Moving to Python 3 > 2019-01-01 about fecon235 HOT 4 OPEN

CHANGELOG 2018-06-23 (tag: v6.18.0623)

Major version change for fecon235 from v5 to v6
signaling our integration with fecon236
which was spun-off from our source code.

Henceforth, fecon235 becomes a repository solely of Jupyter notebooks.
The old Python source code at fecon235 will remain for archival purposes,
while new code development shifts over to fecon236.
Please see https://git.io/econ for details.

Revise docs/fecon235-00-README.ipynb to introduce fecon236.
Function names have been retained, but under fecon236
the call routing is expected to be more explicit than casual,
i.e. modules names are more significant.
Please see https://git.io/fecon-intro

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Source code spin-off to fecon236

Home for our Jupyter notebooks shall remain at fecon235
due to their bulky size.
Migration to the python3 kernel should present no problems
since fecon235 is compatible with both python27 and python3.
End users will be able to simply import fecon236 as fe
as a drop-in replacement.

Version 10 of fecon236 represents the refactoring of only the fecon235
v5.18.0312 library code (not the Jupyter notebooks).
It shall maintain compatibility with both python27 and python34.

After 2019-01-01, our official support for python27 will discontinue
(like numpy and pandas), however, straddling code may still
continue to work.

Version 11 of fecon236 will signal when our Travis builds under python27 fail,
and at that point we expect to require at least Python 3.6.

Note the change in repository OWNERSHIP from
INDIVIDUAL rsvp to ORGANIZATION MathSci
for fecon236 in order to accommodate team permissions.

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Numpy and Pandas: Python 3 only > 2019-01-01

Starting January 1, 2019, all releases will be Python 3 only.

https://github.com/pandas-dev/pandas/pull/20540/files

Note that this date is one year before Python 3 itself.
Since we depend heavily on numpy and pandas,
fecon235 and fecon236 shall also follow this schedule.

Porting to Python 3 guide: https://docs.python.org/3/howto/pyporting.html

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Rebuild Docker container

The gist is to use Miniconda3 as base for python3, e.g.

wget http://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
bash miniconda.sh -b -p $HOME/miniconda
export PATH="$HOME/miniconda/bin:$PATH"
conda config --set always_yes yes --set changeps1 no
conda config --add channels pandas
conda update -q conda
conda info -a
conda install numpy pytz python-dateutil
conda install pandas=0.22
#  ^Example: install specific version.
conda install matplotlib
conda list

Then add the few dependencies from the scientific numpy/pandas stack.
This avoids the huge bloat to the Docker image size
from the alternate, but full, Anaconda distribution (astropy, bokeh, etc.).
Take a look at https://hub.docker.com/r/rsvp/fecon235
where eventually we will directly install fecon236 modules.

(Also, this is the way the environment for fecon236 continuous integration
will be built. The .travis.yml file will appear shortly with more details.)

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