Skip to content

Workshop materials for PyCon 2018 workshop on reproducible analysis in Python

License

Notifications You must be signed in to change notification settings

trallard/ReproduciblePython

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

ReproduciblePython 🐍🐱‍👤

DOI

Binder

Materials associated with the PyCon 2018 workshop on reproducible analysis in Python.

The proposal for this workshop can be found in the proposal.md file.


Slides

🗒️ The slides for the workshop can be found here:


💬 Discussion

We will encourage discussions over the workshop, for this purpose we will be using an Etherpad. Click on the following link: https://public.etherpad-mozilla.org/p/ReproduciblePython


🗃️ The content

This material covers the basics of reproducible workflows in Python and is provided in the following sections:

  1. Setup: installation instructions for the workshop
  2. Setting up projects: advise on best practices to set up projects with a reproducibility-first approach
  3. Working with data: information on how to use, archive, and share data
  4. Processing data, workflows: producing automated wokrflows
  5. All things testing: introduction to testing of standalone scripts and Jupyter notebooks
  6. Making code public: how to share your code and being credited for it

🦄 Additional materials

These are complementary materials that you can follow at your own pace if you wanted to dive further.

Solutions

The solutions to the tutorial can be found in the solutions folder. Make sure to read the solutions README first

🖥️ What do I need for this workshop?

The installation instructions can be found at http://bitsandchips.me/ReproduciblePython/Setup.html

Acknowledgements

The development of this material was funded by OpenDreamKit, a Horizon2020 European Research Infrastructure project (676541) that aims to advance the open source computational mathematics ecosystem.

OpenDreamKit logo

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

About

Workshop materials for PyCon 2018 workshop on reproducible analysis in Python

Resources

License

Stars

Watchers

Forks

Packages

No packages published