Hi,
# 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 git@github.com: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 directories.
Ah - with the paragraph below, I begin to see what you mean. You often have uncommitted changes, hence the need for several working trees. You can compare repositories, but it's a bit harder that with - say - bzr: http://stackoverflow.com/questions/687450/how-do-i-compare-two-git-repositor...
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.
Right - I see your point. Maybe the git solution to that workflow will be more obvious to others than it is to me.
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.
That's fair. It is easier to mess up with git - it has a steeper learning curve when you go past the basics. It is well worthwhile spending some time understanding the model underneath it - good links from Fernando's page : http://www.fperez.org/py4science/git.html ; I particularly liked http://tom.preston-werner.com/2009/05/19/the-git-parable.html .
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)
Worth saying - thanks for the thoughtful feedback, Matthew