# pybluez/pybluez

Bluetooth Python extension module

Repository: https://github.com/pybluez/pybluez
Canonical: https://ross.abutalabs.com/products/pybluez
Homepage: https://pybluez.readthedocs.io/
Language: HTML
License: GPL-2.0
License Family: copyleft
Last push: 2024-01-01T13:29:28+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 4190, "days_push": 975, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2409, forks 690 (observed 2026-08-28T04:06:44.309187+00:00)

## What it is
PyBluez is a Python extension module that lets Python code access the host machine's Bluetooth resources, including device discovery, SDP browsing, and RFCOMM/L2CAP connections. It supports Linux, Raspberry Pi, macOS, and Windows, but the project is no longer under development.

## Use cases
- scan for nearby bluetooth devices from python
- connect to a bluetooth device over rfcomm in python
- discover bluetooth low energy devices with python
- browse sdp services on a bluetooth device
- write a bluetooth l2cap client and server in python

## When to choose
- you need classic Bluetooth (RFCOMM/L2CAP/SDP) access from Python on Linux, macOS, or Windows
- you are maintaining legacy code already built on PyBluez

## When to avoid
- you need actively maintained software - the project is explicitly not under development
- you need Bluetooth Low Energy - prefer Bleak or Bless
- you need modern Python or current OS support guarantees

## Facets
- artifact type: library
- maturity: abandoned
- function: sdk, networking
- domain: developer-tools, cross-platform
- platform: windows, python
- tags: bluetooth, rfcomm, ble, python-extension, linux, macos

## Member repositories
- pybluez/pybluez (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:44.309187+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 2026-08-30T02:34:01.480881+00:00, confidence not recorded.
  - readme: https://github.com/pybluez/pybluez (fetched 2026-08-28T04:06:44.309187+00:00, sha bce73764c7e9)
- Data as of 2026-08-30T08:39:29.467469+00:00.