semvec/pypi-packages huggingface dataset:
wapps 0.1.2.dev0
Some Wagtail reusable applications
License: MIT
Keywords: wagtail

WApps
=====

`![CircleCI <https://img.shields.io/circleci/project/github/apihackers/wapps.svg>`_](https://circleci.com/gh/apihackers/workflows/wapps)
`![codecov <https://codecov.io/gh/apihackers/wapps/branch/master/graph/badge.svg>`_](https://codecov.io/gh/apihackers/wapps/branch/master)
`![Last version <https://img.shields.io/pypi/v/wapps.svg>`_](https://pypi.python.org/pypi/wapps)
`![License <https://img.shields.io/pypi/l/wapps.svg>`_](https://pypi.python.org/pypi/wapps)
`![Supported Python versions <https://img.shields.io/pypi/pyversions/wapps.svg>`_](https://pypi.python.org/pypi/wapps)

A very optionated set of Wagtail reusable applications and helpers
meant to speedup website development. There is not any universality intent.

stack
-----

It assumes the following stacks:

Server-side stack:
******************

- Python 3
- Latest Wagtail and Django versions
- Django-Jinja for template rendering
- Django-Babel for localization
- Django-Appconf for default settings

Frontend Stack
**************

- Vue 2 for front components
- Webpack 3 as front build toolchain
- SCSS as style language
- Bootstrap and Font-awesome as base frameworks

Requirements
------------

Wapps is designed to work with Python 3, Django-jinja, Django-babel and latest Django and Wagtail versions.

Wapps also provides JS/Vue2 helpers and scss mixins and classes

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

Python installation
*******************

Install it with pip:

.. code-block:: shell

    $ pip install wapps
    


then add the required bases apps to your settings (ie. `settings.py`):

.. code-block:: python

    INSTALLED_APPS = [
        '...',
        'wapps',
        'memoize'
    ]
    


Node modules installation
*************************

Install it with `npm` or `yarn`

.. code-block:: shell

    $ npm install wapps@<wapps-version>
    


Changelog
=========

Current
-------

- Initial release
corenlp-protobuf 3.8.0
Python bindings for Stanford CoreNLP protobufs
License: MIT
Keywords: protobuf corenlp natural-language-processing nlp

Stanford CoreNLP Python Bindings
================================

.. image:: https://travis-ci.org/stanfordnlp/python-corenlp-protobuf.svg?branch=master
    :target: https://travis-ci.org/stanfordnlp/python-corenlp-protobuf

This package contains python bindings for `Stanford
CoreNLP <https://github.com/stanfordnlp/CoreNLP>`_'s protobuf
specifications, as generated by `protoc`. These bindings can used to
parse binary data produced by, e.g., the `Stanford CoreNLP
server <https://stanfordnlp.github.io/CoreNLP/corenlp-server.html>`_.

----

Usage:

.. code-block:: python
  
  from corenlp_protobuf import Document, parseFromDelimitedString

  # document.dat contains a serialized Document.
  with open('document.dat', 'r') as f:
    buf = f.read()
  doc = Document()
  parseFromDelimitedString(doc, buf)

  # You can access the sentences from doc.sentence.
  sentence = doc.sentence[0]

  # You can access any property within a sentence.
  print(sentence.text)

  # Likewise for tokens
  token = sentence.token[0]
  print(token.lemma)

See `test_read.py` for more examples.
pyllist 0.3
Linked list data structures (in pure Python)
License: MIT
Keywords: linked list

pyllist - linked lists for Python
=================================

pyllist is a Python module providing basic linked list data structures.
Collections implemented in the pyllist module perform well in problems
which rely on fast insertions and/or deletions of elements in
the middle of a sequence.
For this kind of workload, they can be faster than collections.deque
or standard Python lists.

This extension requires Python 2.x or 3.x. It should work with any
implementation (tested with CPython and PyPy).
Note however, that for CPython there is a much faster C extension
module with the same API at http://github.com/ajakubek/python-llist/

Currently pyllist provides the following types of linked lists:
 - dllist - a doubly linked list
 - sllist - a singly linked list

Full documentation of these classes is available at:
http://packages.python.org/pyllist/

To install this package, either run "pip install pyllist",
or download it manually from http://pypi.python.org/pypi
then unpack the sources and compile them with "python setup.py install".

The most current development version is available at:
https://github.com/rgsoda/pypy-llist/

Bugs can be reported at:
https://github.com/rgsoda/pypy-llist/issues

This software is distributed under the MIT license.
Please see the LICENSE file included in the package for details.
persefone 0.2.0
Encoder for the Siren hypermedia format
License: MIT

Persefone
=========
|Pypi| |Travis|

Persefone is an encoder for the `Siren <https://github.com/kevinswiber/siren>`_
hypermedia format that uses ujson to generate Siren-compliant JSON efficiently.

Usually such encoders work with JSON, so you convert your data to JSON and pass
it to the encoder.

The idea behind persefone is to provide a perfomant Siren encoder by removing
the JSON conversion step: you pass your data as provided by your ORM and
persefone deals with that, returning JSON.


Supported orms and data structures
##################################

Persefone currently supports only peewee, but I plan to add support for other
ORMs and similar tools.res

Usage
#####

Install with pip::

    pip install persefone


Then::

    from persefone.peewee import Siren

    Siren(data, '/path', model=MyModel).encode() # returns Siren-valid JSON


If you have a list::

    Siren([item, ...], '/path', model=MyModel)

Pagination::

    Siren([item, ...], '/path', model=MyModel, total_items=100, current_page=2)


Contributing
############
Contributions and feedbacks are welcome. You can just open an issue.


.. |Pypi| image:: https://img.shields.io/pypi/v/persefone.svg?maxAge=3600&style=for-the-badge
   :target: https://pypi.python.org/pypi/persefone

.. |Travis| image:: https://img.shields.io/travis/Vesuvium/persefone.svg?maxAge=3600&style=for-the-badge
   :target: https://travis-ci.org/Vesuvium/persefone