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        "author": "NL Healthcare (NLHC), Henk-Jan van Reenen",
        "author_email": "henk-jan.van.reenen@nlhealthcareclinics.com",
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        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "Intended Audience :: Healthcare Industry",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU Lesser General Public License v3 or later (LGPLv3+)",
            "Natural Language :: Dutch",
            "Operating System :: POSIX :: Linux",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "PYELT\r\n=====\r\n\r\n\r\nUsage\r\n^^^^^\r\n\r\nThis example will create and fill the historical staging area::\r\n\r\n    pipeline = Pipeline(config)\r\n    pipe = pipeline.get_or_create_pipe('test_source', source_config)\r\n\r\n    source_file = CsvFile(get_root_path() + '/sample_data/patienten1.csv', delimiter=';')\r\n    source_file.reflect()\r\n    source_file.set_primary_key(['patientnummer'])\r\n    mapping = SourceToSorMapping(source_file, 'persoon_hstage', auto_map=True)\r\n    pipe.mappings.append(mapping)\r\n\r\n    pipeline.run()\r\n    \r\nMore examples can be found on `the GitHub repository of NL Healthcare <https://github.com/NLHEALTHCARE/PYELT/tree/master/samples//>`_.\r\n\r\n\r\nIntroduction\r\n^^^^^^^^^^^^\r\n\r\nPyelt is a Python DDL and ETL framework for **creating and loading Data Vaults** for datawarehousing.\r\n\r\nPyelt supports **several data-layers**, including Source-of-Record (SOR), Raw datavault (RDV), Business datavault (BDV) and Datamarts (DM) \r\n\r\nPyelt can import data from several **different source systems** such as fixed length files, csv-files, and different databases.\r\n\r\nPyelt is developed to run on a **postgreSQL database**.\r\n\r\nPyelt uses the SQLAlchemy.core only for the connection and for reflection. All other SQL statements (ddl, copy, insert and update statements) are created by the pyelt framework itself.\r\n\r\n**Write your own mappings** to transfer and transform data from sources via staging into the data ware house.\r\n\r\nContent \r\n----------------------------\r\n\r\n(`current documentation on pythonhosted <http://pythonhosted.org/pyelt//>`_ is only in dutch):\r\n\r\n- `concepts <https://github.com/NLHEALTHCARE/PYELT/tree/master/docs/source/00concepts.rst/>`_\r\n- `config <https://github.com/NLHEALTHCARE/PYELT/tree/master/docs/source/01config.rst/>`_\r\n- `pipeline <https://github.com/NLHEALTHCARE/PYELT/tree/master/docs/source/02pipeline.rst/>`_\r\n- `domain <https://github.com/NLHEALTHCARE/PYELT/tree/master/docs/source/03domain.rst/>`_\r\n- `mappings <https://github.com/NLHEALTHCARE/PYELT/tree/master/docs/source/03mappings.rst/>`_\r\n- `run proces <https://github.com/NLHEALTHCARE/PYELT/tree/master/docs/source/04etl_proces.rst/>`_\r\n\r\nwork in progress:\r\n\r\n- api docs (https://github.com/NLHEALTHCARE/PYELT/tree/master/docs/source/09api.rst/>_\r\n\r\n\r\n\r\nBackground\r\n^^^^^^^^^^\r\nThe pyelt framework is presently under development at NL Healthcare, with the aim to implement our next-generation datawarehouse (DWH2.0). It serves as the foundation for our work in the area of clinical business intelligence (CBI) and machine-learning.\r\n\r\nArchitectural cornerstones of this project are:\r\n\r\n- the Data Vault (DV) design pattern of `Hans Hultgren <https://hanshultgren.wordpress.com/>`_ \r\n- Domain-specific modelling of the DV, following `HL7 v3 Reference Information Model <https://www.hl7.org/documentcenter/public_temp_0BB49CB1-1C23-BA17-0C2E211163D07382/calendarofevents/himss/2009/presentations/Reference%20Information%20Model_Tue.pdf/>`_ and the Dutch Detailed Clinical Model `Zorginformatiebouwstenen <https://zibs.nl/>`_ (in Dutch).",
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        "keywords": "datavault, datawarehouse, ETL, ELT, healthcare, domain model",
        "license": "LGPL3",
        "maintainer": "Daniel Kapitan",
        "maintainer_email": "daniel@kapitan.net",
        "name": "pyelt",
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