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        "description": "#etlTest\n\n[![Build Status](https://travis-ci.org/OpenDataAlex/etlTest.png?branch=dev)](https://travis-ci.org/OpenDataAlex/etlTest)\n[![Coverage Status](https://coveralls.io/repos/OpenDataAlex/etlTest/badge.png?branch=dev)](https://coveralls.io/r/OpenDataAlex/etlTest?branch=dev)\n[![Codacy Badge](https://www.codacy.com/project/badge/0ff3a2e5b651416e9292ca9cdedf58f8)](https://www.codacy.com)\n[![Documentation Status](https://readthedocs.org/projects/etltest/badge/?version=latest)](https://readthedocs.org/projects/etltest/?badge=latest)\n[![endorse](https://api.coderwall.com/dbaalex/endorsecount.png)](https://coderwall.com/dbaalex)\n\n\n##Installation\n\nYou can install **etlTest** by downloading the source and using the setup.py script as follows:\n\n    $ git clone git@github.com:OpenDataAlex/etlTest.git\n    $ cd etlTest\n    $ python setup.py install\n\nThis setup call installs all of the necessary python dependencies. There are a few external dependencies as well, so please see the section below labeled \"Non-Python Dependencies\".\n\nOnce you have done that, its ready to run!\n\n### So what is etlTest?\n\nHaving come from software development and working with data integration tools, we always wondered why there wasn't \nsome kind of uniform unit and integration testing tool specific to data integration.  etlTest aims to fill that gap \nby providing an easy to use tool and data source agnostic testing tool.  Testing is designed to be \"black box\" - \nwhich means that we aren't diving into the actual data integration code.  Rather, \nwe are executing the data integration process based on test data sets provided by the test writer and comparing the \nresults using Python's unittest framework.\n\netlTest is based on the work and discussions that were started with etlUnit.\n\n### Quickstart\n\nTo actually use etlTest, you need a data and test file for it to act on. A most basic resource file can be \nfound in \nthe [samples](https://github.com/OpenDataAlex/etlTest/tree/dev/etltest/samples) directory of the project \n(data/etlUnitTest/users.yml and test/dataMart/users_dim.yml). \nExecuting the\n following will take that resource, generate some python code in the output directory specified, and run the code which will display the output of the tests executed to your terminal.\n\n    $ python etlTest/etltest/etlTest.py -f <path to users_dim.yml test file> -o /tmp/ -g -e\n\n### Documentation\n\nThe documentation for **etlTest** can be found on Read the Docs [here](https://etlTest.readthedocs.org/en/latest/).\n\n### Non-Python Dependencies\n\nThe only dependencies that are not handled in python currently are the ones for SQLAlchemy to connect to datasources. Documentation on how to install these is as follows:\n\n* [MySQL](https://github.com/OpenDataAlex/etlTest/blob/develop/docs/mysql_deps.md)\n* [Oracle](https://github.com/OpenDataAlex/etlTest/blob/develop/docs/oracle_deps.md)\n\n### Reporting Issues\n\nWe would love some feedback! Please do not hesitate to report any issues/questions/comments via the [Github Issue Tracker](https://github.com/OpenDataAlex/etlTest/issues).\n",
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