# alex-sherman/deco

Repository: https://github.com/alex-sherman/deco
Canonical: https://ross.abutalabs.com/products/deco
Language: Python
License: MIT
License Family: permissive
Last push: 2021-11-03T22:59:55+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3800, "days_push": 1764, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1567, forks 49 (observed 2026-08-28T04:05:04.915833+00:00)

## What it is
DECO is a Python library that provides decorators for automatic parallelization of Python programs using multiprocessing.pool. It requires minimal code changes—just @concurrent and @synchronized decorators—to make use of all CPU cores.

## Use cases
- parallelize a slow python loop across all cpu cores
- speed up processing of large datasets with minimal code changes
- run independent function calls concurrently in python
- avoid manually managing multiprocessing pools
- parallelize grid computations like lat/lon processing

## When to choose
- you have a serial python program with slow, independent function calls
- you want near-zero-effort parallelism with just two decorators
- your functions take longer than ~1ms and arguments are pickleable

## When to avoid
- your functions run in under ~1ms, where overhead makes code slower
- you need fine-grained control over workers, queues, or async patterns
- arguments or return values cannot be pickled
- you need an actively developed library—last release was 2021

## Facets
- artifact type: library
- maturity: maintenance
- function: concurrency
- domain: developer-tools, performance
- platform: python, cross-platform
- tags: parallel-computing, decorators, multiprocessing, python-library

## Member repositories
- alex-sherman/deco (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:04.915833+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:58:59.786531+00:00, confidence not recorded.
  - readme: https://github.com/alex-sherman/deco (fetched 2026-08-28T04:05:04.915833+00:00, sha 31de59610f5d)
  - registry_pypi: https://pypi.org/pypi/deco/json (fetched 2026-08-29T11:28:52.514312+00:00, sha 1782f818a0aa)
- Data as of 2026-08-30T08:39:29.467469+00:00.