multitasking
Non-blocking Python methods using decorators
Decision gist · record as of 2026-08-14
Yes. Low install friction, no dependencies, active maintenance, permissive license, and zero known vulnerabilities make it a safe choice. Use it if you want to parallelize I/O-bound work without learning asyncio or threading APIs. Not suitable if you need fine-grained control over task results or complex async patterns—consider asyncio or concurrent.futures for those cases.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low friction: pure Python wheel with no runtime dependencies.
- Active maintenance since 2016, last commit 2026-04-23, and marked Production/Stable.
- No known vulnerabilities.
License · maintenance · safety
Apache (permissive) — Apache License (permissive): you can use, modify, and distribute freely in commercial and private projects with minimal restrictions.
last release 2026-04-23 (113 days) · last repo commit 2026-04-23 · 235 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 23,060,727 downloads/mo, #958 on PyPI
Alternatives
Verify before relying
import multitasking
import time
@multitasking.task
def fetch_data(item_id):
time.sleep(1)
return f"Data {item_id}"
for i in range(5):
fetch_data(i)
multitasking.wait_for_tasks()- Whether thread pool size scales automatically or requires manual configuration for optimal performance in production
- Whether the decorator preserves return values or if task results must be captured via side effects
- Compatibility with async/await syntax or whether it is threading-only
What it is and what it does
MultiTasking is a lightweight decorator-based library that lets you run Python functions concurrently without writing threading or multiprocessing boilerplate. You mark a function with @multitasking.task, call it multiple times in a loop, and the library handles spawning and managing worker threads or processes in the background. It's designed for I/O-bound workloads—web scraping, API calls, database operations—where you want to avoid blocking while waiting for I/O to complete.
The library provides pool management (create separate thread or process pools for different workload types), task monitoring (check active and completed tasks), and signal handling (gracefully shut down or wait for tasks on Ctrl-C). You can tune concurrency by setting max threads, choosing between threading and multiprocessing engines, and creating specialized pools for different job types. It has no external dependencies and supports a wide range of Python versions.
Use it for
- Fetch multiple URLs or API endpoints concurrently without blocking on each request
- Process large datasets in parallel batches (e.g., database inserts or file transformations)
- Run I/O-heavy operations like web scraping across many pages simultaneously
- Execute CPU-intensive tasks using process pools to bypass Python's GIL
- Monitor and control concurrent background jobs with built-in task tracking
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Low install friction, no dependencies, active maintenance, permissive license, and zero known vulnerabilities make it a safe choice. Use it if you want to parallelize I/O-bound work without learning asyncio or threading APIs. Not suitable if you need fine-grained control over task results or complex async patterns—consider asyncio or concurrent.futures for those cases.
Install
multitasking on PyPI
Before you install
Low friction: pure Python wheel with no runtime dependencies. Active maintenance since 2016, last commit 2026-04-23, and marked Production/Stable. No known vulnerabilities.
License in practice
Apache License (permissive): you can use, modify, and distribute freely in commercial and private projects with minimal restrictions.
Quickstart
import multitasking
import time
@multitasking.task
def fetch_data(item_id):
time.sleep(1)
return f"Data {item_id}"
for i in range(5):
fetch_data(i)
multitasking.wait_for_tasks()Verify before relying
- Whether thread pool size scales automatically or requires manual configuration for optimal performance in production
- Whether the decorator preserves return values or if task results must be captured via side effects
- Compatibility with async/await syntax or whether it is threading-only
Package facts
| License | Apache permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 113 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 23,060,727 / month, #958 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: Python :: 2.7Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.5Programming Language :: Python :: 3.6Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Software Development :: LibrariesTopic :: Software Development :: Libraries :: Python Modules |
Evidence: multitasking-0.0.13-py3-none-any.whl
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