Learning-Automation 🚀

This repository contains various automation scripts and a common library of functions used by these scripts. The repository is organized to facilitate easy access, modification, and execution of automation tasks.

Getting Started 🌟

Prerequisites 📋

Ensure you have the following installed:

• Python 3.x
• Pip (Python package installer)
• Jupyter Notebook (optional, for working with lib.ipynb)

Setup 🛠️

1. Clone the repository

   git clone https://github.com/deepesh611/Learning-Automation.git
   cd Learning-Automation/src

2. Run setup.sh to install dependencies

   ./setup.sh

3. Running the Script Selection

   • Using PowerShell (Administrator)

   • You can create a shortcut of this file on the Desktop for ease of access, and perform Run with PowerShell on Right-Click

     .\Script-Selection.ps1

   • Create a shortcut: You can create a shortcut of the file Script-Selection.ps1 on your desktop for easy access.

Usage 📚

1. Adding New Scripts

   • Place your new script files in the Scripts directory.

   • Ensure your scripts import the common library i.e lib.py.

     import os
     import sys
     import importlib.util
     
     # Specify the module file path
     lib_path = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', 'lib', 'lib.py'))
     
     # Load the module
     spec = importlib.util.spec_from_file_location("lib", lib_path)
     lib = importlib.util.module_from_spec(spec)
     sys.modules["lib"] = lib
     spec.loader.exec_module(lib)

2. Modifying the Common Library

   • Add or modify functions in lib.py.
   • If you're working in a Jupyter environment, update lib.ipynb accordingly.
   • Always ensure changes are reflected in both lib.py and lib.ipynb.

Contributing 🤝

Contributions are always appreciated. Here are some guidelines to help you get started:

1. Fork the repository and create your branch from main.
2. If you've added code that should be tested, add tests.
3. If you've changed any scripts or the common library, update the documentation.
4. Ensure the new code or scripts follow the existing style and format.
5. Update both lib.py and lib.ipynb when modifying the common library functions.
6. Make sure that you have given proper description in your PR
7. Include your GitHub profile picture and name in the contributors section below.

Contributors ✨

Thanks goes to these wonderful people :

Deepesh Patil 💻 📖 📆

License 📄

This project is licensed under the MIT License - see the LICENSE file for details.