- add a few missing `--system` flags to conda config
- install default notebook config to /etc/jupyter instead of ~/.jupyter
- add a few missing `conda clean`s
* Upgrade to latest debian base image
* Upgrade to Notebook 4.3
* Upgrade to Miniconda 4.2.12
* Remove USE_HTTPS env var in favor of command line options for key and cert
* Add GEN_CERT env var for generating a self-signed certificate
* Remove PASSWORD env var in favor of the new Notebook 4.3 default token auth
or the more secure a hashed password command line option
As per [their blog post of the 27th April](https://blog.readthedocs.com/securing-subdomains/) ‘Securing subdomains’:
> Starting today, Read the Docs will start hosting projects from subdomains on the domain readthedocs.io, instead of on readthedocs.org. This change addresses some security concerns around site cookies while hosting user generated data on the same domain as our dashboard.
Test Plan: Manually visited all the links I’ve modified.
base-notebook defines environment variables for the Conda install path and the
notebook user. However, in some instances, these locations were still hardcoded.
Let’s use the variables instead.
stacks easily usable with JupyterHub.
* pip install jupyterhub to gain access to the jupyterhub-singleuser
startup script, which starts a single-user instance of the Notebook
server
* Add shell script to wrap jupyterhub-singleuser script; use as
alternate Docker command
fixes#181
(c) Copyright IBM Corp. 2016
* create `.juliarc.jl` start up script to point Julia to conda libraries, specifically the hdf5 libraries installed through the h5py package in the scipy stack
* add the HDF5 Julia package
Update README.md to document HDF5 addition
Add -F option to force config load
Add the -F flag to julia expression execution to load .juliarc.jl before execution.
Bite the bullet and preinstall it so that plotting libs that default
to using desktop rendering just work (matplotlib, ggplot, ...)
out of the box without having to get configuration right beforehand
(e.g., %matplotlib inline ahead of matplotlib import)
Only adds ~100k to the image size
(c) Copyright IBM Corp. 2015
