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https://github.com/avara1986/ardy

AWS lamba toolkit to Continuous Integration
https://github.com/avara1986/ardy

aws aws-lambda python toolkit

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AWS lamba toolkit to Continuous Integration

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Ardy (Arthur Hendy)
===================

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:alt: Python 3

Ardy is a toolkit to work with AWS Lambas and implement Continuous Integration.
AWS Lambda is a serverless compute service that runs your code in response to events and automatically manages the underlying compute resources for you. Alas,
AWS Lambda has a very bad GUI interfaces, especially if you work with teams and releases. You can't see at a glance
the triggers you have active, the resources of your AWS Lambda or have a version control.

With `Ardy` you can manage your AWS Lambda with a JSON config file stored in your VCS.

**IMPORTANT NOTE**: If you want to work with AWS Lambda, it's recommended read about it. `Ardy` helps and support you to manage your environments but doesn't performs "The black magic" for you.

Installation
------------

Install the latest Ardy release via pip:

.. code-block:: bash

pip install ardy

You may also install a specific version:

.. code-block:: bash

pip install ardy==0.0.1

Quickstart
----------

See the documentation

How to contrib
--------------
This project is build with `Git Flow `_. If you want to commit some
code use this pattern please:

.. image:: http://nvie.com/img/git-model@2x.png

Extra: Why this name?
---------------------

.. code-block::

import operator
from nltk import FreqDist
from nltk.tokenize import RegexpTokenizer
from nltk.book import text6 # Book Monty Python Holy Grail
import requests

tokens = [f.lower() for f in text6]
result_holygrail = FreqDist(tokens)
# result_holygrail.most_common(42)
holygrail_top = [s[0] for s in sorted([(w, result_holygrail[w]) for w in set(tokens) if len(w) > 4 and result_holygrail[w] > 20], key=operator.itemgetter(1), reverse=True)]

tokenizer = RegexpTokenizer(r'\w+')

response = requests.get("http://www.angelfire.com/movies/closedcaptioned/meanlife.txt")
meanlife = response.text

tokens = tokenizer.tokenize(meanlife)

result_meanlife = FreqDist(tokens)
# result_meanlife.most_common(42)
meanlife_top = [s[0] for s in sorted([(w, result_meanlife[w]) for w in set(tokens) if len(w) > 4 and result_meanlife[w] > 20], key=operator.itemgetter(1), reverse=True)]
for i in range(0, 30):
print("{}: {} {}".format(i+1, holygrail_top[i], meanlife_top[i]))
print("{}: {}{}".format(i+1, holygrail_top[i][:2], meanlife_top[i][-2:]))