Description
I think it would be good to reestructure a bit our scripts, make sure all them have a header explaining what they do and how to use them, get rid of the ones not in use anymore (if any), and add the inventory of them to the contributing documentation, with what they do.
I'd move all them to ci/
(or if the name is not good rename it; sklearn uses build_tools
, numba buildscripts
). And inside, I'd have different directories (names can probably be improved):
ci/deps/
: conda requirements filesci/setup/
: scripts to create the environment, like downloading conda, building pandas...ci/testing/
: scripts to run the testsci/checks/
: scripts to validate code, likecode_checks.sh
orvalidate_docstrings.py
ci/release/
: scripts used during the releaseci/benchmarks/
: I'd move the asv files insideci
ci/config
: A directory for the yaml files with the CI configurationci/tools/
: scripts likemerge-pr.py
,find_commits_touching_func.py
...
It would probably be good to unify scripts, like script_single.sh
and script_multi.sh
that share 70% of the code, and have a single script with an argument run_tests.sh single
/ run_tests.sh multi
.
And it could also be useful to have a single script for things like the set up, so we have downloading and running conda in the same script, and it can be called all together, or just a part (like code_checks.sh
), so we can do setup_env.sh download
, setup_env.sh create
, or simply setup_env.sh
to do both.
@pandas-dev/pandas-core thoughts?