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When stdlib isn't enough.

Project description

Apathetic Python Utils ⚙️

CI License: MIT-a-NOAI Discord

📘 Roadmap · 📝 Release Notes

Grab bag of helpers for Apathetic projects.
When stdlib just isn't enough.

Apathetic Python Utils provides a lightweight, dependency-free collection of utility functions designed for CLI tools. It includes helpers for file loading, path manipulation, system detection, text processing, type checking, pattern matching, and more.

[!NOTE] Heads up: the AI cooked dinner. It's edible, but watch your step.
Detailed bug reports welcome.

Quick Start

from apathetic_utils import load_jsonc, load_toml, is_ci, detect_runtime_mode
from pathlib import Path

# Load configuration files
config = load_jsonc(Path("config.jsonc"))
pyproject = load_toml(Path("pyproject.toml"))

# Detect environment
if is_ci():
    print("Running in CI")

# Detect runtime mode (installed, standalone, zipapp, frozen)
mode = detect_runtime_mode("my_package")
print(f"Running in {mode} mode")

Installation

# Using poetry
poetry add apathetic-utils

# Using pip
pip install apathetic-utils

Documentation

📚 Full Documentation →

For installation guides, API reference, examples, and more, visit our documentation website.

Features

  • 🪶 Zero dependencies — Uses only Python's standard library (except apathetic-logging for logging)
  • 📁 File loading — Load TOML and JSONC files with comment support
  • 🛤️ Path utilities — Cross-platform path normalization and glob handling
  • 🔍 Pattern matching — Portable glob pattern matching with recursive ** support
  • 🧪 System detection — Detect CI environments, pytest execution, and runtime modes
  • 📝 Text processing — Pluralization and error message cleanup utilities
  • 🔧 Type utilities — Safe isinstance checks for TypedDicts and generics
  • 🎯 CLI-friendly — Designed with command-line applications in mind

⚖️ License

You're free to use, copy, and modify the library under the standard MIT terms.
The additional rider simply requests that this project not be used to train or fine-tune AI/ML systems until the author deems fair compensation frameworks exist.
Normal use, packaging, and redistribution for human developers are unaffected.

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