[SciPy-Dev] git on windows (was: scipy.stats)
Tue Jun 1 22:38:21 CDT 2010
On Tue, Jun 1, 2010 at 6:14 PM, Matthew Brett <email@example.com> wrote:
>> My main problem with git was the treatment of the file system, and I
>> find it much easier to work with separate branches as in bzr or
> Yes, it is true that the git lightweight branch model takes some time
> to get used to. My experience is that it's quick to get used to the
> git way, and once I did, it was a large relief to get rid of all those
> branch directories when we switched, but I understand that it is a
> I am sure you know this, but you can replicate the heavyweight
> branches of hg and bzr with:
> # initial git clone of 'trunk'
> git clone git://github.com/nipy/nipy.git
> # make a heavyweight branch
> git clone nipy my-nipy-branch
> # push somewhere
> # First add repo for the branch via github interface, then
> cd my-nipy-branch
> git remote add origin firstname.lastname@example.org:matthew-brett/my-nipy-branch.git
> git push origin master
However, I think this works only with a remote remote, github or similar
When I looked at bzr vs hg vs git, I also thought about my private
use, where I didn't find a way to compare across branches in separate
My work style in statsmodels is similar to the mailing list reference
that Fernando gave. Mainly I have many uncommitted files in each
branch, test scripts, examples scripts, quick checks whether a rewrite
would work, or R and matlab files. None of it I want to commit to the
repository, but have available when I work on it again.
> I think you'd agree that it's not a windows / unix difference though.
> I'd agree it is a larger conceptual leap from svn to git than it is
> from svn to bzr or svn to mercurial. The git argument is that making
> that initial leap gives you a great deal of freedom and flexibility,
> but it can be intimidating at first.
A great deal of freedom gives any new user also a lot of opportunities
to shoot in his own foot.
And my impression from the mailing lists is that the rescue team is
called more often than with bzr or hg.
My recommendation to myself is not to use with git more than the 10 or
so basic commands similar to svn or bzr. Then I don't think it will
create any real problems.
So the basic workflow description by the nipy and numpy/scipy git
developers will be the most useful help for the transition. (just
confirming what is obvious to you)
>> As long as it is possible to stick with the basic workflow of git
>> without anything fancy, similar what I have seen while skimming the
>> nipy docs, I think it is not a problem on windows.
> I think that is true that most of us won't need to go further than the
> nipy basic workflow - but we haven't been using git long enough to
> know that very well. I would defer to the git masters out there -
> David, Pauli and others - ?
>> However, if/when parts of statsmodels go into scipy and I have to do
>> maintenance of less isolated code, then I think the Mercurial
>> interface might be my preferred choice.
>> I haven't used Mercurial much yet, but I don't see any problems with it.
>> So, the bottom line is, that documentation for the hg-git interface
>> would be very useful for Windows users (or those that think git is a
>> strange/unfamiliar concept.)
> So - two issues:
> 1) The conceptual issues involved in switching mind-set from svn or
> bzr to git. That may require some thought and documentation
> 2) There might be some technical issues using git on windows - but I
> think so far we don't have any reason to think so?
> 3) Some people may prefer mercurial for other reasons; it would be
> good to respect that if possible.
> So, it may well be worth making a hg-git doc for numpy when we do the
> transition - with the caveats that David raised.
> In the meantime, it would be very good to hear of any problems that do
> come up specifically using git on windows...
Right now I only use 3 or so git commands and I don't see any problems.
> See you,
> SciPy-Dev mailing list
More information about the SciPy-Dev