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openlmi-tools 0.9.1

OpenLMI (non)interactive shell and meta-command

Package Documentation

Latest Version: 0.10.4

Client-side python modules and command line utilities.

It comprises of one binary called `lmi` and a common library. `lmi`
meta-command allows to run commands on a set of OpenLMI providers. These
commands can be installed separately in a modular way.

`lmi` is a command line application allowing to run single command on a set
of hosts with just one statement from `shell` or it can run in an
interactive way.

For more information please refer to online documentation on [pythonhosted][]
or build your own in `doc/` directory.

Code base is written for `python 2.7`.
There are following python dependencies:

* python-docopt

### Uploading to PyPI
Since *PyPI* expects README file to be in a *reStructuredText* markup
language and the one present is written in *markdown*, it needs to be
converted to it. So please make sure you have `pandoc` installed before

$ python sdist upload

Use standard `setuptools` script for installation:

$ cd openlmi-scripts
$ python install --user

This installs just the *lmi meta-command* and client-side library. To install
subcommands, you need to do the same procedure for each particular command
under `commands/` directory.

Script eggs are also available on *PyPI*, install them with:

$ pip install --user openlmi-scripts
$ # add any provider you want to interact with
$ pip install --user openlmi-scripts-service openlmi-scripts-software

To get a help and see available commands, run:

$ lmi help

To get a help for particular command, run:

$ lmi help service

To issue single command on a host, run:

$ lmi --host ${hostname} service list

To start the app in interactive mode:

$ lmi --host ${hostname}
> service list --disabled
> service start svnserve.service
> quit

Developing lmi scripts.

This documents how to quickly develop lmi scripts without the need to
reinstall python eggs, when anything is changed. This presumes, that the
development process takes place in a git repotory checked out from [git][].
It can be located anywhere on system.

Before we start with setting up an environment, please double check, that you
don't have installed anything from openlmi-scripts in system path
(`/usr/lib/python2.7/site-packages/lmi/scripts` should not exist). And make
sure, that user path is also cleared:

$ rm -rf $HOME/.local/lib/python2.7/site-packages/lmi*
$ rm -rf $HOME/.local/lib/python2.7/site-packages/openlmi*

Install all dependencies:

* python-docopt
* openlmi-python-base
* openlmi-tools

Either via rpms or from respective git repositories. For openlmi-python-base
package contained in [providers-git][] repository the setup script is
located at `src/python/`. In future these will be available from PyPi.

Let's setup an environment:

1. Create a workspace directory for current `$USER` (let's call it a `WSP`).
This is a place, where our eggs and binaries will be "installed".
It can be located anywhere, for example:

$ WSP=~/.python_workspace
$ mkdir $WSP

2. Add workspace to your python path to make all modules installed there
importable (you can add this to your `~/.bashrc`):


3. Add workspace to your PATH, so the installed binaries can be run:

$ export PATH=$WSP:$PATH

4. Now let's "install" to our workspace. First `cd` to checked out
openlmi-scripts repository.
5. Install them and any commands you want -- possibly your own

$ python develop --install-dir=$WSP
$ for cmd in service storage; do
> pushd commands/$cmd
> python develop --install-dir=$WSP
> popd
> done

Now any change made to openlmi-scripts is immediately reflected in `lmi`

[git]: "openlmi-scripts"
[providers-git]: "openlmi-providers"
[pythonhosted]: "python hosted"
[PyPI]: "PyPI"  
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