semvec/pypi-packages huggingface dataset:
django-designer 0.2.1
Django template renderer for designers
License: MIT

===============
django-designer
===============

Allow designers to work on your templates without having to run
the Django development server, database etc.

Designer's workflow:

#. Pulls repo
#. Edits template, makes it look pretty
#. Runs manage.py command to render template and produce html file
#. Points browser to file
#. Views pretty rendered template in browser
#. Repeats steps 2 and 3, refreshes browser
#. Commits and pushes pretty templates

Note: To state the obvious, context variables are not rendered on page.
View functions are not called.  Context variables are often not needed
when a desinger is viewing templates for design purposes.

-------
Install
-------
Install package::

    pip install django-designer

-----
Usage
-----
Run::

    $ ./manage.py render_template your_app/templates/home.html
    file:///Users/you/Projects/your_project/your_app/templates/home_rendered.html

Copy-paste output into browser address bar and view rendered template.

Recommend you add ``*_rendered.html`` to your .gitignore.
flask-funktional-gae 0.0.1
flask-funktional-gae
~~~~~~~~~~~~~~~~~~~~

flask extension to make functional testing of flask applications with the
app engine sdk easier.

used on top of the `flask-funktional <http://github.com/gregorynicholas/flask-funktional>`_ extension, it provides setup of app engine sdk stubs with
a focus on being transparent and minimally invasive.


links
`````

* `docs <http://gregorynicholas.github.io/flask-funktional-gae>`_
* `source <http://github.com/gregorynicholas/flask-funktional-gae>`_
* `package <http://packages.python.org/flask-funktional-gae>`_
* `travis-ci <http://travis-ci.org/gregorynicholas/flask-funktional-gae>`_
License: MIT

flask-funktional-gae

====================



[flask](http://flask.pocoo.org) extension to make functional testing of flask

applications with the [app engine sdk](http://appengine.google.com) easier.





[![Build Status](https://secure.travis-ci.org/gregorynicholas/flask-funktional-gae.png?branch=master)](https://travis-ci.org/gregorynicholas/flask-funktional-gae)





* [docs](http://gregorynicholas.github.io/flask-funktional-gae)

* [source](http://github.com/gregorynicholas/flask-funktional-gae)

* [package](http://packages.python.org/flask-funktional-gae)

* [changelog](https://github.com/gregorynicholas/flask-funktional-gae/blob/master/CHANGES.md)

* [travis-ci](http://travis-ci.org/gregorynicholas/flask-funktional-gae)





-----





### getting started



install with *pip*:



    pip install flask-funktional-gae==0.0.1





-----





### overview



used on top of the [`flask-funktional`](http://github.com/gregorynicholas/flask-funktional)

extension, it provides setup of app engine sdk stubs with a focus on being

transparent, seamless, and minimally invasive.





### features



* [todo]





-----





### example usage



    from flask.ext import funktional

    from flask.ext import funktional_gae





    # define a test Flask application..

    app = Flask(__name__)

    app.debug = True

    app.request_class = funktional.FileUploadRequest





    class TestCase(funktional.TestCase):

      def test_upload_returns_valid_blob_result(self):

        data, filename, size = funktional.open_test_file('test_file.jpg')

        response = app.test_client().post(

          data={'test': (data, filename)},

          path='/test_upload1',

          headers={},

          query_string={})

        self.assertEqual(200, response.status_code)
flask-funktional 0.0.1
flask-funktional
~~~~~~~~~~~~~~~~

flask extension which hopes to make functional testing easier.

links
`````

* `documentation <http://gregorynicholas.github.io/flask-funktional>`_
* `package <http://packages.python.org/flask-funktional>`_
* `source <http://github.com/gregorynicholas/flask-funktional>`_
* `development version
  <http://github.com/gregorynicholas/flask-funktional>`_
License: MIT

flask-funktional
================

[flask](http://flask.pocoo.org) extension which hopes to make functional testing easier.


[![Build Status](https://secure.travis-ci.org/gregorynicholas/flask-funktional.png?branch=master)](https://travis-ci.org/gregorynicholas/flask-funktional)


* [docs](http://gregorynicholas.github.io/flask-funktional)
* [source](http://github.com/gregorynicholas/flask-funktional)
* [package](https://pypi.python.org/pypi/flask-funktional)
* [changelog](https://github.com/gregorynicholas/flask-funktional/blob/master/CHANGES.md)


-----


### getting started

install with *pip*:

    pip install flask-funktional

-----


### features

* completely seamless
    * nifty pre / post class setup code means you don't have to make repetitive `super()` calls.
    * focus on signals + hooks to help avoid having to write shitty code in your subclasses.
* enables and promotes the healthy use of `url_for` instead of hard coding url paths.
    * boom, less brittle code.
    * oddly, there's a lot of things that go wrong out of the box with this, so funktional removes all of this shity setup code from your actual test code.
* test file uploads in flask applications. right ouf of the box.
    * perfect for your [shitty] little csv uploader tools.
* cross platform
    * works in any standard python flask application + platform, such as amazon or google app engine.
participation 0.1.dev1
Participation is a python package for social participation ontologies, rdf data (linked data) triplification and analysis
License: MIT
Keywords: complexity networks human interaction physics data text mining analysis visualization music physics synthesis toolbox semantic web linked data owl ontology social participation

==================================================================
Social participation data analysis and exploitation
==================================================================

Routines for analysis and synthesis of RDF social participation data.
Idealized facilites include:

   - Observance of expected stability and overall measures of each instance.
   - Integration of data from a number of instances.
   - Integration of data from a usual social platforms (Facebook, Twitter, LinkedIn).
   - Recommendation of resources through topological and textual criteria, with explicit routines and potential uses.
   - Synthesis of audiovisual artifacts to ease observation, probing and exploitation.
   - Translation of participatory data to RDF.
   - HTTP utilities, such as bootstrapping participatory ontologies or an access to resource recommendation routines.

Public data, such as provided by the Gmane database or donated profiles from private networks (e.g. Facebook), or gathered by Twitter, can be incorporated as RDF in the Social Graph.

Usage example
=================

.. code:: python

    import participation as P

    # downloads Social Participation data from Participabr,
    # Cidade Democrática and AA from datahub.io
    P.download()

    # The triplification routines are available:
    # accesses Participa.br data on PostgreSQL and save RDF Xml and Turtle
    P.triplification.ParticipaTriplification("dbname","username")
    # accesses Participa.br data on PostgreSQL and save RDF Xml and Turtle
    P.triplification.AATriplification("dbname","username","dbname2","username2","ircLog.txt")
    # accesses Participa.br data on PostgreSQL and save RDF Xml and Turtle
    P.triplification.OCDTriplify("dbname","username")

    # print number of users in each RDF graph
    # print number of incidences of each
    # print vocabulary

    import social as S
    # To load GDF file:
    fg=S.GDFgraph("../data/RenatoFabbri06022014.gdf") # graph should be on fg.G
    # find posts by friends with similar names

    # To make an abstract animation with the overall network:
    song=S.FSong(fg.G,"fsong/",True,True,False,True)
    # Check mixedVideo.webm

    # Add information about users that are equivalent (through RDF).
    # make network with and without that information

    # Make recommendation based on a target resource
    # Make recommendation of percolatory method

    # Rise a flask instance, point an example meteor interface

    # more ***under construction***
    # Enjoy!