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Test-Driven Data Analysis (Python TDDA library)
===============================================

Version |version|. (`Installation <installation.html>`_)



The TDDA module helps with the testing of data and of code that
manipulates data. It serves as a concrete implementation of the ideas
discussed on the `test-driven data analysis
<http://www.tdda.info/pages/table-of-contents.html#table-of-contents>`_
blog.  When installed, the module offers a suite of command-line tools
that can be used with data from any source, not just Python.  It also
provides enhanced test methods for Python code, and the new
*Gentest* functionality enables automatic generation of
test programs for arbitrary code (not just Python code).  There is
also a full Python API for all functionality.

*Test-driven data analysis* is closely related to
`reproducible research <https://en.wikipedia.org/wiki/Reproducibility>`_,
but with more of a focus on automated
testing. It is best seen as overlapping and partly complementary
to reproducible research.

The major components of the TDDA module are:

.. image:: image/tdda-machines-light.png
  :alt: Machines illustrating the constraint discovering functionality,
        which takes data in and produces constraints as output;
        rexpy, which takes strings in and produces regular expressions
        as output, and gentest, which takes code in and produces
        tests as output.



* **Automatic Constraint Generation and Verification:** The package includes command-line tools and API calls for

  - *discovery* of constraints that are satisfied by (example)
    data --- ``tdda discover``;
  - *verification* that a dataset satisfies a set of constraints.
    The constraints can have been generated automatically,
    constructed manually, or (most commonly) consist of
    generated constraints that have been
    subsequently refined by hand --- ``tdda verify``;
  - *detection* of records, fields and values that fail to satisify
    constraints (anomaly detection) --- ``tdda detect``.

* **Reference Testing:** The TDDA library offers extensions to
  ``unittest`` and ``pytest`` for managing the testing of data analysis
  pipelines, where the results are typically much larger, and more
  complex, and more variable than for many other sorts of programs.

* **Automatic Generation of Regular Expressions from Examples:** There
  is a command-line tool (and API) for automatically inferring
  `regular expressions <https://en.wikipedia.org/wiki/Regular_expression>`_
  from (structured) textual data --- ``rexpy``. This was developed
  as part of constraint generation, but has broader utility.

* **Automatic Test Generation (Experimental):** From version 2.0 on,
  the TDDA library also includes experimental features for
  automatically generating tests for almost any command-line based
  program or script. The code to be tested can take the form of a
  shell script or any other command-line code, and can be written
  in any language or mix of languages.



Contents
========

.. toctree::
   :maxdepth: 2

   overview.txt
   installation.txt
   constraints.txt
   rexpy.txt
   gentest.txt
   referencetest.txt
   constraints-api.txt
   rexpy-api.txt
   windows.txt
   tests.txt
   examples.txt
   changes.txt

Resources
=========

* `Talks & Filmed Tutorials about TDDA etc (Nick Radcliffe) <https://stochasticsolutions.com/talks/>`_
* `TDDA Library (PyCon DE, Eberhard Hansis, 2019) <https://www.youtube.com/watch?v=ADEBxja8vw4>`_
* `Tutorial Video Screencasts on Exercises <http://www.tdda.info/exercises>`_
* `Tutorials YouTube Channel <https://www.youtube.com/channel/UCAwK_xYqaEL3lEOz4YUZmZw>`_
* `Paper: Automatic Constraint Generation and Verification <http://www.tdda.info/pdf/tdda-constraint-generation-and-verification.pdf>`_
* `1-page summary of ideas <http://stochasticsolutions.com/pdf/TDDA-One-Pager.pdf>`_
* `Quick-reference Guide / Cheat Sheet <http://www.tdda.info/pdf/tdda-quickref.pdf>`_
* `TDDA Blog <http://www.tdda.info/pages/table-of-contents.html#table-of-contents>`_
* `Twitter tdda0 <https://twitter.com/tdda0>`_
* `Slack <https://tdda.slack.com>`_ (mail/DM on twitter for invitation)
* `Source Repository (Github) <https://github.com/tdda/tdda>`_




Indexes and Search
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`