[yaph]

If a package doesn't get all its dependencies installed via pip its because of missing information in the package itself. That's neither a flaw of pip or Python but will cause problems for any package manager.

I find the combination of virtual environments and pip very convenient to work with. When I run into trouble with missing dependencies I often find the project on GitHub and can send a pull request.

Regarding Numpy and the scientific Python stack, check out Anaconda https://store.continuum.io/cshop/anaconda/ it makes managing environments where you need these packages a lot less painful.

[andreasvc]

Not necessarily. pip cannot resolve all dependencies. For example, if a package specifies both numpy and pandas as a requirement, installation will fail. This is because pandas in turn requires numpy, and pip does not resolve the dependencies in a single step, you need to install numpy first and then go on with pandas.

[yaph]

In that case, couldn't you just specify Pandas as a dependency and Numpy would automatically be installed?

[andreasvc]

I think not, I think the problem is that it is a build-time dependency and pip wants to resolve all dependencies before installation begins.

See https://github.com/pypa/pip/issues/1386 (oddly, the issue is closed, while the problem is acknowledged).

[yaph]

I see, thanks for pointing to that issue. The other issue referred https://github.com/pypa/pip/issues/988 is still open, so I guess they work on sorting this out.