pyconverge

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converge

Resolve Data from Abstract Hierarchies and Templates

Managing configuration is hard. More often than not you have high key/values duplication and storage. DRY <https://en.wikipedia.org/wiki/Don't_repeat_yourself>__ your tears, it's time for some hierarchical magic, so you can get back to the important stuff.

This is where converge comes in. There are a few basic concepts when using or extend converge: * Readers: get data from your backends * Filters: filter data before or after resolution (example: search & replace values, inject data post resolution) * Resolvers: convert abstract data to resolved data * Writers: output your data to the format and backend you need

Abstract hierarchies of data chewed up and spit out to your liking.

Getting started

install pyconverge, this will add the converge command to your classpath using setup.py/PyPi

.. code:: bash

pip install pyconverge
converge version
converge --help

Create a converge.yaml.template file in your project working directory, modify and move it to converge.yaml

.. code:: bash

# create the converge.yaml.template file
converge init conf
# modify your converge parameters
vim converge.yaml.template
# activate converge
mv converge.yaml.template converge.yaml
# verify the integrity of your configuration file
converge check

Try it out! You chould have a bunch more options!

.. code:: bash

converge --help

Example: Simple testing

create a converge.yaml as described above

.. code:: bash

converge init conf
mv converge.yaml.template converge.yaml
converge check

Create a sample repository structure

.. code:: bash

converge init repository target_directory

# you should now have the following structure
find target_directory/ -type d
# this is where the application centric data goes
./data
./data/default
./data/default/shared
./data/default/app
# the hierarchy file is situated here
./hierarchy
# target (or host for most) centric data resides here
./targets
./targets/hosts
./targets/mapping

Configuration

converge.yaml

This file is a bit peculiar, it allows you to add programs, options, configurations on the fly. Let's try it out before adding the converge.yaml:

.. code:: bash

converge --help
# positional arguments:
#  {init,check,version}
#    init                initialize configuration or repository
#    check               run sanity check on configuration
#    version             get converge version and build information

Put the following in a converge.yaml:

.. code:: yaml

conf:
    default:
        logging_level: "INFO"
programs:
    # user command
    amazingcommand:
        # arguments expected by the command
        args:
            - "argument_one"
            - "argument_two"
        # description for the python help
        description: "application description"
        modes:
            amazing_mode_one:
                - "com.insane.class.path.Class1"
                - "com.insane.class.path.Class2"
            amazing_mode_two:
                - "com.insane.class.path.Class1"
                - "com.insane.class.path.Class3"

Now you should see a new option:

.. code:: bash

converge --help
# positional arguments:
#  {init,check,version,amazingcommand}
#    init                initialize configuration or repository
#    check               run sanity check on configuration
#    version             get converge version and build information
#    amazingcommand      application description <-- MAGIC STUFF with description!!

And even more so there are sub-options available too:

.. code:: bash

converge amazingcommand --help
# usage: converge-runner.py amazingcommand [-h]
#                                         argument_one argument_two
#                                         {amazing_mode_two,amazing_mode_one}
#
# positional arguments:
#  argument_one
#  argument_two
#  {amazing_mode_two,amazing_mode_one}

Classpath Execution Explained

Those classpaths you listed under the modes, will be executed expecting a method matching the following:

.. code:: python

def run(self, data, conf, **kwargs):
    """
    Args:
        data (dict): The data object that is passes and returned from all class runs
        conf (dict): Dictionary of all configurations found in converge.yaml (directories, logging etc)
        kwargs (object): magical python variable variable variables.

    Returns:
        dict: the data object that will be passed to all following class-runs.
    """
    return data

Example: Configuration for Java property files

A rough overview

A general example in diagram form:

.. figure:: docs/converge-diagram.png :alt: Converge Overview

Alt text

A Brief History of Pain

You may have hit some (or all) of these stages in the pursuit of configurability:

In short: from the file, to the GUI, back to the file you idiot. #wevecomefullcircle * Externalize configuration from your applications, to avoid re-releases due to simple conf tuning * Realizing that you're now managing a million de-centralized files with no similar structure * Create or use a centralized, GUI/DB based configuration management system (woohoo! configuration liberation!) * Realizing that you are missing flexibility, automation is complex, added abstraction layers are painful.

The better model is to accept any data format, process it and output it as you wish.

Files are better because: * you can use time tested versioning systems like git or mercurial to branch, release, rollback, check history * you can automate the modification of files with any tool you want * doing migrations/deployment/modifications on DB values/REST endpoints sucks (unnecessarily complex)

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