Metadata-Version: 2.0
Name: cfn-pyplates
Version: 0.5.0
Summary: Amazon Web Services CloudFormation template generator
Home-page: UNKNOWN
Author: Sean Myers
Author-email: sean.dst@gmail.com
License: MIT
Keywords: setup
Requires-Dist: distribute
Requires-Dist: docopt
Requires-Dist: ordereddict
Requires-Dist: pbr
Requires-Dist: pyyaml
Requires-Dist: schema

============
cfn-pyplates
============

Amazon Web Services CloudFormation templates, generated with Python!

..
  Keep the README in-sync with intro.rst in the sphinx docs!
  The travis image isn't really useful on readthedocs, and also causes
  sphinx warnings, so it should be excluded.

.. image:: https://travis-ci.org/seandst/cfn-pyplates.png
    :target: https://travis-ci.org/seandst/cfn-pyplates/

Where to get it
===============

- https://pypi.python.org/pypi/cfn-pyplates/
- easy_install cfn-pyplates
- pip install cfn-pyplates

Documentation
=============

- https://cfn-pyplates.readthedocs.org/

Intended Audience
=================

pyplates are intended to be used with the `Amazon Web Services CloudFormation
<https://aws.amazon.com/cloudformation/>`_ service. If you're already a
CloudFormation (CFN) user, chances are good that you've already come up with
fun and interesting ways of generating valid CFN templates. pyplates are a
way to make those templates while leveraging all of the power that the python
environment has to offer.

What is a pyplate?
==================

A pyplate is a class-based python representation of a JSON CloudFormation
template and resources, with the goal of generating cloudformation
templates based on input python templates (pyplates!) that reflect the
cloudformation template hierarchy.

Features
========

- Allows for easy customization of templates at runtime, allowing one
  pyplate to describe all of your CFN Stack roles (production, testing,
  dev, staging, etc).
- Lets you put comments right in the template!
- Supports all required elements of a CFN template, such as Parameters,
  Resources, Outputs, etc.)
- Supports all intrinsic CFN functions, such as base64, get_att, ref,
  etc.
- Converts intuitiviely-written python dictionaries into JSON templates,
  without having to worry about nesting or order-of-operations issues.



