emr-notebooks-magics
Jupyter Magics for EMR Notebooks.
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires S3-FUSE or Goofys installed on EMR cluster via bootstrap action; requires Amazon EMR Notebooks environment; kernel restart needed after installation.
- 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 · maintenance · safety
permissive license (permissive) — Licensed under Apache-2.0 (permissive), allowing commercial and private use with minimal restrictions.
last release 2023-06-30 (1141 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 1,981,563 downloads/mo, #3,387 on PyPI
Alternatives
Verify before relying
# 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- 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).
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 on this page. Verify before relying on it.
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
emr-notebooks-magics on PyPI
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.
Requires S3-FUSE or Goofys installed on EMR cluster via bootstrap action; requires Amazon EMR Notebooks environment; kernel restart needed after installation.
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.ipynbVerify 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 | permissive license permissive |
| Python support | Not specified |
| Install friction | High. Source build required |
| Runtime dependencies | None |
| Maintenance | Abandoned 1,141 days since the last release |
| First released | |
| Downloads | 1,981,563 / month, #3,387 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseNatural Language :: English |
Evidence: emr-notebooks-magics-0.2.4.tar.gz
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