As it appears that `defaults` has added `blas` without a feature, the
`conda` solver appears to be prioritizing the removal of features over
channel priority. As a result, we leverage `MatchSpec` here to pin the
`blas` package to `conda-forge` and the `openblas` feature. This should
be respected by `conda` and thus avoid switching to the incompatible
`blas` package from `defaults`.

Upgrade Ubuntu to latest LTS (Bionic 18.04)

Continued work on contributor doc

Require at least blas 1.1; otherwise other packages dependencies may
attempt to downgrade it.

Add Mesos GPG key since accessing the keyserver seems to be flaky:
https://github.com/docker-library/official-images/issues/4252#issuecomment-381783035

Upgrade Ubuntu to latest LTS (Bionic 18.04), including:
- Change the IMAGE used for base-notebook;
- Keep Mesos install from Mesosphere's Xenial repository, since they
  don't yet have a Bionic repository;
- gnupg needs to be installed for apt-key to work;
- --force-yes option to apt-get has been removed;
- Package libav-tools is replaced by ffmpeg;
- Update Let's Encrypt example script to use 18.04.

Upgrade to conda 4.5.4

[ci skip] Fill out github community files

Add nano and vim to Dockerfiles

Migrate from READMEs to RTD site

Some contributor documentation

Don't chown -R a user's home directory

If people have a use case for recursive chowns that's fine.  I think it's dangerous for people to use, but that's tailored to my use case.

My attempt at reorganization

Made language stronger on this for variety.

extraneous space removed

Took out bullets and reworked item 3

Trimmed line 2 for clarity and moved sections and added headings

CHOWN_EXTRA is a comma separated list of directories to chown.

send2trash not work

https://github.com/jupyter/notebook/issues/3130
Now, files not delete on https://hub.docker.com/r/jupyter/base-notebook/ and derived container images.

Only the top level permissions are set wrong due to kubernetes not being able to do this automatically.

This hits significant problems when the chown takes more than 30s and the pod fails to start