threaded

What it is and what it does

threaded is a decorator library that wraps ordinary Python functions to run them concurrently using standard library primitives—ThreadPoolExecutor, threading.Thread, or asyncio.Task. Instead of writing boilerplate like `loop.create_task()` or `thread_pool.submit()` every time you want to run a function concurrently, you decorate it once and call it normally; the decorator handles the concurrency setup and returns a future or thread object. It supports Python 3.8 through 3.12 on CPython and PyPy, with no external dependencies beyond the standard library.

The library provides three main decorators: ThreadPooled (submits to a thread pool with configurable worker count), Threaded (wraps in a threading.Thread with optional daemon and auto-start modes), and AsyncIOTask (wraps in an asyncio.Task). Each decorator can be configured with custom event loops or loop-extraction logic for integration with existing async code. The thread pool can be shut down explicitly during application shutdown.

Use it for

• Offload blocking I/O operations (file reads, network calls) to a thread pool without writing submit/future boilerplate
• Launch long-running background tasks as daemon threads with a single decorator instead of manual Thread instantiation
• Wrap synchronous functions to run as asyncio tasks within an event loop for mixed sync/async codebases
• Reduce copy-paste of concurrent.futures or threading setup code across a codebase by standardizing on decorators
• Integrate blocking library calls into async code by scheduling them on a thread pool executor

Worth the install?

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Install

threaded on PyPI

Before you install

Low install friction with no runtime dependencies. Maintenance is aging—last release was 996 days ago—but the repository remains active with a recent commit on 2026-01-12, suggesting occasional updates rather than abandonment.

Requires Python 3.8 or later; asyncio integration requires an active event loop when using AsyncIOTask or ThreadPooled with loop_getter.

License in practice

Licensed under Apache-2.0 (permissive), allowing commercial and private use with minimal restrictions; suitable for most projects without license compatibility concerns.

Quickstart

pip install threaded

import threaded

@threaded.ThreadPooled
def blocking_task():
    return "result"

future = blocking_task()
import concurrent.futures
concurrent.futures.wait([future])

Package facts

Evidence: threaded-4.2.0-py3-none-any.whl

Tags

More Python Modules packages

See also aioprocessing · unsync · kthread · pypeln · snapshot-restore-py · multitasking · Pebble · func-timeout · janus · requests-futures