If this stuff is over your head, please feel free to email/ask a question and I can try to help.Īt work I have to solve a very similar problem to scientific reproducibility I need to write code in one environment (a dev environment, or sometimes my laptop), and then have that code run in a production environment. And scientists are not professional programmers – understanding all of this stuff takes time and training often in short supply in academia (hence me blogging about boring stuff like creating environments and using github). Even if there are different standards of replicability, some code is quite a bit better than no code. What I am going to talk about in this post is to create an environment from the get-go that has the info necessary for others to replicate.įirst before I get to that though, I have come across people critiquing open science using essentially ‘the perfect is the enemy of the good’ arguments. This is more from a perspective of “I have this historical code, how can I try to replicate that researchers environment to get the same results”. We use pytest to run our test suite.DataColada have a recent blog about their groundhog package, intended to aid in reproducible science.

But once you open a PR to contribue your changes, pre-commit willīe automatically run at which point any errors that occur will need to be Optional (if you don’t install pre-commit you will still be able to commit

Strictly speaking using pre-commit on your local machine for commits is : : automatically running pre-commit during commit > git commitīeware that some of the tools run by pre-commit can potentially modify theįiles were modified it will terminate the commit giving you the opportunity to

: : manually running pre-commit on current changes : : note: by default pre-commit only runs on staged files > pre-commit run : : or start the Docker image in interactive mode : : > docker compose run interactive : : install pre-commit hooks for conda > cd ' %CONDA_PROJECT_ROOT% ' > pre-commit install : : reuse the development environment created above >.

Creating conda environment