Unify numpy pinning

[xhochy]

This makes maintenance of a lot of packages easier, also quite some packages already use 1.16 as the minimal version.

This probably qualifies for a announcement in the news?

Checklist

• Used a personal fork of the feedstock to propose changes
• Bumped the build number (if the version is unchanged)
• Reset the build number to 0 (if the version changed)
• Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
• Ensured the license file is being packaged.

[conda-forge-linter]

Hi! This is the friendly automated conda-forge-linting service.

I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

[isuruf]

Migrations have to be fixed too

[isuruf]

cc @conda-forge/numpy

[CJ-Wright]

@isuruf which migrations need fixing?

[isuruf]

pypy.yaml

[beckermr]

Yes we need a news item. Also we probably want to make an @/all announcement on gitter.

[isuruf]

According to https://numpy.org/neps/nep-0029-deprecation_policy.html, numpy <1.16 support is dropped on July 23, 2020 which is 4 days from now.

[CJ-Wright]

FYI @tacaswell

[xhochy]

According to https://numpy.org/neps/nep-0029-deprecation_policy.html, numpy <1.16 support is dropped on July 23, 2020 which is 4 days from now.

Seems like a good date to do the transition at the same time.

[xhochy]

Today is July 23rd, merging.