Python 应用程序的版本冲突，但不适用于交互式开发

Question

I have a package P that depends on a package A . Package A depends on packages B and C==3 . At the same time, Package B depends on C==4 .

This creates conflicts and an akward error message is shown in red every time I pip install packages P or A .

Now, I know I can run packages P and A just fine if I import them in an interactive terminal or Jupyter notebook and I call the functions and classes I need. However, package P has a command line application, which raises an error as long as you have the install conflicts inherited from package A .

This error is not raised by me, it is raised by the Python interpreter alone (I think), since I am not calling any new functionality compared to when I use P as a library. In fact, my CLI is a class wrapped by fire , which I can call without problems in an interactive session.

The error trace shows pkg_resources.ContextualVersionConflict in the end, which I never call in P .

Given that I can only control what happens in package P , is there a way for make it work directly as a command line app?

I am also interested to know what is happening under the hood.

Bytheway, I am always installing P in a new Conda environment.

For package B there is only one version available, not multiple versions.

Thanks!

Answer 1

From what I understood the version of B is not constrained by A , so basically any version of B would be acceptable. Now, maybe there is a version of B that has C==3 in its dependencies. If such a version of B exists, let's say it's B==5 , then the following could work:

path/to/pythonX.Y -m pip install P B==5

If it does indeed work, for a long term solution, you might want to try one of the following:

• Set a B==5 constraint on your project P , since you have control over it. I probably wouldn't recommend it though, since B is not actually a direct dependency of P .
• Use a constraints.txt file containing B==5 and call pip with the --constraint option :
  • path/to/pythonX.Y -m pip install --constraint constraints.txt P

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Additionnally I would recommend giving pip 's new, experimental dependency resolver a try. It might be better at finding the right combination or projects to install in such situations.

path/to/pythonX.Y -m pip --unstable-feature=resolver install P

See this answer for details:

• https://stackoverflow.com/a/62872812/11138259