Python Helpers Library 🐍

A comprehensive collection of Python utilities and helper functions designed for learning and practical development tasks.

🎯 Purpose

This repository serves as both a learning resource and a practical utility library for Python developers. Whether you're just starting your Python journey or looking for reusable code snippets for common tasks, this library has you covered.

✨ Features

• 🗂️ File Operations: Safe file handling, JSON processing, directory management
• 📊 Data Processing: Clean, analyze, and transform data with ease
• 🌐 Web Scraping: HTTP requests, HTML parsing, and content extraction
• ⚙️ Automation: Task scheduling, system commands, and file monitoring
• 🔧 Utilities: Password generation, hashing, validation, and more
• 🧪 Well Tested: Comprehensive test suite with pytest
• 📖 Educational: Clear documentation and learning materials

🚀 Quick Start

Installation

# Clone the repository
git clone https://github.com/your-username/Python-Helper.git
cd Python-Helper

# Install dependencies
pip install -r requirements.txt

# Run an example
python examples/file_operations_example.py

Basic Usage

# Import the helpers you need
from python_helpers.file_ops import ensure_directory, write_json
from python_helpers.utilities import generate_password
from python_helpers.data_processing import clean_data

# Create a directory and save some data
data_dir = ensure_directory("my_project/data")
config = {"api_key": generate_password(32), "version": "1.0"}
write_json(config, data_dir / "config.json")

# Clean messy data
raw_data = [{"name": " John ", "age": "", "score": "85"}]
clean_records = clean_data(raw_data)
print(clean_records)  # [{"name": "John", "score": "85"}]

📁 Project Structure

Python-Helper/
├── 📦 python_helpers/     # Core library modules
│   ├── file_ops/          # File & directory operations
│   ├── data_processing/   # Data cleaning & analysis
│   ├── web_scraping/      # HTTP requests & HTML parsing
│   ├── automation/        # Task automation & scheduling
│   └── utilities/         # General-purpose utilities
├── 📜 scripts/            # Ready-to-use practical scripts
├── 🎯 examples/           # Usage examples & demonstrations
├── 📚 learning/           # Tutorials & educational content
├── 🧪 tests/             # Comprehensive test suite
└── 📖 docs/              # Detailed documentation

🎓 Learning Path

For Beginners:

1. Start Here: Run python examples/file_operations_example.py
2. Learn by Example: Explore the examples/ directory
3. Practice: Try the tutorials in learning/tutorials/
4. Build Something: Work on projects in learning/projects/

For Experienced Developers:

1. Browse the API: Check out docs/README.md for full documentation
2. Use in Projects: Install with pip install -e . for development
3. Extend: Add your own modules and utilities
4. Contribute: Submit pull requests with improvements

🛠️ Available Modules

Module	Purpose	Key Functions
file_ops	File operations	ensure_directory, safe_copy, read_json, write_json
data_processing	Data manipulation	clean_data, group_by, calculate_stats, csv_to_dict
web_scraping	Web scraping	safe_request, parse_html, extract_links, download_file
automation	Task automation	run_command, schedule_task, backup_files, monitor_directory
utilities	General utilities	generate_password, hash_string, validate_email, format_bytes

📋 Quick Examples

File Operations

from python_helpers.file_ops import find_files, get_file_info

# Find all Python files
py_files = find_files(".", "*.py")

# Get detailed file information
for file in py_files:
    info = get_file_info(file)
    print(f"{info['name']}: {info['size']} bytes")

Data Processing

from python_helpers.data_processing import group_by, calculate_stats

employees = [
    {"name": "John", "dept": "Engineering", "salary": 75000},
    {"name": "Jane", "dept": "Engineering", "salary": 80000},
    {"name": "Bob", "dept": "Marketing", "salary": 65000}
]

# Group by department
dept_groups = group_by(employees, "dept")

# Calculate salary statistics
salaries = [emp["salary"] for emp in employees]
stats = calculate_stats(salaries)
print(f"Average salary: ${stats['mean']:,.2f}")

Web Scraping

from python_helpers.web_scraping import safe_request, parse_html, extract_links

# Fetch and parse webpage
response = safe_request("https://example.com")
if response:
    soup = parse_html(response.text)
    links = extract_links(soup)
    print(f"Found {len(links)} links")

Automation

from python_helpers.automation import backup_files, cleanup_old_files

# Backup important files
backup_files(["config.json", "data.csv"], "backups/")

# Clean up old log files
cleanup_old_files("logs/", days_old=7, pattern="*.log")

Utilities

from python_helpers.utilities import generate_password, format_bytes, time_ago
from datetime import datetime, timedelta

# Generate secure password
password = generate_password(16, include_symbols=True)

# Format file sizes
print(format_bytes(1024 * 1024))  # "1.0 MB"

# Human-readable time differences
old_time = datetime.now() - timedelta(hours=2)
print(time_ago(old_time))  # "2 hours ago"

🧪 Testing

# Run all tests
pytest

# Run with coverage
pytest --cov=python_helpers

# Run specific test categories
pytest -m unit          # Unit tests only
pytest -m integration   # Integration tests only

🤝 Contributing

We welcome contributions! Here's how you can help:

1. Report Issues: Found a bug? Create an issue
2. Suggest Features: Have an idea? We'd love to hear it
3. Add Utilities: Write new helper functions
4. Improve Documentation: Help make things clearer
5. Write Tests: Help us maintain quality

Development Setup

# Install in development mode
pip install -e .[dev]

# Install pre-commit hooks (optional)
pre-commit install

# Run tests before committing
pytest

🎯 Use Cases

This library is perfect for:

• Learning Python: Understand practical coding patterns
• Rapid Prototyping: Get common tasks done quickly
• Automation Scripts: Build reliable automation tools
• Data Processing: Handle CSV files and data cleaning
• File Management: Organize and process files safely
• Web Scraping Projects: Extract data from websites
• System Administration: Automate system tasks

📖 Documentation

For detailed documentation, examples, and tutorials:

• API Reference: See docs/README.md
• Examples: Browse the examples/ directory
• Tutorials: Check learning/tutorials/
• Projects: Try learning/projects/

📄 License

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

🌟 Star This Repo!

If you find this library helpful, please give it a star! It helps others discover the project and motivates continued development.

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Happy Coding! 🚀

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Python-Helper

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