{"categories":[{"label":"Distributed Computing","url":"https://skillfed.io/packages/category/system-distributed-computing"}],"enrichment":{"capability":"Provides iPython magics for Amazon EMR Notebooks to mount S3 workspaces, generate presigned S3 download URLs, and execute notebooks in the background.","skillfed_tags":["aws-emr","jupyter-magics","abandoned"],"use_cases":["Mount S3 workspace directories onto an EMR cluster instance to access files as if they were local.","Generate presigned URLs for S3 objects to enable downloads directly from Jupyter notebooks.","Execute long-running notebooks asynchronously in the background while preserving output logs.","Integrate S3 storage workflows into EMR Notebook-based data analysis pipelines."],"what_it_does":"emr-notebooks-magics is a collection of iPython magics designed specifically for Amazon EMR Notebooks. It extends Jupyter with three main commands: one to generate presigned URLs for S3 objects, one to mount S3 workspaces locally using FUSE-based filesystems (S3-FUSE or Goofys), and one to execute other notebooks asynchronously in the background.\n\nThe package is tightly coupled to the EMR Notebooks environment and requires external system dependencies to be installed via EMR cluster bootstrap actions before the package itself can function. Installation happens either through an EMR step or directly within a Jupyter notebook, but a kernel restart is required after installation. The project is no longer actively maintained, with the last release over three years ago.","worth_installing":"No. The package is abandoned (1141 days since last release) with no active maintenance, and it requires manual system-level dependency management (S3-FUSE or Goofys) on each EMR cluster. For new EMR Notebook projects, consider whether AWS has released newer tooling or whether direct boto3 S3 operations better suit your needs. If you are already using this package in a stable environment, proceed cautiously and monitor for security issues independently."},"id":"emr-notebooks-magics","links":{"html":"https://skillfed.io/packages/emr-notebooks-magics","md":"https://skillfed.io/packages/emr-notebooks-magics.md","pypi":"https://pypi.org/project/emr-notebooks-magics/"},"maintenance":{"status":"abandoned"},"meta":{"latest_release":"2023-06-30","license_spdx":null,"license_treatment":"permissive","name":"emr-notebooks-magics","python_support":"unspecified","summary":"Jupyter Magics for EMR Notebooks."},"popularity":{"monthly_downloads":1981563,"position":3387,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.2.4"}