# ryfeus/lambda-packs

Precompiled packages for AWS Lambda

Repository: https://github.com/ryfeus/lambda-packs
Canonical: https://ross.abutalabs.com/products/lambda-packs
Language: Python
License: MIT
License Family: permissive
Topics: aws-lambda, phantomjs, serverless, aws, tensorflow, keras, numpy, pandas, tesseract, sklearn, skimage, wrk, opencv, pillow, selenium, python, lightgbm, spacy, hdf, pytorch
Last push: 2023-11-09T16:24:28+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": 3605, "days_push": 1028, "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 1116, forks 235 (observed 2026-08-28T04:03:38.804246+00:00)

## What it is
A collection of precompiled Python packages bundled as ZIP files ready to upload to AWS Lambda, covering libraries like TensorFlow, PyTorch, OpenCV, Selenium/PhantomJS, spaCy, and pandas. It lets developers use heavy dependencies that are difficult to build in Lambda's constrained environment without compiling them locally.

## Use cases
- deploy python packages with c extensions to aws lambda
- run selenium headless browser scraping on lambda
- run tensorflow or pytorch inference in a lambda function
- do image processing with opencv and pillow in serverless functions
- perform load testing by running many lambdas in parallel with wrk
- parse html with lxml and requests on lambda
- use spacy or sklearn in aws lambda without building packages

## When to choose
- you need native-dependency-heavy Python libraries on AWS Lambda and don't want to compile them yourself
- you want quick serverless demos for scraping, ML inference, or load testing
- you're on a Lambda runtime where prebuilt wheels are hard to obtain

## When to avoid
- you use recent Lambda runtimes (Python 3.9+) where many packages are available via pip or Lambda layers
- you need actively maintained, up-to-date library versions
- you're not deploying to AWS Lambda

## Facets
- artifact type: dataset
- maturity: maintenance
- function: web-scraping, machine-learning, load-testing, image-processing, nlp, ocr, developer-tools
- domain: cloud-computing, web-development, machine-learning, developer-tools
- platform: cloud, python, serverless
- tags: aws-lambda, precompiled-packages, phantomjs, selenium, tensorflow, pytorch, opencv, pandas, numpy, spacy, tesseract, lightgbm, serverless-deployment, zip-packages, serverless, automation

## Member repositories
- ryfeus/lambda-packs (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:38.804246+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 2026-08-30T06:41:59.605120+00:00, confidence not recorded.
  - readme: https://github.com/ryfeus/lambda-packs (fetched 2026-08-28T04:03:38.804246+00:00, sha 38ece0053a45)
- Data as of 2026-08-30T08:39:29.467469+00:00.