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A comprehensive Python utility library for general-purpose and specialised tasks

Project description

pygenutils

pygenutils is a comprehensive Python utilities package designed to provide a wide range of general-purpose tools for data manipulation, string handling, time operations, and system interactions. It serves as a collection of commonly needed utilities for Python development.

Features

  • String Operations:
    • Advanced string manipulation
    • Text formatting and parsing
    • String pattern matching
    • Text transformation utilities
  • Time Handling:
    • Date and time calculations
    • Calendar operations
    • Time formatting
    • Program execution timing
    • Countdown functionality
  • Data Structures:
    • Array and list manipulation
    • Data pattern matching
    • Mathematical operations
    • Data conversion utilities
  • System Operations:
    • Operating system interactions
    • Process management
    • System information retrieval
  • Audio and Video:
    • Media file handling
    • Format conversion utilities
  • Number Systems:
    • Base conversion utilities
    • Number system operations
  • Set Operations:
    • Interval handling
    • Set manipulation
  • Dictionary Operations:
    • Dictionary manipulation
    • Key-value operations

Installation Guide

Dependency Notice

This package has minimal external dependencies and is designed to be lightweight. Most functionality works with Python's standard library.

Installation Instructions

Install the package using pip:

pip install pygenutils

Package Updates

To stay up-to-date with the latest version of this package, simply run:

pip install --upgrade pygenutils

Project Structure

The package is organised into several specialised modules:

  • strings/: String manipulation utilities

    • string_handler.py: Core string operations
    • text_formatters.py: Text formatting utilities
  • time_handling/: Time and date operations

    • date_and_time_utils.py: Date/time calculations
    • time_formatters.py: Time formatting
    • calendar_utils.py: Calendar operations
    • program_snippet_exec_timers.py: Execution timing
    • countdown.py: Countdown functionality
  • arrays_and_lists/: Data structure operations

    • data_manipulation.py: Data handling
    • patterns.py: Pattern matching
    • conversions.py: Data conversion
    • maths.py: Mathematical operations
  • operative_systems/: System operations

    • System interaction utilities
    • Process management tools
  • audio_and_video/: Media handling

    • Media file operations
    • Format conversion
  • number_bases/: Number system operations

    • Base conversion utilities
  • sets_and_intervals/: Set operations

    • Interval handling
    • Set manipulation
  • dictionaries/: Dictionary operations

    • Dictionary manipulation tools

For detailed version history and changes, please refer to:

  • CHANGELOG.md: Comprehensive list of changes for each version
  • VERSIONING.md: Versioning policy and guidelines

Usage Examples

String Operations

from pygenutils.strings import string_handler, text_formatters

# String manipulation
modified_str = string_handler.modify_obj_specs("example.txt", "new")
formatted_text = text_formatters.print_format_string("Hello, {name}!", name="World")

Time Operations

from pygenutils.time_handling import date_and_time_utils, time_formatters

# Date calculations
next_week = date_and_time_utils.add_days_to_date("2024-03-20", 7)
formatted_time = time_formatters.format_time_string("14:30:00", "HH:MM")

Array Operations

from pygenutils.arrays_and_lists import data_manipulation, patterns

# Data manipulation
processed_data = data_manipulation.process_array([1, 2, 3, 4, 5])
matched_pattern = patterns.find_pattern([1, 2, 3, 1, 2, 3], [1, 2, 3])

Best Practices

  1. Module Organisation:

    • Use appropriate sub-packages for related functionality
    • Keep utility functions focused and single-purpose
    • Document all public functions and classes
  2. Performance Considerations:

    • Optimise frequently used operations
    • Use appropriate data structures
    • Consider memory usage for large operations
  3. Error Handling:

    • Implement proper error checking
    • Provide meaningful error messages
    • Handle edge cases appropriately

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