semvec/pypi-packages huggingface dataset:
Flask-DataTables-peewee 0.1.2
Flask integration with DataTables and peewee.
License: BSD 3-Clause License
Requires Python: >=3.6
Keywords: flask,peewee,datatables

Flask & peewee integration with DataTables server-side processing
=================================================================

As `DataTables`_ is a quite power and useful JavaScript library for manipulating
and displaying data, we intended to make integration of the client-side DataTables
scripts with the server-side processing based on ``Flask`` and ``peewee``.

Installation
------------

   **Note**

   As we have noticed, there's already a ``Flask-DataTables`` library available
   on `PyPI`_. However, this package was intended for integration with ``SQLAlchemy``
   instead of ``peewee``.

   .. _PyPI: https://pypi.org/project/Flask-DataTables/

To start with, simply install the ``Flask-DataTables`` package from
`PyPI <https://pypi.org/project/Flask-DataTables-peewee>`__:

.. code-block:: shell

   pip install Flask-DataTables-peewee

or should you prefer the bleeding edge version:

.. code-block:: shell

   git clone https://github.com/JarryShaw/Flask-DataTables.git
   cd Flask-DataTables
   pip install .

Usage
-----

``Flask-DataTables`` is quite simple to use, just declare your data model in
the preferable way from ``peewee`` and voilà, that's it.

Taking examples from the ``peewee`` `documentation <http://docs.peewee-orm.com/en/latest/peewee/playhouse.html>`__,
we can have a `DataTables`_ integrated data model just as below:

.. code-block:: python

   from flask import Flask
   from flask_datatables import (CharField, DataTable, DateTimeField,
                                 ForeignKeyField, Metadata, TextField)

   DATABASE = 'postgresql://postgres:password@localhost:5432/my_database'

   app = Flask(__name__)
   app.config.from_object(__name__)

   db_wrapper = DataTable(app)


   class User(db_wrapper.Model):
       username = CharField(unique=True)

       class Meta(Metadata):
           datatables = True


   class Tweet(db_wrapper.Model):
       user = ForeignKeyField(User, backref='tweets')
       content = TextField()
       timestamp = DateTimeField(default=datetime.datetime.now)

       class Meta(Metadata):
           datatables = True

And now, you may simply call ``Tweet.search()`` to perform the server-side
processing queries.

   **See Also**

   It is also possible to customise the orderable and/or searchable
   fields through ``flask_datatables.fields.Field`` parameters,
   and their corresponding behaviours by subclassing the
   ``flask_datatables.fields.Field`` classes.

.. _DataTables: https://datatables.net/
jwz 0.1.0
Email message threading algorithm by JWZ.
License: BSD 3-Clause License
Requires Python: >=3.6
Keywords: email,threading

Email message threading algorithm by JWZ.

The implementation is based on JavaScript implementation of the `JWZ algorithm`_
by Max Ogden (`@maxogden`_) on `GitHub`_.

.. _JWZ algorithm: https://www.jwz.org/doc/threading.html
.. _@maxogden: https://github.com/maxogden
.. _GitHub: https://github.com/maxogden/conversationThreading-js