Metadata-Version: 2.1
Name: aws_textract_pipeline
Version: 0.2.1
Summary: Package short description.
Home-page: https://github.com/MacHu-GWU/aws_textract_pipeline-project
Download-URL: https://pypi.python.org/pypi/aws_textract_pipeline/0.2.1#downloads
Author: Sanhe Hu
Author-email: husanhe@gmail.com
Maintainer: Sanhe Hu
Maintainer-email: husanhe@gmail.com
License: MIT
Platform: Windows
Platform: MacOS
Platform: Unix
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: MacOS
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3 :: Only
Requires-Python: >=3.8
License-File: LICENSE.txt
License-File: AUTHORS.rst
Requires-Dist: aws-textract <1.0.0,>=0.2.1
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Welcome to ``aws_textract_pipeline`` Documentation
==============================================================================
.. image:: https://aws-textract-pipeline.readthedocs.io/en/latest/_static/aws_textract_pipeline-logo.png
    :target: https://aws-textract-pipeline.readthedocs.io/en/latest/

This project is a low-level implementation of the "Data Store Pipeline" component described in the `Intelligent Document Processing Platform Solution Design <https://dev-exp-share.readthedocs.io/en/latest/search.html?q=Intelligent+Document+Processing+Platform+Solution+Design&check_keywords=yes&area=default>`_ solution.

The term "low-level implementation" implies that this implementation does not rely on AWS services and performs pure in-memory computations. This implementation can be deployed on any platform and is not limited to the AWS ecosystem. It can be deployed as a batch job using virtual machines or containers, or it can be used for real-time processing with an event-driven architecture.

See usage example at `test_pipeline.py <https://github.com/MacHu-GWU/aws_textract_pipeline-project/blob/main/debug/test_pipeline.py>`_.


.. _install:

Install
------------------------------------------------------------------------------

``aws_textract_pipeline`` is released on PyPI, so all you need is to:

.. code-block:: console

    $ pip install aws-textract-pipeline

To upgrade to latest version:

.. code-block:: console

    $ pip install --upgrade aws-textract-pipeline
