Metadata-Version: 2.0
Name: filters
Version: 1.2.2
Summary: Validation and data pipelines made easy!
Home-page: https://filters.readthedocs.io/
Author: Phoenix Zerin
Author-email: phoenix.zerin@eflglobal.com
License: MIT
Keywords: data validation
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Text Processing :: Filters
Requires-Dist: python-dateutil
Requires-Dist: pytz
Requires-Dist: regex
Requires-Dist: six
Provides-Extra: iso
Requires-Dist: filters-iso; extra == 'iso'

.. image:: https://travis-ci.org/eflglobal/filters.svg?branch=master
   :target: https://travis-ci.org/eflglobal/filters
.. image:: https://readthedocs.org/projects/filters/badge/?version=latest
   :target: http://filters.readthedocs.io/

=======
Filters
=======
The Filters library provides an easy and readable way to create complex
data validation and processing pipelines, including:

- Validating complex JSON structures in API requests or config files.
- Parsing timestamps and converting to UTC.
- Converting Unicode strings to NFC, normalizing line endings and removing
  unprintable characters.
- Decoding Base64, including URL-safe variants.

And much more!

The output from one filter can be "piped" into the input of another, enabling
you to "chain" filters together to quickly and easily create complex data
pipelines.

Examples
========
Validate a latitude position and round to manageable precision:

.. code:: python

   (
       f.Required
     | f.Decimal
     | f.Min(Decimal(-90))
     | f.Max(Decimal(90))
     | f.Round(to_nearest='0.000001')
   ).apply('-12.0431842')

Parse an incoming value as a datetime, convert to UTC and strip tzinfo:

.. code:: python

   f.Datetime(naive=True).apply('2015-04-08T15:11:22-05:00')

Convert every value in an iterable (e.g., list) to unicode and strip
leading/trailing whitespace.
This also applies `Unicode normalization`_, strips unprintable characters and
normalizes line endings automatically.

.. code:: python

   f.FilterRepeater(f.Unicode | f.Strip).apply([
     b'\xe2\x99\xaa ',
     b'\xe2\x94\x8f(\xc2\xb0.\xc2\xb0)\xe2\x94\x9b ',
     b'\xe2\x94\x97(\xc2\xb0.\xc2\xb0)\xe2\x94\x93 ',
     b'\xe2\x99\xaa ',
   ])

Parse a JSON string and check that it has correct structure:

.. code:: python

   (
       f.JsonDecode
     | f.FilterMapper(
         {
           'birthday':  f.Date,
           'gender':    f.CaseFold | f.Choice(choices={'m', 'f', 'x'}),

           'utcOffset':
               f.Decimal
             | f.Min(Decimal('-15'))
             | f.Max(Decimal('+15'))
             | f.Round(to_nearest='0.25'),
         },

         allow_extra_keys   = False,
         allow_missing_keys = False,
       )
   ).apply('{"birthday":"1879-03-14", "gender":"M", "utcOffset":"1"}')

============
Requirements
============
Filters is compatible with Python versions 3.6, 3.5 and 2.7.

============
Installation
============
Install the latest stable version via pip::

    pip install filters

Extensions
==========
The following extensions are available:

- `ISO Filters`_: Adds filters for interpreting standard codes and identifiers.
  To install::

     pip install filters[iso]

.. _ISO Filters: https://pypi.python.org/pypi/filters-iso
.. _Unicode normalization: https://en.wikipedia.org/wiki/Unicode_equivalence


