winiutils 2.2.32

A package with many utility functions

winiutils

A comprehensive Python utility library providing production-ready tools for data processing, concurrent execution, security, and object-oriented programming patterns.

Built with pyrig

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Table of Contents

• Features
• Installation
• Quick Start
• Documentation
• Modules
• Development
• License

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Features

• DataFrame Cleaning Pipeline — Extensible Polars DataFrame cleaning with an 8-step pipeline
• Concurrent Processing — Unified multiprocessing and multithreading with automatic resource optimization
• OOP Utilities — Metaclasses and mixins for automatic method logging and instrumentation
• Security Tools — OS keyring integration and AES-GCM encryption utilities
• Type Safety — Full type hints with strict mypy compliance
• Production Ready — Comprehensive test coverage and logging integration

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Installation

Using uv (recommended)

uv add winiutils

Using pip

pip install winiutils

From source

git clone https://github.com/Winipedia/winiutils.git
cd winiutils
uv sync

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Quick Start

DataFrame Cleaning

from winiutils.src.data.dataframe.cleaning import CleaningDF
import polars as pl

class UserDataCleaner(CleaningDF):
    """Clean and standardize user data."""

    USER_ID = "user_id"
    EMAIL = "email"
    SCORE = "score"

    @classmethod
    def get_rename_map(cls):
        return {cls.USER_ID: "UserId", cls.EMAIL: "Email", cls.SCORE: "Score"}

    @classmethod
    def get_col_dtype_map(cls):
        return {cls.USER_ID: pl.Int64, cls.EMAIL: pl.Utf8, cls.SCORE: pl.Float64}

    # ... implement other abstract methods

# Usage
cleaned = UserDataCleaner(raw_dataframe)
result = cleaned.df

Concurrent Processing

from winiutils.src.iterating.concurrent.multiprocessing import multiprocess_loop
from winiutils.src.iterating.concurrent.multithreading import multithread_loop

# CPU-bound tasks (multiprocessing)
def process_chunk(data, config):
    return heavy_computation(data, config)

results = multiprocess_loop(
    process_function=process_chunk,
    process_args=[(chunk,) for chunk in data_chunks],
    process_args_static=(config,),
    process_args_len=len(data_chunks),
)

# I/O-bound tasks (multithreading)
def fetch_url(url, headers):
    return requests.get(url, headers=headers)

results = multithread_loop(
    process_function=fetch_url,
    process_args=[(url,) for url in urls],
    process_args_static=(headers,),
    process_args_len=len(urls),
)

Automatic Method Logging

from winiutils.src.oop.mixins.mixin import ABCLoggingMixin

class MyService(ABCLoggingMixin):
    def process_data(self, data: list) -> dict:
        # Automatically logged with timing
        return {"processed": len(data)}

# Logs: "MyService - Calling process_data with (...) and {...}"
# Logs: "MyService - process_data finished with 0.5 seconds -> returning {...}"

Encryption with Keyring

from winiutils.src.security.keyring import get_or_create_aes_gcm
from winiutils.src.security.cryptography import encrypt_with_aes_gcm, decrypt_with_aes_gcm

# Get or create encryption key (stored in OS keyring)
aes_gcm, key = get_or_create_aes_gcm("my_app", "[e-mail]")

# Encrypt and decrypt
encrypted = encrypt_with_aes_gcm(aes_gcm, b"Secret message")
decrypted = decrypt_with_aes_gcm(aes_gcm, encrypted)

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Documentation

Full documentation is available in the docs folder:

• Data Processing — DataFrame cleaning pipeline and data structures
• Iterating & Concurrency — Parallel processing utilities
• OOP Utilities — Metaclasses and mixins
• Security — Encryption and keyring integration

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Modules

Module	Description
winiutils.src.data	DataFrame cleaning pipeline and data structure utilities
winiutils.src.iterating	Concurrent processing with multiprocessing and multithreading
winiutils.src.oop	Metaclasses and mixins for automatic method logging
winiutils.src.security	AES-GCM encryption and OS keyring integration

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Development

Setup

git clone https://github.com/Winipedia/winiutils.git
cd winiutils
uv sync --all-groups

Running Tests

uv run pytest

Code Quality

# Linting
uv run ruff check .

# Type checking
uv run mypy .

# Security scanning
uv run bandit -r winiutils/

Pre-commit Hooks

uv run pre-commit install
uv run pre-commit run --all-files

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Project Structure

winiutils/
├── src/                          # Main source code
│   ├── data/                     # Data processing
│   │   ├── dataframe/            # Polars DataFrame cleaning
│   │   └── structures/           # Dicts, text utilities
│   ├── iterating/                # Iteration utilities
│   │   └── concurrent/           # Multiprocessing & multithreading
│   ├── oop/                      # OOP patterns
│   │   └── mixins/               # Logging metaclass & mixin
│   └── security/                 # Security utilities
│       ├── cryptography.py       # AES-GCM encryption
│       └── keyring.py            # OS keyring integration
├── dev/                          # Development tools
│   ├── cli/                      # CLI subcommands
│   └── tests/fixtures/           # Test fixtures
├── docs/                         # Documentation
└── tests/                        # Test suite

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License

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

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Contributing

Contributions are welcome! Please ensure:

1. All tests pass (uv run pytest)
2. Code passes linting (uv run ruff check .)
3. Types are correct (uv run mypy .)
4. New features include tests
5. Documentation is updated for API changes