useful-types

library0.2.1pypypiunverified

useful-types is a Python library offering a collection of common type aliases and protocols to reduce boilerplate in projects. It aims to provide frequently used type definitions, such as JSON-related types. The library's types are not specially handled by type checkers, and users are encouraged to vendor them if they wish to avoid a direct dependency. It is currently at version 0.2.1 and maintains an active development cadence with occasional updates to type definitions.

type-stubs

pip install useful-types

github ↗package ↗changelog ↗

INSTALL

IMPORT

SIG · USEFUL-TYPES

useful-types

type-stubspythonv0.2.1

Install

1.6s avg

Import

—

Disk

16MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.2.1 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.920 runs

installs and imports cleanly · install 0.0s · import 0.000s · 18.1MB

glibc

py 3.10–3.920 runs

installs and imports cleanly · install 1.6s · import 0.000s · 19MB

16MB installed

● package 16MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

JSONDict

✓ from useful_types import JSONDict

✗ from useful_types import JSONDict

This quickstart demonstrates the use of `JSONDict` and `JSONType` to define and process data conforming to JSON structures. It shows how to type-hint complex nested JSON data and perform basic operations while maintaining type safety.

from useful_types import JSONDict, JSONType def process_json_data(data: JSONType) -> JSONType: if isinstance(data, dict): if 'id' in data and isinstance(data['id'], str): print(f"Processing record with ID: {data['id']}") return {k: v for k, v in data.items() if k != 'private_field'} elif isinstance(data, list): return [process_json_data(item) for item in data] return data example_dict: JSONDict = { "name": "Alice", "age": 30, "isStudent": False, "courses": ["Math", "Science"], "address": {"street": "123 Main St", "zip": 90210}, "private_field": "secret" } example_list: JSONType = [1, "hello", True, None, example_dict] processed_data = process_json_data(example_list) print(f"Original: {example_list}") print(f"Processed: {processed_data}")

Debug

Known issues

gotchaThe library explicitly states that its types are not specially handled by type checkers and encourages users to 'vendor' (copy) them into their own projects if they prefer not to take on a direct dependency. This is a design philosophy choice, not a technical limitation.

fix

Consider whether you want to include 'useful-types' as a dependency or copy the specific type definitions you need directly into your codebase, as recommended by the library author. Either approach is supported.

affects: All versions

gotchaThe library guarantees support on `mypy 1.4` and `pyright 1.1.314` or higher. Using older versions of these type checkers or alternative type checkers (e.g., Pyright, Pylance, etc.) might lead to unexpected type-checking behavior or errors, as the types might rely on newer type checker features.

fix

Ensure your project's type checker (mypy or pyright) meets or exceeds the stated minimum versions. If using another type checker, verify compatibility by running your type checks against the library's types.

affects: <=0.2.1

Upgrade

Version history

0.2.1latest on PyPI · released Apr 20, 2024

Audit

Dependencies

No dependency data recorded yet.

Agent activity

47 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/hauntsaninja/useful_types ↗

packagehttps://pypi.org/project/useful-types/ ↗

changeloghttps://github.com/hauntsaninja/useful_types/blob/main/CHANGELOG.md ↗