ayeaye 0.1.5

An ETL (Extract, Transform, Load) framework

Aye Aye

An ETL (Extract, Transform, Load) framework.

Quick install

In the virtual environment for the project you’d like to use Aye Aye in, run:-

pip install ayeaye

Quick start

Use Pipenv to manage a python virtual environment and package management0

pipenv shell
pipenv install ayeaye

Within the environment created by pipenv above, run one of the examples:-

curl "https://raw.githubusercontent.com/Aye-Aye-Dev/AyeAye/master/examples/poisonous_animals.py" \
  --output poisonous_animals.py
mkdir data
curl https://raw.githubusercontent.com/Aye-Aye-Dev/AyeAye/master/examples/data/poisonous_animals.json \
  --output data/poisonous_animals.json
python poisonous_animals.py 

This model takes a small input dataset of animals and collates them by the country they are found. It doesn't write to a dataset, it just outputs a log. The log for this example contains the name of the country and the animals found there.

There are more examples in the Aye-Aye-Recipes git repo.

Overview

An Aye Aye ETL model inherits from ayeaye.model and uses class level variables to declare connectors to the data it acts on.

Example:-

import ayeaye

class PoisonousAnimals(ayeaye.Model):
    poisonous_animals = ayeaye.Connect(engine_url='json://data/poisonous_animals.json')

When instantiated, self.poisonous_animals will be a dataset that ETL operations can be done with.

The engine_url parameter passed to ayeaye.Connect is specifying the dataset type JSON in this case) and exact location for the data (data/poisonous_animals.json is a relative file path).

Instead of engine_url you could also specify a ref and this uses the data catalogue to lookup the engine_url. (TODO this feature is coming soon!). When used this way, ayeaye.Connect is responsible for resolving the ref to an engine_url and passing this to a subclass of ayeaye.connectors.base.DataConnector which can read and maybe write this data type.

Unit tests

Ensure the working directory is the base Aye Aye directory (i.e. the same directory as the Pipfile):

pipenv install --dev
export PYTHONPATH=`pwd`/lib
pipenv run python -m unittest discover

Development version

To use the latest code in editable mode-

pipenv install -e git+https://github.com/Aye-Aye-Dev/AyeAye#egg=ayeaye

When venv is being used, add this line to requirements.txt-

git+https://github.com/Aye-Aye-Dev/AyeAye#egg=ayeaye

Optional extras

Extra dependencies for API usage within Aye-aye models can be installed like this:

pipenv install "ayeaye[api]"
 or multiple
pipenv install "ayeaye[api,aws,compression]"

Label	Functionality
api	Restful JSON via http(s)
aws	File based connectors can use Amazon Web Service S3 file storage
compression	On the fly compression for file based connectors

License

Aye Aye is distributed under the terms of the Apache License 2.0 and Copyright Progressive Logic Limit 2021 and onwards.