Skip to main content

Jupyter Notebook tracing/reproduction using ReproZip

Project description

ReproZip is a tool aimed at simplifying the process of creating reproducible experiments from command-line executions, a frequently-used common denominator in computational science. It tracks operating system calls and creates a package that contains all the binaries, files and dependencies required to run a given command on the author’s computational environment (packing step). A reviewer can then extract the experiment in his environment to reproduce the results (unpacking step).


This package provides tracing and reproduction of Jupyter notebooks, allowing one to pack all the libraries and data used in their notebook to allow anyone to re-run it easily.

You can use it from the command-line:

# Trace & pack
$ reprozip-jupyter trace mynotebook.ipynb
$ reprozip pack notebook_environment.rpz

# Unpack and reproduce
$ reprounzip docker setup notebook_environment.rpz /tmp/notebook
$ reprozip-jupyter run /tmp/notebook

Or you can pack directly from the Jupyter notebook interface, if you enable the extension:

$ jupyter nbextension install --py reprozip_jupyter --user
$ jupyter nbextension enable --py reprozip_jupyter --user
$ jupyter serverextension enable --py reprozip_jupyter --user

Please refer to reprozip and reprounzip for more information.

Additional Information

For more detailed information, please refer to our website, as well as to our documentation.

ReproZip is currently being developed at NYU. The team includes:

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for reprozip-jupyter, version 0.3
Filename, size File type Python version Upload date Hashes
Filename, size reprozip_jupyter-0.3-py3-none-any.whl (12.5 kB) File type Wheel Python version py3 Upload date Hashes View
Filename, size reprozip-jupyter-0.3.tar.gz (9.5 kB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page