---
id: emr-notebooks-magics
version: "0.2.4"
license: unclear
license_treatment: permissive
maintenance: abandoned
---

# emr-notebooks-magics — Jupyter Magics for EMR Notebooks.

License: permissive · Maintenance: abandoned · Downloads: 2.0M/mo

## What it is and 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.

The 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 The project is no longer actively maintained, with the last release over three years ago.

Use it for:

- 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.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides iPython magics for Amazon EMR Notebooks to mount S3 workspaces, generate presigned S3 download URLs, and execute notebooks in the background.

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.

## Install

pip install emr-notebooks-magics
uv add emr-notebooks-magics
poetry add emr-notebooks-magics

## Installing emr-notebooks-magics

Before you install: High install friction: requires system-level dependencies (S3-FUSE or Goofys) installed via EMR bootstrap actions before the package can be used. Package is abandoned as of 1141 days since last release, with no active maintenance.

License in practice: Licensed under Apache-2.0 (permissive), allowing commercial and private use with minimal restrictions.

Quickstart:

# Install via Jupyter in EMR Notebook
%pip install emr-notebooks-magics

# After kernel restart, use magics:
%generate_s3_download_url s3://my_bucket/path/to/object
%mount_workspace_dir .
%execute_notebook notebook_name.ipynb

Requires S3-FUSE or Goofys installed on EMR cluster via bootstrap action; requires Amazon EMR Notebooks environment; kernel restart needed after installation.

Verify before relying:

- Current compatibility with recent EMR Notebook versions, given 1141-day gap since last release.
- Whether S3-FUSE and Goofys dependencies remain maintained and secure.
- Python version support (listed as unspecified in metadata).

## Package facts

- License: not declared (permissive)
- Python support: unspecified
- Install friction: high
- Maintenance: abandoned
- Downloads: 2.0M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

emr notebook magics, jupyter s3 mount, aws emr notebooks, s3 workspace access, emr notebook utilities, aws-emr, jupyter-magics, abandoned

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