link.
+2. Fork the repository to your GitHub account.
+3. Clone the forked repository to your local machine using:
+
+```bash
+git clone <repo-url>
+cd module-lab-pip-pypi-scripting
+```
+
+### Install Python and pip
+
+Ensure Python and pip are installed:
+
+```bash
+python --version
+pip --version
+```
+
+Optionally, create a virtual environment:
+
+```bash
+python -m venv venv
+source venv/bin/activate  # macOS/Linux
+venv\Scripts\activate   # Windows
+```
+
+Install any required dependencies:
+
+```bash
+pip install -r requirements.txt
+```
+
+## Tasks
+
+### Task 1: Define the Problem
+
+Your goal is to create a **Python script** that automates a small task:
+
+- Uses one or more pip-installed packages (e.g., `requests`, `pandas`, `rich`)
+- Outputs data to a `.txt` or `.csv` file using File I/O
+- Logs or prints messages to confirm behavior
+- Is executable from the command line
+- Records dependencies in `requirements.txt`
+
+---
+
+### Task 2: Determine the Design
+
+You will implement a script with the following design principles:
+
+- Use `pip` to install packages
+- Import modules inside a Python script
+- Wrap logic in `if __name__ == "__main__"` to support reusability
+- Structure output files with filenames that include timestamps
+- Track dependencies using `pip freeze > requirements.txt`
+
+---
+
+### Task 3: Develop and Run Your Script
+
+#### Step 1: Create a script called `generate_log.py`
+
+```python
+from datetime import datetime
+
+log_data = ["User logged in", "User updated profile", "Report exported"]
+filename = f"log_{datetime.now().strftime('%Y%m%d')}.txt"
+
+with open(filename, "w") as file:
+    for entry in log_data:
+        file.write(f"{entry}\n")
+
+print(f"Log written to {filename}")
+```
+
+#### Step 2: Add an API integration using `requests`
+
+```python
+import requests
+
+def fetch_data():
+    response = requests.get("https://jsonplaceholder.typicode.com/posts/1")
+    if response.status_code == 200:
+        return response.json()
+    return {}
+
+if __name__ == "__main__":
+    post = fetch_data()
+    print("Fetched Post Title:", post.get("title", "No title found"))
+```
+
+#### Step 3: Track your dependencies
+
+After installing any packages with `pip install ...`, run:
+
+```bash
+pip freeze > requirements.txt
+```
+
+---
+
+## Best Practices
+
+- Use clear function names (`fetch_data`, `write_log`) for clarity.
+- Always check file write success with print or logging statements.
+- Avoid hardcoding data—use variables and functions where appropriate.
+- Use virtual environments to isolate dependencies.
+- Wrap script logic in `if __name__ == "__main__"` for script reusability.
+
+---
+
+## Conclusion
+
+After completing this lab, you will:
+
+✅ Automate tasks with Python scripting  
+✅ Use external packages from PyPi with pip  
+✅ Track project dependencies with `requirements.txt`  
+✅ Generate structured output files from your script  
+✅ Structure projects for portability and collaboration
+
+These scripting and packaging skills are essential for building automation tools and working in modern Python development workflows.