A collection of powerful, reusable utility scripts designed to streamline development, automate tasks, and enhance workflow efficiency.

This repository contains modular and production-ready utilities for:

• Logging & Error Handling – Robust logging setup and custom error-handling decorators.
• Repository Automation – Quickly initialize new Git repositories with useful templates.
• Data Analysis – Summarization tools for CSV files, statistics computation, and visualizations.
• Web Development Scaffolding – Automate project setup with HTML/CSS/JS frameworks and backend support.
• Machine Learning Experimentation – Dataset loaders, model training, and evaluation scripts.
• Web Scraping & Automation – Dynamic price scraping and automated web interactions.
• PDF Utilities – Merge, split, watermark, encrypt, and extract text from PDFs.

Whether you're building software, analyzing data, or automating workflows, these utilities make your development process faster, cleaner, and more efficient.

• Centralized logging for debugging and monitoring.
• Custom error handling with decorators and retry mechanisms.

• Automated Git repository setup, including README.md, .gitignore, and license generation.
• Command-line interface for quick initialization.

• CSV parsing and cleaning, including detection of numerical columns and interactive data removal.
• Statistical computation: mean, median, mode, variance, standard deviation, and correlation matrices.
• Visualization: automatic generation of histograms, boxplots, and scatter plots for numerical data.

• Automated creation of structured web development folders.
• Optional integration with HTML/CSS/JS frameworks such as Bootstrap, Tailwind, Flask, or Express.
• Backend server setup for Python (Flask) and Node.js (Express).

• Dataset loaders for MNIST, CIFAR-10, and others.
• Model training and evaluation pipelines, including loss tracking and accuracy computation.
• Model checkpointing for saving and restoring trained models.

• Price scraping with dynamic fetching and logging.
• Automated browsing using Helium for programmatic web interactions.

• Merge multiple PDFs into one.
• Split PDFs into individual pages.
• Add text-based watermarks to each page.
• Extract text from PDFs by page.
• Encrypt PDFs with password protection.

1. Clone the Repository

   git clone https://github.com/zanemilo/utils.git
   cd utils

2. Set Up a Virtual Environment

   python -m venv venv
   source venv/bin/activate  # Windows: venv\Scripts\activate

3. Install Dependencies

   pip install -r requirements.txt

python webdev_setup.py --project-name MyApp --include-server flask --license MIT

Creates a fully structured web development project with an optional backend.

python data_summary.py sample.csv --output summary.csv --save-plots

Parses CSV data, computes statistics, and generates visualizations.

python price_scraper.py --product "Laptop" --url "https://example.com/product"

Logs and tracks product price changes over time.

python ml_utils.py --dataset mnist --epochs 10 --batch_size 32 --lr 0.001 --save_path mnist_model.pth

Trains a model on MNIST with adjustable parameters.

python pdf_utils.py merge output.pdf file1.pdf file2.pdf
python pdf_utils.py split input.pdf output_folder
python pdf_utils.py watermark input.pdf output.pdf "Watermark Text"
python pdf_utils.py extract input.pdf
python pdf_utils.py encrypt input.pdf output.pdf password

Perform PDF merges, splits, watermarking, text extraction, and encryption through a command-line interface.

This project is licensed under the MIT License – free to use, modify, and contribute.

Contributions are welcome. Feel free to fork, submit pull requests, or open issues.

GitHub • LinkedIn

• Add requirements.txt (can be generated if needed)
• Refine documentation for each script as necessary
• Consider making the repository public once finalized