Remove abandoned alternatives from the documentation

This commit is contained in:
Javier Goizueta 2016-03-16 16:30:03 +01:00
parent 4706442a1d
commit bad09ffd7b

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@ -20,37 +20,29 @@ nosetests test/
---
We have two possible approaches being considered as to how manage
the Python virtual environment: using a pure virtual enviroment
or combine it with some system packages that include depencencies
for the *hard-to-compile* packages (and pin them in somewhat old versions).
To avoid troublesome compilations/linkings we will use
the available system package `python-scipy`.
This package and its dependencies provide numpy 1.6.1
and scipy 0.9.0. To be able to use these versions we cannot
PySAL 1.10 or later, so we'll stick to 1.9.1.
### Alternative A: pure virtual environment
```
apt-get install -y python-scipy
```
In this case we will install all the packages needed in the
virtual environment.
This will involve, specially for the numerical packages compiling
and linking code that uses a number of third party libraries,
and requires having theses depencencies solved for the production
environments.
We'll use virtual environments to install our packages,
but configued to use also system modules so that the
mentioned scipy and numpy are used.
#### Create and use a virtual env
We'll use a virtual enviroment directory `dev`
under the `src/pg` directory.
# Create the virtual environment for python
$ virtualenv dev
# Create a virtual environment for python
$ virtualenv --system-site-packages dev
# Activate the virtualenv
$ source dev/bin/activate
# Install all the requirements
# expect this to take a while, as it will trigger a few compilations
(dev) $ pip install -r requirements.txt
# Add a new pip to the party
(dev) $ pip install pandas
(dev) $ pip install -I ./crankshaft
#### Test the libraries with that virtual env
@ -94,37 +86,3 @@ Then, execute the tests with:
import pysal
import nose
nose.runmodule('pysal')
### Alternative B: using some packaged modules
This option avoids troublesome compilations/linkings, at the cost
of freezing some module versions as available in system packages,
namely numpy 1.6.1 and scipy 0.9.0. (in turn, this implies
the most recent version of PySAL we can use is 1.9.1)
TODO: to use this alternative the python-scipy package must be
installed (this will have to be included in server provisioning)
```
apt-get install -y python-scipy
```
#### Create and use a virtual env
We'll use a `dev` enviroment as before, but will configure it to
use also system modules.
# Create the virtual environment for python
$ virtualenv --system-site-packages dev
# Activate the virtualenv
$ source dev/bin/activate
# Install all the requirements
# expect this to take a while, as it will trigger a few compilations
(dev) $ pip install -I ./crankshaft
Then we can proceed to testing as in Alternative A.