[Discuss] analyzing Git

People who teach or use Git may be interested in http://people.csail.mit.edu/sperezde/pre-print-oopsla16.pdf, which is reviewed at http://neverworkintheory.org/2016/09/30/rethinking-git.html: / Git is a widely used version control system that is powerful but complicated. Its

Re: [Discuss] analyzing Git

If you like the idea of Gitless it is a thing you can install and try yourself: http://gitless.com/ - Matt On Fri, Sep 30, 2016 at 10:55 AM W. Trevor King wrote: > On Fri, Sep 30, 2016 at 09:23:25AM -0400, Greg Wilson wrote: > > > Based on this analysis, we designed a

Re: [Discuss] analyzing Git

On Fri, Sep 30, 2016 at 09:23:25AM -0400, Greg Wilson wrote: > > Based on this analysis, we designed a reworking of Git (called > > Gitless) that attempts to remedy these flaws. When Git-wrappers have come up on this list in in the past, the balance has been between the wrapper APIs (which are

Re: [Discuss] Defensive Programming with R

Hi Raniere - I think it isn't a part of the materials because it's a bit advanced for the usual audience level. But that's not to say it wouldn't be nice to have. I imagine such a lesson could intro the base assertion functions like `stopifnot()` and also Hadley's testthat package. PRs

Re: [Discuss] Defensive Programming with R

I agree with Naupaka that it is a bit advanced. However, the package `testthat` is not for defensive programming per se, but for unit tests. For defensive programming specifically there is the `assertive` and `assertr` packages. However, unlike Python, the facilities for defensive programming are

Re: [Discuss] Defensive Programming with R

I like the idea of keeping the lessons closer together as asked by Raniere, and in fact I think software carpentry workshops is aimed to teach good practices than data and statistically analysis (even though it may be what drives the people to join the workshop). Last week we did our first

Re: [Discuss] Defensive Programming with R

Hello, My approach is quite opposite to Luke's. I mostly do exploratory "data analysis at an individual researcher/team level" precisely. I use knitr/R Markdown dynamic reports (think Jupyter notebooks, for all the Pythonistas out there). At this (exploratory) stage, I don't do testing per se.

Re: [Discuss] Data on lessons for self-learners

Thanks for starting this discussion, Dan. In developing the semester-long biology course for Data Carpentry [1], we specifically included self-learners in our approach to organizing the materials. We have a very clear starting point for self-learners that is accessible from the home page [2].