semvec/pypi-packages huggingface dataset:
feedzilla 0.24
Django application for ATOM/RSS feeds aggregation i.e. planet engine
License: BSD
Keywords: django application feeds syndication aggregation atom rss planet

============================
Feedzilla Django Application
============================

Changelog
=========


0.21::
------
* Bug fixes and a little code clean up
* pt_BR localization
* ``django-tagging`` replaced by ``django-taggit``
* Using tag slug in URL 


0.20::
----

* lxml instead BeautifulSoup
* New dependencies: lxml, grab
* Templates for ATOM/RSS feed moved to templates/feedzilla/feed directory


About feedzilla
===============

This is Django application that adds to your site ability to aggregate
ATOM/RSS feeds and display them in single stream. In other words you can
use feedzilla to build planet site.

Project page: http://bitbucket.org/lorien/feedzilla

Installation
============

* Use ``pip`` or ``easy_install`` to install *feedzilla* package.
* Install dependencies (see below).
* Add feedzilla to INSTALLED_APPS.
* Run ``manage.py syncdb`` or ``manage.py syncdb --migrate`` if you use South.
* Include ``url('', include('feedzilla.urls'))`` in url config.
* Setup Site instance via Django admin interface.
* Setup feedzilla settings via settings.py. See available settings below.
  You have to import default settings with ``from feedzilla.settings import *``
  line.
* Setup static files. You should copy or symlink ``static/feedzilla`` directory
  contents from feedzilla installation directory to your ``%MEDIA_ROOT%``.
* Play with templates. Probably you'll want override some of default templates.

Dependencies
============

See
* django-common
* django-taggit
* south
* feedparser
* lxml
* grab
* transliterate

Settings
========

* ``FEEDZILLA_PAGE_SIZE`` - number of items per page
* ``FEEDZILLA_SUMMARY_SIZE``
* ``FEEDZILLA_SITE_TITLE`` - used in feed generation
* ``FEEDZILLA_SITE_DESCRIPTION`` - used in feed generation

For actual list of settings look into ``feedzilla/settings.py``
Wiring-x86 1.0.0
A Python module to use most Arduino wiring functions on Intel® Arduino capable boards.
License: BSD

Wiring-x86
==========

Wiring-x86 is a Python module that lets you use Arduino like functionality on
Intel® Arduino capable boards such as:

* `Intel® Edison <http://www.intel.com/content/www/us/en/do-it-yourself/edison.html>`_
* `Intel® Galileo Gen2 <http://www.intel.com/content/www/us/en/do-it-yourself/galileo-maker-quark-board.html>`_ 
* `Intel® Galileo <http://www.intel.ie/content/www/ie/en/do-it-yourself/galileo-maker-quark-board.html>`_

It provides a simple and unified API (similar to the WiringPi module) to talk
to the GPIO pins on the board.

.. image:: https://raw.githubusercontent.com/emutex/wiring-x86/master/docs/source/_images/galileo1.jpg

At the moment the Wiring-x86 library provides support to:

-  Writing to a GPIO pin configured as output.
-  Reading from a GPIO pin configured as high impedance input.
-  Reading from a GPIO pin configured as pullup input.
-  Reading from a GPIO pin configured as pulldown input.
-  Reading from a GPIO pin configured as analog input (ADC).
-  Writing to a GPIO pin configured as analog output (PWM).

Here is a simple example:

.. code-block:: python

    # Import the time module enable sleeps between turning the led on and off.
    import time

    # Import the GPIOEdison class from the wiringx86 module.
    # In case you want to use a different board, simply the import right class
    # below. The API is unified for all supported boards.
    from wiringx86 import GPIOEdison as GPIO

    # Create a new instance of the GPIOEdison class.
    # Setting debug=True gives information about the interaction with sysfs.
    gpio = GPIO(debug=False)
    pin = 13
    state = gpio.HIGH

    # Set pin 13 to be used as an output GPIO pin.
    print 'Setting up pin %d' % pin
    gpio.pinMode(pin, gpio.OUTPUT)


    print 'Blinking pin %d now...' % pin
    try:
        while(True):
            # Write a state to the pin. ON or OFF.
            gpio.digitalWrite(pin, state)

            # Toggle the state.
            state = gpio.LOW if state == gpio.HIGH else gpio.HIGH

            # Sleep for a while.
            time.sleep(0.5)

    # When you get tired of seeing the led blinking kill the loop with Ctrl-C.
    except KeyboardInterrupt:
        # Leave the led turned off.
        print '\nCleaning up...'
        gpio.digitalWrite(pin, gpio.LOW)

        # Do a general cleanup. Calling this function is not mandatory.
        gpio.cleanup()

Full documentation can be found at
`wiring-x86 site <http://wiring-x86.readthedocs.org>`_ on Read the Docs.

The original YOCTO Linux OS provided by Intel® must be used. For more
information on how to get this software go to `Intel® Makers site
<https://communities.intel.com/community/makers>`_. This module will only work
with that combination of boards and OS since it uses specific Intel® GPIO
driver sysfs interface.
modelr 0.5.5
Web Service like google charts API
License: BSD

========================
Welcome to modelr server
========================

.. image:: https://img.shields.io/badge/license-Apache-blue.svg
    :target: https://github.com/agile-geoscience/modelr/blob/develop/LICENSE.md
    :alt: Apache 2 license

.. image:: http://img.shields.io/pypi/dw/modelr.svg
    :target: http://pypi.python.org/pypi/modelr/
    :alt: PyPI downloads
    
.. image:: https://img.shields.io/pypi/v/modelr.svg
    :target: http://pypi.python.org/pypi/modelr/
    :alt: PyPI version
    
.. image:: http://img.shields.io/github/issues/badges/modelr.svg
    :target: https://github.com/agile-geoscience/modelr
    :alt: GitHub issues

This is the documentation for the back-end modelr server software. You might be looking for `modelr.io <https://www.modelr.io/>`_

Modelr server is a Google-Charts-like API for geophysics! Submit tasks via a URL.

Example: 

* `<https://www.modelr.org/plot.jpeg?script=wedge_spatial.py&theta=0&f=25&colourmap=Greys&base1=variable-density&overlay1=none&base2=earth-model&overlay2=wiggle&opacity=0.5&Rock0=3000.0%2C1600.0%2C2500.0%2C%0A%09%20%2050.0%2C%2050.0%2C%2050.0&Rock1=2770.0%2C1780.0%2C2185.0%2C%0A%09%20%2050.0%2C%2050.0%2C%2050.0&Rock2=3000.0%2C1600.0%2C2500.0%2C%0A%09%20%2050.0%2C%2050.0%2C%2050.0&tslice=0.15&scale=1.0%2C99&type=scenario>`_

Full interface
+++++++++++++
* There's a full interface for modelr at `modelr.io <https://www.modelr.io/>`_

Prerequisites
++++++++++++++++

You will need scientific python (numpy, scipy, matplotlib), which come with
Enthought Canopy:  `<http://www.enthought.com>`_

They can alternatively be installed via pip, aptitude, ports, or sourced from git.

Additionally, ImageMagick will need to be installed in order to handle conversion of svg to png. Binaries can be downloaded from the ImageMagick website: 
`<http://www.imagemagick.org/script/binary-releases.php#unix>`_

ImageMagick can also be installed via ports or aptitude.

Other python packages that will be automatically installed during setup:

* agilegeo
* pypng
* requests
* jinja2
* svgwrite

Links
+++++++++++

* `Agile Geoscience <http://www.agilegeoscience.com>`_
* `Homepage <http://agile-geoscience.github.com/modelr/>`_
* `Issue Tracker <https://github.com/agile-geoscience/modelr/issues/>`_
* `PyPi <http://pypi.python.org/pypi/modelr/>`_
* `Github <https://github.com/agile-geoscience/modelr>`_

Authors
++++++++++++++++

* `Matt Hall <https://github.com/kwinkunks>`_ @ `Agile Geoscience <http://www.agilegeoscience.com>`_
* `Sean Ross-Ross <https://github.com/srossross>`_ @ now at `Continuum`
* `Evan Bianco <https://github.com/EvanBianco>`_ @ `Agile Geoscience <http://www.agilegeoscience.com>`_
* `Ben Bougher <https://github.com/ben-bougher>`_