Python on The Carpentries

Instats Pilot: What and Why? (and a Call for Helpers)

Wed, 25 Mar 2026 00:00:00 +0000

At the end of 2025, we began exploring a partnership with Instats to offer recorded Carpentries workshop sessions. Instats is a mission-driven organisation that focuses on delivering a diverse range of seminars that inspire high-quality, ethical, and impactful research.

Why are we partnering with Instats?

The goal of working with Instats is to create more opportunities for anyone who can’t attend in-person or locally hosted workshops due to availability in their region, and circumstances such as time zone conflicts. An added benefit is the ability for all learners to engage with our lessons at their own pace.

Updating our Lesson Setup Instructions

Wed, 12 Mar 2025 00:00:00 +0000

The Lesson Setup Instructions Task Force was established in August 2024 to review existing setup instructions for Data Carpentry, Library Carpentry, and Software Carpentry lessons and decide where and how these instructions should be updated. Members of the task force considered a wide range of options for installing Bash, Git, Python, and R, and engaged in many constructive discussions. The task was challenging, and the “best” option was often difficult to identify.

Library Carpentry Curriculum Advisory Committee Approves a Major Update to the LC Python Lesson

Wed, 26 Jun 2024 00:00:00 +0000

Introduction

We are excited to announce that the Library Carpentry Curriculum Advisory Committee (LC-CAC) has approved a major update to the Python Intro for Libraries lesson.

The lesson demonstrates how to use Python to clean, analyse, and visualise library usage data, providing an introduction to reproducible workflows in Python for library and information workers. While the lesson repurposes some elements from the previous Library Carpentry Introduction to Python, it is a major overhaul that includes a new library-specific dataset, the use of JupyterLab instead of Spyder, and new episodes that use Pandas to tidy a dataset and Plotly to visualise data.

Incubator Lesson Spotlight: Interactive Data Visualizations in Python

Wed, 27 Apr 2022 00:00:00 +0000

The first virtual CarpentryConnect South Africa 2021 took place from 6 to 17 September. The event included 2 Carpentries workshops, 1 Carpentries instructor training event, 2 networking events, 1 learning session and 1 opening address.

The main goal of CarpentryConnect South Africa 2021 was to build capacity for workshops through instructor training and bring together newer and more experienced community members to share knowledge, network, develop new skills, and develop strategies for building strong local communities around digital and computational literacy in Africa.

Fourteen and Counting - People's Favorite Tools

Mon, 08 Jan 2018 00:00:00 +0000

This post originally appeared on the Software Carpentry website.

Thank you to all the people who have sent in short posts about their favourite tools. We are up to fourteen now, and the variety of tools is great to see. Finding out what other people use - and possibly more importantly - why they use it, and for what, is a great shortcut for researchers. There are a bewildering number of research tools around. Getting a tip from someone in your discipline, or from someone who is doing a similar task to you, can really help.

People's Favorite Tools

Wed, 29 Nov 2017 00:00:00 +0000

This post originally appeared on the Software Carpentry website.

A big thank you to everyone who has responded so far to the call for short posts about their favourite tools.

So far we have had Paula Martinez on R, with Bianca Peterson enthusiastically seconding, Jeff Oliver sharing his love of Git and GitHub, Kellie Ottoboni talking up IPython, and Thomas Arildsen on how the Jupyter Notebook facilitates his teaching. Juliane Schneider weighed in on the wonders of OpenRefine. Clifton Franklund likes RStudio, while Francesco Montanari is a fan of emacs.

My Favourite Tool: Jupyter Notebook

Sat, 28 Oct 2017 00:00:00 +0000

This post originally appeared on the Software Carpentry website.

My favorite tool is … the Jupyter Notebook.

One of my favourite tools is the Jupyter notebook. I use it for teaching my students scientific computing with Python.

Why I like it:

Using Jupyter with the plugin RISE, I can create presentations including code cells that I can edit and execute live during the presentation to demonstrate the various aspects of Python that I introduce. It is a very good compromise between running scripts and typing in the command prompt on the projector screen vs. just showing static slides with code.

My Favourite Tool: IPython

Fri, 27 Oct 2017 00:00:00 +0000

This post originally appeared on the Software Carpentry website.

My favorite tool is … IPython.

IPython is a Python interpreter with added features that make it an invaluable tool for interactive coding and data exploration. IPython is most commonly taught via the Jupyter notebook, an interactive web-based tool for evaluating code, but IPython can be used on its own directly in the terminal as a replacement for the standard Python interpreter.

Why I like it

You can run Unix commands directly in IPython. For instance, if you want to load a file from another directory, it is convenient to cd into the directory from within the IPython window.

Teaching Python to undergraduate geoscientists: A summary of our approaches and experiences over the years

Sat, 18 Jun 2016 00:00:00 +0000

This post originally appeared on the Software Carpentry website.

In 2010, a new course commenced at Imperial College London that aimed to teach undergraduate geoscience students how to program in Python. Over the course of five years (2010 to 2014 inclusive) our teaching methodology evolved significantly in response to student feedback and examination performance. The course lecturers (Gerard Gorman and myself, Christian Jacobs) along with several of our Teaching Assistants also undertook Software Carpentry instructor training which offered a fantastic pedagogical insight into how to effectively teach novices how to program. As a result, many of our teaching techniques were influenced by this which helped to greatly improve our course. In this blog post we summarise what we changed throughout the five years and why, in the hope that this will benefit other instructors currently offering, or planning to offer, an undergraduate computer programming course.

Designing a New Novice Python Lesson

Sun, 10 Apr 2016 00:00:00 +0000

This post originally appeared on the Software Carpentry website.

Last November, I volunteered to pull together a new full-day lesson on Python suitable for people with no previous programming experience. It has taken longer to come together than I expected, but that’s partly because I saw it as an opportunity to create a full-length example of the “backward” lesson design method we teach in the instructor training class.

What we have so far is in this GitHub repository, which is rendered at this site. We would be very grateful for input: if you think crucial topics have been left out, please say so, while if there’s stuff that could be removed or re-ordered, please say that as well.

Python Education Summit at PyCon 2016

Wed, 23 Mar 2016 00:00:00 +0000

This post originally appeared on the Software Carpentry website.

The Python Education Summit is a gathering of educators from all venues (school, colleges, universities, community workshops, online courses, government) that share interest and passion in teaching Python. It is an interesting opportunity for Software Carpentry instructors to get inspiration and tips from educators in completely different contexts.

Schedule

The Summit will take place at the Oregon Convention Center, same site of PyCon, on Sunday, May 29th, the 2nd day of the tutorials and the day before the main conference starts. It will run from 9am to 4:30pm.

A New Lesson on Testing

Sun, 22 Nov 2015 00:00:00 +0000

This post originally appeared on the Software Carpentry website.

Katy Huff has just posted a new lesson on testing and continuous integration with Python drawn in part from the book that she and Anthony Scopatz recently published. There's a lot of useful material in here, all of it tested in the classroom—please check it out.

Python Lesson Rewrite

Sun, 15 Nov 2015 00:00:00 +0000

This post originally appeared on the Software Carpentry website.

Recent analysis and introspection regarding Software Carpentry's Python lesson has led us to conclude that the lesson would benefit from a complete rewrite. The subcommittee on lesson development met twice to plan much about the new lessons (yes, that's plural). This post will describe our plans for the new lessons.

We're going to write two new Python lessons, one intended for students who are completely new to programming (the "novice" lesson), and another for students with some programming experience in any language (the "intermediate" lesson). Data Carpentry also targets new programmers so we'll be developing the new novice lesson in collaboration with DC, and both DC and SWC will use the lesson. We decided to use Gapminder data for both the novice and intermediate lessons in order to have a consistent experience and approachable, meaningful data (and because some lessons are already using it).

A Summary of Debriefing Feedback on Our Python Lesson

Thu, 08 Oct 2015 00:00:00 +0000

This post originally appeared on the Software Carpentry website.

Last month, we discussed results from a survey of how our instructors are teaching Python. We now have a summary of the feedback we've received in our bi-weekly debriefing meetings. The recurring themes are:

A greater choice of exercises and multiple choice questions would allow instructors to select domain specific examples and cater to varying levels of learner.
Some instructors added an explanation of the Jupyter notebook or Spyder IDE environments.
Some instructors added an explanation of basic Python datatypes before presenting the lessons.
Comments that there is too much material to fit into a workshop and that some sections seem rushed.
Request for a better explanation of the advantages of the Anaconda Distribution at the start of workshops and resources for post workshop learning.
Comments on presenters style were positive for funny and entertaining examples and negative for highly mathematical examples.

Feedback on Math with Python for Undergraduates

Fri, 21 Aug 2015 00:00:00 +0000

This post originally appeared on the Software Carpentry website.

Ian Hawke (who put together these notebooks on testing numerical code) is now putting together some Jupyter Notebooks to teach Python to first-year undergraduates in mathematics. He would be grateful for feedback, and we'd be grateful if you could give him some: we'll learn a lot about what we should teach from seeing what you think he should.

Prepping for the Python Lesson

Sun, 16 Aug 2015 00:00:00 +0000

This post originally appeared on the Software Carpentry website.

Inspired in part by Byron Smith's post about trimming our standard Python lesson, Christina Koch has written a post of her own about preparing to teach that lesson. She organizes her discussion around the motivating question that opens the lesson: "We have to accomplish a task (reading in data, analyzing and plotting it) by writing a program. How can we be smart about it?" It's a good read, as it shows how an experienced instructor thinks about (re-)designing teaching material. I hope her conclusions will feed into our discussion of how to revise the lesson (which we're going to decide in September).

Trimming the Python Lesson

Thu, 13 Aug 2015 00:00:00 +0000

This post originally appeared on the Software Carpentry website.

We are close to releasing a new version of our standard Python lesson that uses Python 3 instead of Python 2. As soon as that's done, we're going to warm up this discussion about fixing that lesson. One new contribution to that is this post by Byron Smith about how he trimmed the existing lesson. If you have other experiences or comments, please add them to this GitHub issue so that we can make decisions in September about what to include in Version 5.4 in November.

Fourth Python Lecture for Software Carpentry

Sun, 29 Jan 2006 00:00:00 +0000

This post originally appeared on the Software Carpentry website.

The fourth lecture on Python for the Software Carpentry course is now up. It covers sets, dictionaries, and a little bit of algorithmic complexity. Comments and criticisms are very welcome.

And if that's too serious for year, check out the web site for the Waterfall 2006 conference ;-).