Git Product home page Git Product logo

Comments (8)

moble avatar moble commented on July 29, 2024

In your .travis.yml file, I'm guessing you have a section with something like

install:
  - pip install numpy numpy-quaternion

Try changing that to

install:
  - pip install numpy
  - CI=false pip install numpy-quaternion

That sort of thing would work in bash by just changing the value of CI for that one command. Hopefully travis doesn't do so much "magic" that this is broken.

Unfortunately, auto_version is a little too dumb and used throughout too many of my projects to provide a more elegant solution. I'm afraid I don't really use pip myself, and I won't have a lot of time for this stuff any time soon (we're having twins!), so I'm sorry if this isn't the most robust or helpful solution, but I am open to suggestions that don't break my own process.

from quaternion.

bennyrowland avatar bennyrowland commented on July 29, 2024

Thanks for a very speedy response, at least. Actually in my .travis.yml file I have a pip install . which installs my own module and its dependencies from setup.py. I could no doubt break out the dependency separately as you suggest but as you note it is not super elegant, as it removes the automatic installation that pip otherwise provides.

From my point of view the obvious question is whether it is necessary to error out on CI if the git command fails. I guess that you put that in to make sure that it was working early on, but I don't see why that is a useful feature now. Not suggesting that it needs to be changed though, I can work around it as you suggest. I will close the issue for now.

from quaternion.

moble avatar moble commented on July 29, 2024

This is a legitimate problem, so I'll leave it open in case other people come looking for a way to solve it.

From my point of view the obvious question is whether it is necessary to error out on CI if the git command fails.

My answer is yes. The problem is that the CI process doesn't just test, but also uploads pip and conda packages, and those packages get their versions from this git information. Some times git does indeed fail, even now when things are generally working — usually due to subtle errors or changes in travis-ci. These particular version numbers fulfill a few requirements, including solving conda dependencies, and ensuring that data produced from my code (in which I include the version numbers of any packages I use) can be easily traced back to its origins down to the commit level. So I definitely don't want the packages going out if they can't get their version numbers. There's probably a better way to set the versions using git hooks, but it won't be easy for me to change at this point.

from quaternion.

moble avatar moble commented on July 29, 2024

This should be fixed since b732124, which simplified the version number so that it no longer uses auto_version (even though the submodule is still in the code...).

from quaternion.

jvgomez avatar jvgomez commented on July 29, 2024

Should this work now then?
pip install --no-cache-dir numpy numpy-quaternion because this still fails for me

from quaternion.

Achllle avatar Achllle commented on July 29, 2024

This is still an issue @moble

from quaternion.

moble avatar moble commented on July 29, 2024

@Achllle No, this is not still an issue; the issue you appear to be talking about is jvgomez's question, which is a different issue. This issue was about the CI stuff. See #99.

from quaternion.

Achllle avatar Achllle commented on July 29, 2024

Alright, sorry that I commented on this issue. Seems like it's the same as #99 in that case.

from quaternion.

Related Issues (20)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.